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Article Contents

Introduction, limitations, acknowledgments, supporting information, the effects of organic food on human health: a systematic review and meta-analysis of population-based studies.

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Bibo Jiang, Jinzhu Pang, Junan Li, Lijuan Mi, Dongmei Ru, Jingxi Feng, Xiaoxu Li, Ai Zhao, Li Cai, The effects of organic food on human health: a systematic review and meta-analysis of population-based studies, Nutrition Reviews , Volume 82, Issue 9, September 2024, Pages 1151–1175, https://doi.org/10.1093/nutrit/nuad124

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Although the nutritional composition of organic food has been thoroughly researched, there is a dearth of published data relating to its impact on human health.

This systematic review aimed to examine the association between organic food intake and health effects, including changes in in vivo biomarkers, disease prevalence, and functional changes.

PubMed, EMBASE, Web of Science, the Cochrane Library, and ClinicalTrials.gov were searched from inception through Nov 13, 2022.

Both observational and interventional studies conducted in human populations were included, and association between level of organic food intake and each outcome was quantified as “no association,” “inconsistent,” “beneficial correlation/harmful correlation,” or “insufficient”. For outcomes with sufficient data reported by at least 3 studies, meta-analyses were conducted, using random-effects models to calculate standardized mean differences.

Based on the included 23 observational and 27 interventional studies, the association between levels of organic food intake and (i) pesticide exposure biomarker was assessed as “beneficial correlation,” (ii) toxic metals and carotenoids in the plasma was assessed as “no association,” (iii) fatty acids in human milk was assessed as “insufficient,” (iv) phenolics was assessed as “beneficial”, and serum parameters and antioxidant status was assessed as “inconsistent”. For diseases and functional changes, there was an overall “beneficial” association with organic food intake, and there were similar findings for obesity and body mass index. However, evidence for association of organic food intake with other single diseases was assessed as “insufficient” due to the limited number and extent of studies.

Organic food intake was found to have a beneficial impact in terms of reducing pesticide exposure, and the general effect on disease and functional changes (body mass index, male sperm quality) was appreciable. More long-term studies are required, especially for single diseases.

PROSPERO registration no. CRD42022350175.

Organic agriculture is an ecological production management system that emphasizes rotating crops, managing pests naturally, diversifying crops and livestock, and improving the soil with compost additions and animal and green manures. 1 All food sold as organic must be certified as such by approved organic food control bodies according to defined criteria. 2 With an increase of 14 billion euros, in 2020 the global market for organic food saw its largest year of growth ever, surpassing 120 billion euros. 1

Belief that organic food is healthier than conventional food is one of the key reasons why people consume it. 3 Organic farming imposes restrictions on the use of antibiotics and pesticides. Several research groups have explored differences in pesticide residue concentrations between organic and conventional products, their findings indicating that organic production results in lower levels of pesticide residues. 4–6 Moreover, organic food may contain more beneficial nutrients or phytochemicals. Organic milk has higher concentrations of beneficial fatty acids compared with conventional milk, 7 , 8 and higher levels of polyphenols have been detected in organically grown tomatoes, blue honeysuckle, and apples. 9 , 10

However, the potential health benefits of organic food remain unclear. Previous systematic reviews have mostly focused on differences in nutrition or pesticide residue concentrations between conventionally produced foods and those produced using organic agriculture. Some meta-analyses have concluded that organic food has a lower risk of being contaminated with detectable pesticide residues, and that there are higher PUFA levels in organic meat. 4 , 11 Średnicka-Tobe et al aimed to determine the direct health effects of organic food intake, but were unable to perform a quantitative analysis due to the lack of studies and high level of heterogeneity in those studies. 11 Another systematic review expanded the breadth of the evidence examined related to human health outcomes, including potential changes in the preclinical stage, such as total antioxidant status, carotenoids, but no quantitative results were obtained. 12 A recent meta-analysis found that organic food consumption was associated with a modest reduction (11%) in the risk of obesity. 13 However, the meta-analysis only focused on obesity, and the 4 included studies were observational only and of moderate quality, with significant heterogeneity.

Thus, there is a need for further investigation of the potential health effects of organic food, especially given the growing consciousness among consumers of the environmental impacts of food production. The present study aimed to examine the direct clinical impact of organic food intake on human health by including assessment of potential preclinical biomarker changes in vivo, detectable functional changes, and disease outcomes. Furthermore, classification criteria were established to categorize the association between the consumption of organic food and health outcomes.

Search strategy

The review was registered with PROSPERO (CRD42022350175) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. 14 Four electronic databases (PubMed, EMBASE, Cochrane, and Web of Science) were searched for relevant studies from their years of inception up to November 13, 2022. The gray literature was searched on ClinicalTrials.gov to avoid publication bias. Individualized search strategies for the various databases included combinations of terms related to organic food and health outcomes. An example search strategy can be found in Appendix S1 in the Supporting Information online.

Inclusion and exclusion criteria

Both observational and interventional studies performed in humans were identified. The route of intervention/exposure to organic food was limited to dietary intake, and there was no restriction on the food type. For inclusion, studies needed to report differences in outcomes between groups, or risk estimates (odds ratio [OR], relative ratio [RR] or hazard ratio [HR]) for organic food intake. Outcomes studied included diseases (body mass index [BMI] and male sperm quality), in vivo biomarkers, and physiological biochemical parameters. Only English language articles were included. Studies were excluded if there was no description about the route of exposure to / intervention with organic food ( Table 1 ) .

PICOS criteria for inclusion of studies

Data extraction

Title scans and abstract reviews were conducted by 2 investigators independently, and the full text of all included studies was evaluated based on the inclusion and exclusion criteria. Discrepancies were resolved by discussion until a consensus was reached. Data were extracted by a research assistant (J.B.) and checked by another reviewer (L.X.). Information describing the study sample (sample size, age, sex, geographic region, and health condition), study design (study type, exposure or intervention duration, groups, and organic food types), and outcomes (specimen types, outcome indicators, and conclusions) were extracted. Moreover, the values of outcome indicators before and after the intervention in the single interventional study (at baseline and follow-up in cohort studies) were collected, including the subgroup data.

Risk-of-bias assessment

The risk of bias of the clinical trial study was assessed using the The Cochrane Risk of Bias Assessment Tool. 15 The observational studies were assessed using the Newcastle–Ottawa Quality Assessment Form and the Specialist Unit for Review Evidence (SURE) checklist. 16 , 17 Two reviewers participated in the assessment of bias risk, and any disagreement was settled by discussion.

Data synthesis and meta-analyses

Outcomes were categorized into 2 categories: (I) biomarkers (pesticide exposure; toxic metals; fatty acids in human milk; nutrients in plasma; serum parameters; and total antioxidant status) and (II) disease and functional change (BMI, male sperm quality).

The included studies were coded and the data subsequently classified and summarized to determine the associations between organic food intake and outcomes ( Table 2 ); the coding and classification method used was first described by James. 18 Briefly, the evidence for an association was defined as “insufficient” if it was indicated by 3 or fewer studies. If the association was indicated by more than 3 studies, the results were classified based on the percentage of studies reporting statistically significant results as follows: (1) “no association” if less than 30% of the studies reported a significant association; (2) “inconsistent” if the significant association was reported in 34% to 59% of the studies; (3) “beneficial/harmful correlation” if over 60% of the studies reported a significant association. Whether the correlation was considered beneficial or harmful was based on the direction of the reported correlation. The “beneficial/harmful correlation” assessment was not completely equivalent to the assessment of “positive/negative correlation” between organic food and outcomes. For example, when the outcome was pesticide exposure, a “beneficial correlation” indicated that organic food consumption led to a reduction in pesticide exposure (a numerically negative correlation). The same coding was also applied to the subgroup analysis of study type to examine whether the findings were influenced or not.

Classifying criteria for association level between organic food intake and outcomes

The correlation was rated as a “Beneficial correlation” when the organic food was associated with a more favourable outcome; otherwise, it was rated as a “Harmful correlation”.

All analyses were performed using Stata software version 14.2, and standardized mean differences (SMDs) were calculated using random-effects models for outcomes with at least 3 studies reporting sufficient data. Differences were calculated as levels for the organic diet group minus levels for the conventional diet group. Heterogeneity was determined using Cochran’s Q statistic and I 2 values ( I 2 values of 25, 50, and 75 were considered as indicating low, moderate, and high heterogeneity, respectively).

Literature search and study characteristics

A total of 13 060 relevant articles were identified after searching. Following the removal of duplicates and initial screening of titles and/or abstracts, 50 studies were included ( Figure 1 ). 19–68 Twenty-seven of the included studies were interventional trials and used traditional food as a control diet. 18–30 , 46 , 49 , 52 , 53 , 55–58 , 60 , 61 , 63 , 65–67 Most of the studies were conducted in Europe 18–23 , 26–28 , 30–45 , 50–53 , 55 , 57 , 62 , 64 , 66 , 67 and the United States 24 , 25 , 45–48 , 54 , 59–61 , 63 , 65 ; 2 were conducted in Brazil, 29 , 56 1 in Japan, 58 and 1 in Australia. 49 Eleven studies were conducted in children, 24 , 25 , 40 , 41 , 46 , 48 , 53 , 60 , 64 , 65 , 67 4 were in pregnant women, 35–37 , 51 and 2 were in senior men. 54 , 59 The main characteristics of the included studies are summarized ( Table 3 ), 18–67 and the results of the classification of the association levels are shown in Table 4 . 18–67 The subgroup analysis of the study types is presented in Table 5 . 18–67 The results of the risk-of-bias assessment indicate that more than half of the trials had a high risk of bias in terms of blinding. The reporting bias of the majority of the trials was assessed as low risk (see Figure S1 in the Supporting Information online).

Flowchart of search and selection process.

Main characteristics of studies examining the health effects of organic food on humans

Whether there were statistically significant differences in outcomes before and after organic food intervention (or between the organic food group and the conventional food group): correlation between organic food and positive outcomes is indicated by “+”, and correlation between organic food and negative outcomes is indicated by “–”; “0” indicates that there were no statistically significant differences between groups.

Sixteen categories of labeled organic products: fruits; vegetables; soy-based products; dairy products; meat and fish; eggs; grains and legumes; bread and cereals; flour; vegetable oils and condiments; ready-to-eat meals; coffee, tea, and herbal tea; wine; biscuits, chocolate, sugar, and marmalade; other foods; and dietary supplements.

Specific criteria for grouping: (1) conventional (ie, 50% of both the meat and dairy they consumed was of organic origin, or they ate no meat and 50% of the dairy they consumed was of organic origin, or they ate no dairy and 50% of the meat they consumed was of organic origin); (2) 50%–90% organic (ie, 50% of both the meat and dairy they consumed was of organic origin, but 90% of either meat or dairy was of organic origin, or they ate no meat and 50%–90% of the dairy they used was of organic origin, or they ate no dairy and 50%–90% of the meat they consumed was of organic origin); (3) 90% organic (ie, 90% of both the meat and dairy they consumed was of organic origin, or they ate no meat and 90% of the dairy they consumed was of organic origin, or they ate no dairy and 90% of the meat they consumed was of organic origin); (4) other (including any combination of 50% meat of organic origin and 50% dairy of organic origin or vice versa, and missing and inconsistent data). Abbreviations : BLS, beet leaves and stalks; BMI, body mass index; C, conventional agricultural system; CCF, commercial complementary food; CKD, chronic kidney disease; Cu, copper; ED, erectile dysfunction; GDM, gestational diabetes; HDL, high-density lipoprotein; IFN, interferon; IgE, immunoglobulin E; IL, interleukin; LDL, low-density lipoprotein; MDA, malondialdehyde; MDOO, meat and dairy products of organic origin; MedDiet, Mediterranean diet; MetS, metabolic syndrome; mo, month(s); NS, not stated; OA, organic agricultural system using animal manure; OB, organic agricultural system using cover crops; OM, otitis media; OP, organophosphate; OR, odds ratio; Org-FFQ, organic FFQ; OS, organic food score; Pb, lead; RR, relative risk; WBC, white blood cell; %Df, a decreasing detection frequency; 2,4,5-T, 2,4,5-Trichlorophenoxy acetic acid; 2,4-D, 2,4-Dichlorophenoxyacetic acid; 2-AAS, 2-aminoadipic semialdehyde; 3M-4NP, 3-Methyl-4-nitrophenol; 3-PBA, 3-phenoxybenzoic acid; 4-F-3-PBA, 4-fluoro-3-phenoxybenzoic acid; 4NP, Amino-methyl-phosphoric acid; 5OH-Imd, 5-Hydroxy-Imidacloprid; 5OH-TBZ, 5-Hydroxy-Thiabendazole; 6-CNA, 6-Chloronicotinic acid; 8-OHdG, 8-hydroxy-20-deoxyguanosine; ACE, acetamiprid; AMPA, aminomethylphosphonic acid; AOA, total antioxidant activity; BMI z-scores, age-and sex-standardized BMI z-scores; Br2CA, cis-3-(2,2-dibromovinyl)-2,2-dimethylcyclopropane carboxylic acid; CAT, catalase; CCC, Chlormequat; Cd, cadmium; cDCCA, cis-2,2-(Dichloro)-2-dimethyl vinyl cyclopropane carboxylic acid; Cl2CA, cis-/trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid; CLA, conjugated linoleic acid isomers; CLO, clothianidin; CMHC, 3-chloro-4-methyl-7-hydroxycoumarin; CPMO, Chlorpyrifos-methyl-oxon; CPO, Chlorpyrifos-oxon; CRP, C-reactive protein; CysC, cystatin C; DAPs, dialkylphosphates; DEAMP, 2-(diethylamino)-6-methylpyrimidin-4-ol/one; DEAMPY, 2-diethylamino-6-methylpyrimidin-4-ol; DEDTP, diethyldithiophosphate; DEP, diethylphosphate; DETP, diethylthiophosphate; DIN, dinotefuran; dm-ACE, N-dm_acetamiprid; DMDTP, dimethyldithiophosphate; DMP, dimethylphosphate; Eps, diethylphosphates; FFQ, Food frquency questionnaire; F-PBA, 4-fluoro-3-phenoxybenzoic acid; GLY, N-(phosphonomethyl)glycine; GPx, glutathione peroxidase; GR, glutathione reductase; GSH, reduced glutathione; GSH-Px, glutathione peroxidase; IMI, imidacloprid; IMPY, 2-isopropyl-6-methyl-pyrimidin-4-ol; m-PBA, 3-Phenoxybenzoic acid; NIT, nitenpyram; ORAC, oxygen radical absorbance capacity; PABA, p-amino benzoic acid; PBMC, peripheral blood mononuclear cells; PNP, para-nitrophenol; SOD, superoxide dismutase; TAC, total antioxidant capacity; TAG, triglyceride; t-CDCA, trans-Chrysanthemumdicarboxylic acid; TCHP, 3,5,6-Trichloro-6-hydroxypyridine; TCP, thiacloprid; TCPY, 3,5,6-trichloro-2-pyridinol; tDCCA, trans-2,2-(Dichloro)-2-dimethyl vinyl cyclopropane carboxylic acid; TEAC, Trolox equivalent antioxidative capacity; tHcy, total plasma homocysteine; TNF, tumor necrosis factor; total DEs, total DEs = DEP+ DETP + DEDTP; total DMs, total DEs = DMP+ DMTP + DMDTP; TTCA, 2-Thio thiazolidin-4-carboxylic acid; TVA, trans-vaccenic acid; UPRE, urinary pesticide residue excretion; FRAP, ferric-reducing ability of plasma; ORAC, oxygen radical absorbance capacity; CAT, catalase; GSH-Px, glutathione peroxidase; eSOD, erythrocytesuperoxide dismutase; eCAT, erythrocyte catalase; eTBARS, erythrocyte thiobarbituric acid reactive substances; PBMC, peripheral blood mononuclear cells

Summary of studies examining the relationship between organic food intake and potential health effects

ID refers to the included study’s reference number.

Abbreviations : FRAP, ferric-reducing ability of plasma; ORAC, oxygen radical absorbance capacity; TEAC, Trolox equivalent antioxidative capacity; CuZn-SOD, copper zinc-superoxide dismutase; CAT, catalase; GSH-Px, glutathione peroxidase; GR, glutathione reductase; MDA, malondialdehyde; 2-AAS, 2-aminoadipic semialdehyde; eSOD, erythrocytesuperoxide dismutase; eCAT, erythrocyte catalase; eTBARS, erythrocyte thiobarbituric acid reactive substances; PBMC, peripheral blood mononuclear cells.

N = the total number of studies that include this outcome, n = the number of studies which reported statistical difference.

The association level rated according to the criteria listed in Table 2 .

Including fatty acids in the plasma, vitamin A, vitamin C, vitamin E, and inorganic elements.

Including glucose, triacylglycerol, cholesterol, urea, uric acid, high-density-lipoprotein cholesterol, low-density-lipoprotein cholesterol, C-reactive protein, cystatin C, and creatinine.

Including FRAP, ORAC, TEAC, DNA strand breaks, CuZn-SOD, CAT, GSH-Px, GR, MDA, 2-AAS, eSOD, eCAT activities, eTBARS, PBMC proliferation, percentages of NK cells, the lytic activity of NK cells, cytokine secretion, and Tumor Necrosis Factor α.

The directions of the results in these 2 studies were opposite; a detailed description has been provided in Table 3 .

There was a favorable association between organic food intake and this outcome.

Subgroup analysis of studies examining the relationship between organic food intake and potential health effects

N = the total number of studies that include this outcome, n = the number of studies that reported statistical difference.

Including fatty acids in plasma, vitamin A, vitamin C, vitamin E, and inorganic elements.

Including glucose, triacylglycerol, cholesterol, urea, uric acid, high-density-lipoprotein cholesterol, low-density-lipoprotein cholesterol, C-reactive protein, cystatin C, creatinine.

Including FRAP, ORAC, TEAC, DNA strand breaks, CuZn-SOD, CAT, GSH-Px, GR, MDA, 2-AAS, eSOD, eCAT activities, eTBARS, PBMC proliferation, percentages of NK cells, the lytic activity of NK cells, cytokine secretion, Tumor Necrosis Factor α.

The directions of the results in the 2 studies was different; a detailed description has been provided in Table 3 or in the “Results.”

This study (ID 37) is a case–control study.

Indicating that the outcome was associated with organic food.

Pesticide exposure

Sixteen studies investigated changes in pesticide exposure biomarkers in response to organic food consumption ( Table 4 ). 24 , 25 , 30 , 34 , 45–49 , 52 , 53 , 57 , 58 , 60 , 61 , 65 Overall, the level of association classification was rated as “beneficial”, and this beneficial association was consistent for the interventional trials ( Table 5 ). These studies measured various biomarkers related to pesticide exposure, including organophosphorus (11), 24 , 25 , 30 , 33 , 46–49 , 52 , 57 , 60 pyrethroid (6), 33 , 46 , 52 , 53 , 57 , 60 neonicotinoid (4), 52 , 53 , 58 , 60 glyphosate (2), 45 , 61 herbicides (3), 46 , 52 , 60 plant growth regulators (1), 52 and fungicides (1). 52

Of these 16 studies, 12 were interventional trials, 24 , 25 , 30 , 46 , 49 , 52 , 53 , 57 , 58 , 60 , 61 , 65 3 were cross-sectional studies, 45 , 47 , 48 and 1 was a cohort study. 34 All interventional trials reported statistically significant results. The interventions primarily involved the consumption of organic vegetables and fruits, and 5 studies did not specify the type of food used. 30 , 49 , 53 , 58 , 65 The duration of the interventions ranged from 5 days to 24 weeks. 46 , 57 Six trials were conducted in adults 30 , 34 , 45 , 47 , 49 , 52 and 5 in children. 24 , 25 , 46 , 48 , 53

Due to the limited number of studies with sufficient data, meta-analysis was only carried out for 3,5,6-trichloro-2-pyridinol (TCPy), a biomarker for organophosphorus pesticide exposure, based on 3 studies. 24 , 57 , 60 The meta-analysis revealed no statistically significant difference in the urinary concentration of TCPy between the group consuming organic food and the group consuming conventional food (SMD: –.57, 95% CI: –1.38, .25) ( Figure 2 ).

Meta-analysis of the effect of organic food intervention on the concentrations of 3,5,6-trichloro-2-pyridinol (TCPy) in urine.   Abbreviations : IV, inverse variance; SD, standard deviation; CI: confidence interval; SMD, standardized mean difference.

Other biomarkers

A total of 22 publications investigated the effect of organic food intake on biomarkers other than those indicating pesticide exposure, 18–23 , 26–30 , 38 , 39 , 50 , 52 , 54–56 , 63 , 65–67 including 18 trials, 18–23 , 26–30 , 52 , 55 , 56 , 63 , 65–67 3 cohort studies, 38 , 39 , 50 and 1 cross-sectional analysis. 54 Only 2 investigations were conducted in children. 65 , 67 The range of intervention time in the trials ranged from several minutes to 4 weeks, 20 , 55 and most interventions involved single food items, including eggs, tomatoes, apples, carrots, red grape juice, etc.

The level of association of organic food with fatty acids in human milk was assessed as having “insufficient” evidence due to the limited number of studies. The levels of association of organic food intake with toxic metals and carotenoids were each classified as “no association”, of organic food intake with phenolics was classified as “beneficial”, and of organic food intake with serum parameters, and with total antioxidant status were each defined as “inconsistent” ( Table 4 ). A beneficial association was identified between phenolics and organic food in the interventional trials ( Table 5 ).

Diseases and functional change

Seventeen studies were identified that investigated the effect of organic food consumption on diseases or functional changes, 27 , 31–33 , 35–37 , 40–44 , 51 , 53 , 59 , 62 , 64 including 2 interventional studies, 27 , 53 10 cohort studies, 33 , 35 , 36 , 40–44 , 59 , 64 4 cross-sectional studies, 31 , 32 , 51 , 62 and a case–control study. 37 The overall correlations between organic food consumption and “diseases and functional change” and between organic food consumption and “BMI or obesity” were each classified as “beneficial” ( Table 4 ).

Obesity/BMI. Four studies specifically reported on the effect of an organic food diet on obesity or BMI, and all concluded that increased organic food consumption was associated with a lower BMI or a reduced risk of obesity. 27 , 42 , 53 , 62

Pregnant women study. Five studies investigated the association between organic food consumption in pregnant women and the risk of disease in the mother or offspring. 35–37 , 41 , 51 An association between organic food consumption and reduction in pre-eclampsia (OR = .79, 95% CI: .62–.99) and between organic food consumption and reduction in hypospadias (OR = .42, 95% CI: .25–.70) was observed in the same cohort, respectively. 36 , 37 Additionally, there was an association between rarely or never choosing organic high-fat dairy products during pregnancy and increased odds of hypospadias in offspring (OR = 2.18, 95% CI: 1.09–4.36). 38 A significant negative association was observed between an organic diet during pregnancy and at least 1 otitis media episode (OR = 2.12, 95% CI: 1.01–4.47). 42 Organic food consumption tended to be lower in women with gestational diabetes than in women without gestational diabetes, but the difference was not statistically significant. 52

Allergy. Kummeling et al discovered that feeding infants with organic dairy products had a protective effect against eczema risk in the first 2 years of life (OR = .64,95% CI: .44–.93). 41 However, another cohort study reported that feeding with organic food during the complementary feeding period was not related to respiratory outcomes or eczema up to age 5.5 years; moreover, children fed frequently with organic food but infrequently with commercial complementary foods were more likely to have a food allergy. 65

Reproductive functional change and disease. It was found that men who ate organic food had a higher sperm concentration, a reduced prevalence of previous reproductive disorders, a higher incidence of cryptorchidism, 32 and a higher proportion of normal sperm. 33 A cohort study conducted in senior men reported patients adhering to an organic diet were approximately 1.8 times less likely to have erectile dysfunction. 60

Cancer. Two large cohort studies examined the association between the consumption of organic food and the risk of cancer. 33 , 44 It was reported that high organic food scores were inversely associated with the overall risk of cancer in a French population, 34 and a beneficial association of organic food with non-Hodgkin lymphoma was observed in British women (RR = .79, 95% CI: .65–.96). 45

To our knowledge, this is the most comprehensive systematic review exploring the effects of organic food intake on health. Furthermore, we developed criteria for classifying the level of association between organic food and health effects, and assessed both the qualitative and quantitative impacts of organic food intake on various health outcomes. We found that there was a beneficial association between organic food intake and pesticide exposure reduction, overall burden of disease and functional changes, and BMI or obesity.

The findings of the interventional trials indicated that an organic diet intervention can reduce pesticide exposure, though more research is needed to quantify the benefits of reducing exposure to particular pesticides. Pesticide residues in food have been a controversial topic of public discussion, and many consumers choose organic food to avoid them. Previous meta-analyses have shown that the risk of pesticide residues being detected in organic food production is 30% lower than that in conventional food production, 4 providing evidence for the benefits of consuming organic food. However, the present meta-analysis found no significant difference in the TCPy concentration in urine when comparing the organic and conventional groups. While pesticide residues detected in food produced organically were significantly lower, the level of correlation between pesticide residues detected in food samples and the absorbed pesticide dose measured in biological samples has rarely been determined, making it difficult to draw definitive conclusions. 69

Previous research has largely focused on organophosphate pesticides, which were once the most frequently used. 67 However, the use of organophosphorus pesticides has declined in the United States since the passage of the Food Quality Protection Act in 1996, and this decrease reflects a shift toward the use of other classes of insecticides 58 ; the use of pyrethroids and neonicotinoids has increased, and neonicotinoids are now the most widely used class of insecticides worldwide. 33 Further research is needed to assess the impact of exposure to individual pesticides.

Biomarkers in vivo

Based on the findings of this systematic review, the impact of organic food intake on physiological parameters, including immune and endocrine biomarkers, is unclear and may vary with food type, population health status, and intervention duration. The nutritional quality of food is influenced by factors such as food type, season, and environment, which could explain why organically produced food has a higher nutritional quality.

However, the impact of organic food intake may vary depending on the type of food and the duration of the intervention. More than half of the included interventional trials focused on single food interventions, mainly involving fruits. While these trials may be useful for investigating the health effects of specific organic foods, they do not reflect the diversity of foods in a typical diet. For instance, the NutriNet-Santé study found that individuals with different organic food consumption patterns tended to consume different types of food, and intake of plant-based foods increased with the proportion of organic foods in the diet. 70 Additionally, most intervention durations in the included studies were relatively short, around 2 weeks, making it challenging to assess the long-term impact of an organic diet. Stracke et al did not observe any health benefits after short-term (several minutes) or long-term (4 weeks) organic apple interventions, 21 likely due to the rapid elimination of apple polyphenols from the body. Conversely, Akçay et al concluded that the long-term consumption of organic red wine may have more potent antioxidant activity than a single dose, 24 possibly due to the storage capacity for flavonoids in the body. Therefore, future long-term intervention studies should consider the absorption, metabolism, and excretion of the various phytochemicals from the human body to better assess the health impact of organic foods.

The health status of study participants is also an important consideration. Most of the included studies selected healthy adults as subjects; however, some studies have reported that a reduction in C-reactive protein (a pro-inflammatory plasma marker) after consuming organic food was only observed in patients with chronic kidney disease, 28 and the modulating effect of enzymatic antioxidant protection from organic beet leaves and stalks (BLS) was only found in individuals with dyslipidemia. 57 Hughes et al suggested that supplementation with carotenoids might be appropriate for undernourished or less healthy individuals, particularly among the elderly. 71 Therefore, changes in biological function associated with organic food intake may be more clinically significant in unhealthy populations.

Organic food intake and disease

The majority of the included studies reporting disease outcomes were observational in nature. Multiple disease outcomes were reported in the included studies, including allergy, hypospadias, erectile dysfunction, pre-eclampsia, obesity, metabolic syndrome, and cancer. Although the evidence for an effect on each individual disease may be insufficient, these findings suggest a beneficial association between organic foods and overall disease and functional changes. One possible explanation for this overall beneficial association is the lower levels of pesticide residues and higher nutrient concentrations in organic food. Higher levels of n-3 PUFAs have been reported in organic milk, 4 which might explain the beneficial association with a lower eczema risk. 41

Pesticides may interfere with the development of the male reproductive system, through their estrogenic or anti-androgenic activity, and animal studies support their role in the development of male reproductive disorders. 72 Pesticides also act on membrane receptors and enzymes in the steroid biosynthetic pathway, which can be delivered through the placenta during fetal development and lead to pregnancy disorders such as preeclampsia. 71 In addition, pesticides can impair glucose metabolism and induce insulin resistance, resulting in an increased risk of obesity and other chronic diseases. Moreover, pesticides can have a significant impact on human health by altering the composition and diversity of the gut microbiota, leading to abnormal intestinal barrier function and the development of diseases. 73 Possible underlying mechanistic pathways for the carcinogenicity of pesticides include structural DNA damage and functional damage through epigenetic mechanisms. 34 , 45

Furthermore, it is important to consider reverse causation bias and confounding bias when making causal inferences about the health effects of organic food. Payet et al reported that a history of allergy strongly affects feeding with organic food during the complementary feeding period. 65 Meanwhile, organic food consumption could be associated with increased odds of food allergy later in childhood. Similar confusion arises when examining the association of organic food with other diseases such as obesity and cancer. Organic food consumers tend to be younger and thinner, with diets of higher nutritional quality, and they tend to be followers of a healthy lifestyle. 70 It is worth exploring whether the beneficial effects of organic food are the results of the general characteristics of the consumers or of the intake of organic food itself.

Finally, it is worth noting that the populations in the studies included in this review vary widely, and the studies cover topics ranging from allergies in infants to reproductive function in the elderly. This suggests that an organic food diet may be beneficial for people of all ages. However, given the special physiological states of children and the elderly, and the high cost of organic food, it may be more cost-effective to investigate the health effects of an organic diet among these special populations. Moreover, most of the included studies were conducted in economically advanced countries, with only 2 being conducted in Brazil. Given the current increasing environmental consciousness of consumers, 74 it would be worthwhile launching studies on the health effects of organic diets in developing countries.

First, language bias could not be avoided, because only English articles were included; however, our review covers studies undertaken in a wide range of non-English-speaking countries. In addition, although we took measures to avoid omitting relevant literature, reporting and publication biases remain potential limitations of systematic reviews. Second, the limited number of studies for any particular outcome prevented us from examining the dose–response relationship of organic food intake with outcomes. Similarly, we were only able to conduct a meta-analysis for TCPy, as few studies were identified for other outcomes. Third, the conclusions regarding the association between organic food and disease were largely based on observational studies, and only a limited number of trials were included. Therefore, there is a need for more interventional trials to further investigate this association. Moreover, caution should be exercised when interpreting the findings, due to the heterogeneity among the included studies in terms of study design, population characteristics, organic food types, and statistical and analytical approaches employed.

The beneficial relationship between organic food intake and pesticide exposure is comparatively robust. There are indications of an overall positive association between an organic diet and improved health outcomes and physiological changes, but further research is needed to establish a definitive link with individual diseases beyond obesity.

Author contributions. C.L and Z.A conceived the study. J.B. searched the literature, performed statistical analysis, and prepared the manuscript draft. R.D. and F.J. screened the literature. J.B. and L.X. carried out quality control. C.L. and Z.A. revised the initial manuscript. P.J., L.J., and M.L. performed data interpretation and critically reviewed this manuscript. All authors contributed to the manuscript revision and approved the submitted version.

Funding. No external funding was received to support this work.

Declaration of interest. The authors have no relevant interests to declare.

The following Supporting Information is available through the online version of this article at the publisher’s website.

Appendix S1   Search strategy in EMBASE

Table S1   Abbreviated list

Figure S1   Bias assessments of interventional trials

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Robert Paarlberg is an associate in the Sustainability Science Program at the Kennedy School and the author of several books on agriculture and food, including “Resetting the Table.” We asked him whether eating organic is better for us.

Is organic food, grown without synthetic chemicals, healthier than conventionally grown food? Roughly 40 percent of Americans say at least some of the food they eat is organic, so quite a few eaters clearly believe it is.

However, there is no reliable evidence showing that organically grown foods are more nutritious or safer to eat. In 2012, a review of data from 237 studies conducted at the Center for Health Policy at Stanford University concluded there were no convincing differences between organic and conventional foods in nutrient content or health benefit. The organic ban on synthetic chemicals also fails to improve food safety in the U.S., since the use of pesticides is now significantly regulated in conventional farming (insecticide use today is 82 percent lower than it was in 1972), and because produce in supermarkets has been washed to remove nearly all of the chemical residues that might remain.

In 2021, the USDA conducted its annual survey of pesticide residues on food in the American marketplace, testing 10,127 food samples from nine different states. It found more than 99 percent had residues safely below EPA’s tolerance levels, which are cautiously set at only 1/100th of an exposure that still does not cause toxicity in laboratory animals. Food scientists at the University of California, Davis, conclude from such surveys that the “marginal benefits of reducing human exposure to pesticides in the diet through increased consumption of organic produce appear to be insignificant.”

By one estimate in 2014, only 8 percent of organic sales in the U.S. were still being made by small farmers through farmers markets or through community supported agriculture.

Many consumers continue to think organic foods come from small local farms, but most now come from distant industrial farms. By one estimate in 2014, only 8 percent of organic sales in the U.S. were still being made by small farmers through farmers markets or through community supported agriculture. Over 80 percent of all U.S. organic sales are now made by corporate conglomerates like ConAgra, H.J. Heinz, and Kellogg. The biggest retailers of organic foods are Walmart, Costco, and Kroger.

Most commercial farmers, both large and small, want to use at least some synthetic nitrogen fertilizer, which means they can’t be certified as organic. This is why less than 1 percent of harvested cropland in America is certified organic. Canadian geographer Vaclav Smil has estimated that without synthetic nitrogen fertilizer, 40 percent of the increased food production required by today’s population could never have taken place. Organic yields are lower, so if we shifted more production to organic we would also have to plow up more land to produce the same amount of food, which would reduce wildlife habitat and damage the environment.

Intuition tells us foods grown without manufactured chemicals are more “natural” and therefore better for the environment, safer to eat and helping small local farms. Even the fact that organic foods are more expensive seems a reason to think they are better. But in this case, intuitive thinking takes us in the wrong direction. If we follow the science, organic food loses its apparent advantage.

— As told to Anna Lamb/Harvard Staff Writer

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• Open access
• Published: 27 October 2017

Human health implications of organic food and organic agriculture: a comprehensive review

• Axel Mie   ORCID: orcid.org/0000-0001-8053-3541 1 , 2 ,
• Helle Raun Andersen 3 ,
• Stefan Gunnarsson 4 ,
• Johannes Kahl 5 ,
• Emmanuelle Kesse-Guyot 6 ,
• Ewa Rembiałkowska 7 ,
• Gianluca Quaglio 8 &
• Philippe Grandjean 3 , 9  

Environmental Health volume  16 , Article number:  111 ( 2017 ) Cite this article

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This review summarises existing evidence on the impact of organic food on human health. It compares organic vs. conventional food production with respect to parameters important to human health and discusses the potential impact of organic management practices with an emphasis on EU conditions. Organic food consumption may reduce the risk of allergic disease and of overweight and obesity, but the evidence is not conclusive due to likely residual confounding, as consumers of organic food tend to have healthier lifestyles overall. However, animal experiments suggest that identically composed feed from organic or conventional production impacts in different ways on growth and development. In organic agriculture, the use of pesticides is restricted, while residues in conventional fruits and vegetables constitute the main source of human pesticide exposures. Epidemiological studies have reported adverse effects of certain pesticides on children’s cognitive development at current levels of exposure, but these data have so far not been applied in formal risk assessments of individual pesticides. Differences in the composition between organic and conventional crops are limited, such as a modestly higher content of phenolic compounds in organic fruit and vegetables, and likely also a lower content of cadmium in organic cereal crops. Organic dairy products, and perhaps also meats, have a higher content of omega-3 fatty acids compared to conventional products. However, these differences are likely of marginal nutritional significance. Of greater concern is the prevalent use of antibiotics in conventional animal production as a key driver of antibiotic resistance in society; antibiotic use is less intensive in organic production. Overall, this review emphasises several documented and likely human health benefits associated with organic food production, and application of such production methods is likely to be beneficial within conventional agriculture, e.g., in integrated pest management.

Peer Review reports

The long-term goal of developing sustainable food systems is considered a high priority by several intergovernmental organisations [ 1 , 2 , 3 ]. Different agricultural management systems may have an impact on the sustainability of food systems, as they may affect human health as well as animal wellbeing, food security and environmental sustainability. In this paper, we review the available evidence on links between farming system (conventional vs organic) and human health.

Food production methods are not always easy to classify. This complexity stems from not only the number and varying forms of conventional and organic agricultural systems but also resulting from the overlap of these systems. In this paper, we use the term “conventional agriculture” as the predominant type of intensive agriculture in the European Union (EU), typically with high inputs of synthetic pesticides and mineral fertilisers, and a high proportion of conventionally-produced concentrate feed in animal production. Conversely, “organic agriculture” is in accordance with EU regulations or similar standards for organic production, comprising the use of organic fertilisers such as farmyard and green manure, a predominant reliance on ecosystem services and non-chemical measures for pest prevention and control and livestock access to open air and roughage feed.

In 2015, over 50.9 million hectares, in 179 countries around the world, were cultivated organically, including areas in conversion [ 4 ]. The area under organic management (fully converted and in-conversion) has increased during the last decades in the European Union, where binding standards for organic production have been developed [ 5 , 6 ]. In the 28 countries forming the EU today, the fraction of organically cultivated land of total agricultural area has been steadily increasing over the last three decades. 0.1%, 0.6%, 3.6%, and 6.2% of agricultural land were organic in 1985, 1995, 2005, and 2015, respectively, equalling 11.2 million ha in 2015 [ 7 , 8 , 9 ]. In 7 EU Member States, at least 10% of the agricultural land is organic [ 7 ]. In 2003, 125,000 farms in the EU were active in organic agriculture, a number that increased to 185,000 in 2013 [ 10 ]. Between 2006 and 2015, the organic retail market has grown by 107% in the EU, to €27.1 billion [ 7 ].

This review details the science on the effects of organic food and organic food production on human health and includes

studies that directly address such effects in epidemiological studies and clinical trials.

animal and in vitro studies that evaluate biological effects of organic compared to conventional feed and food.

Focusing on narrower aspects of production, we then discuss the impact of the production system on

plant protection, pesticide exposure, and effects of pesticides on human health,

plant nutrition, the composition of crops and the relevance for human health,

animal feeding regimens, effects on the composition of animal foods and the relevance for human health.

animal health and well-being, the use of antibiotics in animal production, its role in the development of antibiotic resistance, and consequences of antibiotic resistance for public health.

In the discussion, we widen the perspective from production system to food system and sustainable diets and address the interplay of agricultural production system and individual food choices. The consequences of these aspects on public health are briefly discussed.

Due to a limited evidence base, minimal importance, lack of a plausible link between production system and health, or due to lack of relevance in the European Union, we do not or only briefly touch upon

singular food safety events such as outbreaks of diseases that are not clearly caused by the production system (hygiene regulations for plant production and for animal slaughtering and processing are for the most part identical for organic and conventional agriculture) or fraudulent introduction of contaminated feed into the feed market

historic events and historic sources of exposure, such as the BSE crisis caused by the now-banned practice of feeding cattle with meat and bone meal from cattle, or continuing effects of the historic use of DDT, now banned in all agricultural contexts globally

contaminants from food packaging

aspects of food processing, such as food additives

the presence of mycotoxins in consequence of post-harvest storage and processing which is governed chiefly by moisture and temperature in storage

the use of growth hormones in animal production, which is not permitted in the EU but in several other countries

Furthermore, aspects of environmental sustainability, such as biodiversity and greenhouse gas emissions, may also be affected by the agricultural production system [ 11 , 12 ] and may affect human health via food security [ 13 , 14 ]. While these indirect links are outside the scope of this review, we briefly touch on them in the discussion. Also, the focus of this article is on public health, not on occupational health of agricultural workers or local residents, although these issues are considered as part of the epidemiological evidence on pesticide effects. While agricultural standards vary between countries and regions, we maintain a global perspective when appropriate and otherwise focus on the European perspective.

The literature search for this review was carried out at first using the PubMed and Web of Science databases, while applying “organic food” or “organic agriculture” along with the most relevant keywords, through to the end of 2016 (more recent references were included, when relevant, although they were not identified through the systematic search). We made use of existing systematic reviews and meta-analyses when possible. In some cases, where scientific literature is scarce, we included grey literature e.g. from authorities and intergovernmental organisations. We also considered references cited in the sources located.

Association between organic food consumption and health: Findings from human studies

A growing literature is aiming at characterizing individual lifestyles, motivations and dietary patterns in regard to organic food consumption, which is generally defined from responses obtained from food frequency questionnaires [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Still, current research on the role of organic food consumption in human health is scarce, as compared to other nutritional epidemiology topics. In particular, long-term interventional studies aiming to identify potential links between organic food consumption and health are lacking, mainly due to high costs. Prospective cohort studies constitute a feasible way of examining such relationships, although compliance assessment is challenging. Considering a lack of biomarkers of exposure, the evaluation of the exposure, i.e. organic food consumption, will necessarily be based on self-reported data that may be prone to measurement error.

Some recent reviews have compiled the findings [ 24 , 25 , 26 ] from clinical studies addressing the association between consumption of organic food and health. These studies are scant and generally based on very small populations and short durations, thus limiting statistical power and the possibility to identify long-term effects. Smith-Spangler et al. [ 25 ] summarised the evidence from clinical studies that overall no clinically significant differences in biomarkers related to health or to nutritional status between participants consuming organic food compared to controls consuming conventional food. Among studies of nutrient intakes, the OrgTrace cross-over intervention study of 33 males, the plant-based fraction of the diets was produced in controlled field trials, but 12 days of intervention did not reveal any effect of the production system on the overall intake or bioavailability of zinc and copper, or plasma status of carotenoids [ 27 , 28 ].

In observational studies, a specific challenge is the fact that consumers who regularly buy organic food tend to choose more vegetables, fruit, wholegrain products and less meat, and tend to have overall healthier dietary patterns [ 18 , 29 ]. Each of these dietary characteristics is associated with a decreased risk for mortality from or incidence of certain chronic diseases [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. Consumers who regularly buy organic food are also more physically active and less likely to smoke [ 18 , 19 , 37 ]. Depending on the outcome of interest, associations between organic vs conventional food consumption and health outcome therefore need to be carefully adjusted for differences in dietary quality and lifestyle factors, and the likely presence of residual confounding needs to be considered. In children, several studies have reported a lower prevalence of allergy and/or atopic disease in families with a lifestyle comprising the preference of organic food [ 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. However, organic food consumption is part of a broader lifestyle in most of these studies and associated with other lifestyle factors. Thus, in the Koala birth cohort of 2700 mothers and babies from the Netherlands [ 39 ], exclusive consumption of organic dairy products during pregnancy and during infancy was associated with a 36% reduction in the risk of eczema at age 2 years. In this cohort, the preference of organic food was associated with a higher content of ruminant fatty acids in breast milk [ 40 ], which in turn was associated with a lower odds ratio for parent-reported eczema until age 2y [ 45 ].

In the MOBA birth cohort study of 28,000 mothers and their offspring, women reporting a frequent consumption of organic vegetables during pregnancy exhibited a reduction in risk of pre-eclampsia [ 29 ] (OR = 0.79, 95% CI 0.62 to 0.99). No significant association was observed for overall organic food consumption, or five other food groups, and pre-eclampsia.

The first prospective study investigating weight change over time according to the level of organic food consumption included 62,000 participants of the NutriNet-Santé study. BMI increase over time was lower among high consumers of organic food compared to low consumers (mean difference as % of baseline BMI = − 0.16, 95% Confidence Interval (CI): −0.32; −0.01). A 31% (95% CI: 18%; 42%) reduction in risk of obesity was observed among high consumers of organic food compared to low consumers. Two separate strategies were chosen to properly adjust for confounders [ 46 ]. This paper thus confirms earlier cross-sectional analyses from the same study [ 18 ].

In regard to chronic diseases, the number of studies is limited. In the Nutrinet-Santé study, organic food consumers (occasional and regular), as compared to non-consumers, exhibited a lower incidence of hypertension, type 2 diabetes, hypercholesterolemia (in both males and females), and cardiovascular disease (in men) [ 47 ] but more frequently declared a history of cancer. Inherent to cross-sectional studies, reverse causation cannot be excluded; for example, a cancer diagnosis by itself may lead to positive dietary changes [ 48 ].

Only one prospective cohort study conducted in adults addressed the effect of organic food consumption on cancer incidence. Among 623,080 middle-aged UK women, the association between organic food consumption and the risk of cancer was estimated during a follow-up period of 9.3 y. Participants reported their organic food consumption through a frequency question as never, sometimes, or usually/always. The overall risk of cancer was not associated with organic food consumption, but a significant reduction in risk of non-Hodgkin lymphoma was observed in participants who usually/always consume organic food compared to people who never consume organic food (RR = 0.79, 95% CI: 0.65; 0.96) [ 37 ].

In conclusion, the link between organic food consumption and health remains insufficiently documented in epidemiological studies. Thus, well-designed studies characterized by prospective design, long-term duration and sufficient sample size permitting high statistical power are needed. These must include detailed and accurate data especially for exposure assessment concerning dietary consumption and sources (i.e. conventional or organic).

Experimental in vitro and animal studies

In vitro studies.

The focus on single plant components in the comparison of crops from organic and conventional production, as discussed further below, disregards the fact that compounds in food do not exist and act separately, but in their natural context [ 49 ]. In vitro studies of effects of entire foods in biological systems such as cell lines can therefore potentially point at effects that cannot be predicted from chemical analyses of foods, although a limitation is that most cells in humans are not in direct contact with food or food extracts.

Two studies have investigated the effect of organic and conventional crop cultivation on cancer cell lines, both using crops produced under well-documented agricultural practices and with several agricultural and biological replicates. In the first study extracts from organically grown strawberries exhibited stronger antiproliferative activity against one colon and one breast cancer cell line, compared to the conventionally produced strawberries [ 50 ]. In the second study [ 51 ] the extracts of organic naturally fermented beetroot juices induced lower levels of early apoptosis and higher levels of late apoptosis and necrosis in a gastric cancer cell line, compared to the conventional extracts. Both studies thus demonstrated notable differences in the biological activity of organic vs. conventionally produced crop extracts in vitro, which should inspire further research. However, neither of these studies allows for the distinction of a selective antiproliferative effect on cancer cells, and general cell toxicity. Therefore it cannot be determined which of the organic or conventional food extracts, if any, had the preferable biological activity in terms of human health.

Animal studies of health effects

Considering the difficulties of performing long-term dietary intervention studies in humans, animal studies offer some potential of studying long-term health effects of foods in vivo. However, extrapolation of the results from animal studies to humans is not straight-forward. Studies in this field started almost 100 years ago. A review of a large number of studies [ 52 ] concluded that positive effects of organic feed on animal health are possible, but further research is necessary to confirm these findings. Here we focus on the main health aspects.

In one of the best-designed animal studies, the second generation chickens receiving the conventionally grown feed demonstrated a faster growth rate. However, after an immune challenge, chickens receiving organic feed recovered more quickly [ 53 ]. This resistance to the challenge has been interpreted as a sign of better health [ 54 , 55 ].

In one carefully conducted crop production experiment, followed by a rat feeding trial, the production system had an apparent effect on plasma-IgG concentrations but not on other markers of nutritional or immune status [ 56 ]. A two-generational rat study based on feed grown in a factorial design (fertilisation x plant protection) of organic and conventional practices revealed that the production system had an effect on several physiological, endocrine and immune parameters in the offspring [ 57 ]. Most of the effects identified were related to the fertilisation regimen. None of these studies found that any of the feed production systems was more supportive of animal health.

Several other studies, mostly in rats, have reported some effect of the feed production system on immune system parameters [ 57 , 58 , 59 , 60 ]. However, the direct relevance of these findings for human health is uncertain.

Collectively, in vitro and animal studies have demonstrated that the crop production system does have an impact on certain aspects of cell life, the immune system, and overall growth and development. However, the direct relevance of these findings for human health is unclear. On the other hand, these studies may provide plausibility to potential effects of conventional and organic foods on human health. Still, most of the outcomes observed in animal studies have not been examined in humans so far.

Plant protection in organic and conventional agriculture

Plant protection in conventional agriculture is largely dependent on the use of synthetic pesticides. Conversely, organic farming generally relies on prevention and biological means for plant protection, such as crop rotation, intercropping, resistant varieties, biological control employing natural enemies, hygiene practices and other measures [ 61 , 62 , 63 , 64 ]. Yet, certain pesticides are approved for use in organic agriculture. In the EU, pesticides (in this context, more specifically chemical plant-protection products; micro- and macrobiological agents are excluded from this discussion due to their low relevance for human health) are approved after an extensive evaluation, including a range of toxicological tests in animal studies [ 65 ]. Acceptable residue concentrations in food are calculated from the same documentation and from the expected concentrations in accordance with approved uses of the pesticides. Currently, 385 substances are authorised as pesticides in the EU (Table  1 ). Of these , 26 are also approved for use in organic agriculture [ 6 , 66 ] as evaluated in accordance with the same legal framework.

Most of the pesticides approved for organic agriculture are of comparatively low toxicological concern for consumers because they are not associated with any identified toxicity (e.g. spearmint oil, quartz sand), because they are part of a normal diet or constitute human nutrients (e.g. iron, potassium bicarbonate, rapeseed oil) or because they are approved for use in insect traps only and therefore have a negligible risk of entering the food chain (i.e. the synthetic pyrethroids lambda-cyhalothrin and deltamethrin, and pheromones). Two notable exceptions are the pyrethrins and copper. Pyrethrins, a plant extract from Chrysanthemum cinerariaefolium, share the same mechanism of action as the synthetic pyrethroid insecticides, but are less stable. Copper is an essential nutrient for plants, animals and humans, although toxic at high intakes and of ecotoxicological concern due to toxicity to aquatic organisms.

Plant protection practices developed in and for organic agriculture may be of benefit to the entire agricultural system [ 67 , 68 , 69 , 70 ]. This is of specific value for the transition towards sustainable use of pesticides in the EU, which has a strong emphasis on non-chemical plant protection measures including prevention and biological agents [ 63 , 64 ]. Further, steam treatment of cereal seeds for the prevention of fungal diseases ( http://thermoseed.se/ ) has been developed driven by the needs of organic agriculture as an alternative to chemical seed treatments [ 71 , 72 ]. These methods are now also being marketed for conventional agriculture, specifically for integrated pest management (IPM) [ 73 ].

Pesticide use – Exposure of consumers and producers

One main advantage of organic food production is the restricted use of synthetic pesticides [ 5 , 6 ], which leads to low residue levels in foods and thus lower pesticide exposure for consumers. It also reduces the occupational exposure of farm workers to pesticides and drift exposures of rural populations. On average over the last three available years, EFSA reports pesticide residues below Maximum Residue Levels (MRL) in 43.7% of all and 13.8% of organic food samples. MRLs reflect the approved use of a pesticide rather than the toxicological relevance of the residue. There are no separate MRLs for organic products. A total of 2.8% of all and 0.9% of organic samples exceeded the MRL, which may be due to high residue levels or due to low levels but unapproved use of a particular pesticide on a particular crop [ 74 , 75 , 76 ]. Of higher toxicological relevance are risk assessments, i.e. expected exposure in relation to toxicological reference values. On average 1.5% of the samples were calculated to exceed the acute reference dose (ARfD) for any of the considered dietary scenarios, with the organophosphate chlorpyrifos accounting for approximately half of these cases and azole fungicides (imazalil, prochloraz, and thiabendazole) for approximately 15%. None (0%) of the organic samples exceeded the ARfD [ 74 ]. Residues of more than one pesticide were found in approximately 25% of the samples but calculations of cumulative risks were not included in the reports [ 74 , 75 , 76 ].

The only cumulative chronic risk assessment comparing organic and conventional products known to us has been performed in Sweden. Using the hazard index (HI) method [ 77 ], adults consuming 500 g of fruit, vegetables and berries per day in average proportions had a calculated HI of 0.15, 0.021 and 0.0003, under the assumption of imported conventional, domestic conventional, and organic products, respectively [ 78 ]. This indicates an at least 70 times lower exposure weighted by toxicity for a diet based on organic foods. There are several routes by which pesticides not approved for use in organic agriculture may contaminate organic products, including spray drift or volatilisation from neighbouring fields, fraudulent use, contamination during transport and storage in vessels or storages where previously conventional products have been contained, and mislabelling by intention or mistake. Overall, however, current systems for the certification and control of organic products ensure a low level of pesticide contamination as indicated by chronic and acute risks above, although they still can be improved [ 79 ].

The general population’s exposure to several pesticides can be measured by analysing blood and urine samples, as is routinely done in the US [ 80 ] although not yet in Europe. However, a few scattered European studies from France [ 81 , 82 , 83 ], Germany [ 84 ], the Netherlands [ 85 ], Spain [ 86 ], Belgium [ 87 ], Poland [ 88 ] and Denmark [ 89 ] have shown that EU citizens are commonly exposed to organophosphate and pyrethroid insecticides. A general observation has been higher urinary concentrations of pesticide metabolites in children compared to adults, most likely reflecting children’s higher food intake in relation to body weight and maybe also more exposure-prone behaviours. The urinary concentrations of generic metabolites of organophosphates (dialkyl phosphates, DAPs) and pyrethroids (3-phenoxybenzoic acid, 3-PBA) found in most of the European studies were similar to or higher than in the US studies. Although urinary metabolite concentration might overestimate the exposure to the parent compounds, due to ingestion of preformed metabolites in food items, several studies have reported associations between urinary metabolite concentrations and neurobehavioral deficits as described below. Besides, the metabolites are not always less toxic than the parent compounds [ 90 ].

For the general population, pesticide residues in food constitute the main source of exposure for the general population. This has been illustrated in intervention studies where the urinary excretion of pesticides was markedly reduced after 1 week of limiting consumption to organic food [ 91 , 92 , 93 ]. Similar conclusions emerged from studies investigating associations between urinary concentrations of pesticides and questionnaire information on food intake, frequency of different foodstuffs and organic food choices. Thus a high intake of fruit and vegetables is positively correlated with pesticide excretion [ 94 ], and frequent consumption of organic produce is associated with lower urinary pesticide concentration [ 95 ].

Pesticide exposure and health effects

The regulatory risk assessment of pesticides currently practised in the EU is comprehensive, as a large number of toxicological effects are addressed in animal and other experimental studies. Nonetheless, there are concerns that this risk assessment is inadequate at addressing mixed exposures, specifically for carcinogenic effects [ 96 ] as well as endocrine-disrupting effects [ 97 , 98 ] and neurotoxicity [ 99 ]. Furthermore, there are concerns that test protocols lag behind independent science [ 100 ], studies from independent science are not fully considered [ 101 ] and data gaps are accepted too readily [ 102 ]. These concerns primarily relate to effects of chronic exposure and to chronic effects of acute exposure, which are generally more difficult to discover than acute effects. Most studies rely on urinary excretion of pesticide metabolites and a common assumption is that the subjects were exposed to the parent chemicals, rather than the metabolites.

The overall health benefits of high fruit and vegetable consumption are well documented [ 31 , 35 ]. However, as recently indicated for effects on semen quality [ 103 ], these benefits might be compromised by the adverse effects of pesticide residues. When benefits are offset by a contaminant, a situation of inverse confounding occurs, which may be very difficult to adjust for [ 104 ]. The potential negative effects of dietary pesticide residues on consumer health should of course not be used as an argument for reducing fruit and vegetable consumption. Neither should nutrient contents be used to justify exposures to pesticides. Exposures related to the production of conventional crops (i.e. occupational or drift exposure from spraying) have been related to an increased risk of some diseases including Parkinson’s disease [ 105 , 106 , 107 ], type 2 diabetes [ 108 , 109 ] and certain types of cancers including non-Hodgkin lymphoma [ 110 ] and childhood leukaemia or lymphomas, e.g. after occupational exposure during pregnancy [ 105 , 111 ] or residential use of pesticides during pregnancy [ 105 , 112 ] or childhood [ 113 ]. To which extent these findings also relate to exposures from pesticide residues in food is unclear. However, foetal life and early childhood are especially vulnerable periods for exposure to neurotoxicants and endocrine disruptors. Even brief occupational exposure during the first weeks of pregnancy, before women know they are pregnant, have been related to adverse long-lasting effects on their children’s growth, brain functions and sexual development, in a Danish study on greenhouse worker’s children [ 114 , 115 , 116 , 117 , 118 ].

In order to assess the potential health risk for consumers associated with exposure to dietary pesticides, reliance on epidemiological studies of sensitive health outcomes and their links to exposure measures is needed. Such studies are complicated both by difficult exposure assessment and the necessary long-term follow-up. The main focus so far has been on cognitive deficits in children in relation to their mother’s exposure level to organophosphate insecticides during pregnancy. This line of research is highly appropriate given the known neurotoxicity of many pesticides in laboratory animal models [ 99 ] and the substantial vulnerability of the human brain during early development [ 119 ].

Most of the human studies have been carried out in the US and have focused on assessing brain functions in children in relation to prenatal organophosphate exposure. In a longitudinal birth cohort study among farmworkers in California (the CHAMACOS cohort), maternal urinary concentrations of organophosphate metabolites in pregnancy were associated with abnormal reflexes in neonates [ 120 ], adverse mental development at 2 years of age [ 121 ], attention problems at three and a half and 5 years [ 122 ], and poorer intellectual development at 7 years [ 123 ]. In accordance with this, a birth cohort study from New York reported impaired cognitive development at ages 12 and 24 months and 6 – 9 years related to maternal urine concentrations of organophosphates in pregnancy [ 124 ]. In another New York inner-city birth cohort, the concentration of the organophosphate chlorpyrifos in umbilical cord blood was associated with delayed psychomotor and mental development in children in the first 7 years of life [ 125 ], poorer working memory and full-scale IQ at 7 years of age [ 126 ], structural changes, including decreased cortical thickness, in the brain of the children at school age [ 127 ], and mild to moderate tremor in the arms at 11 years of age [ 128 ]. Based on these and similar studies, chlorpyrifos has recently been categorised as a human developmental neurotoxicant [ 129 ]. Recent reviews of neurodevelopmental effects of organophosphate insecticides in humans conclude that exposure during pregnancy – at levels commonly found in the general population – likely have negative effects on children’s neurodevelopment [ 130 , 131 , 132 ]. In agreement with this conclusion, organophosphate pesticides considered to cause endocrine disruption contribute the largest annual health cost within the EU due to human exposures to such compounds, and these costs are primarily due to neurodevelopmental toxicity, as discussed below.

Since growth and functional development of the human brain continues during childhood, the postnatal period is also assumed to be vulnerable to neurotoxic exposures [ 119 ]. Accordingly, five-year-old children from the CHAMACOS cohort had higher risk scores for development of attention deficit hyperactive disorder (ADHD) if their urine concentration of organophosphate metabolites was elevated [ 122 ]. Based on cross-sectional data from the NHANES data base, the risk of developing ADHD increases by 55% for a ten-fold increase in the urinary concentration of organophosphate metabolites in children aged 8 to 15 years [ 133 ]. Also based on the NHANES data, children with detectable concentrations of pyrethroids in their urine are twice as likely to have ADHD compared with those below the detection limit [ 134 ]. In addition, associations between urinary concentrations of pyrethroid metabolites in children and parent-reported learning disabilities, ADHD or other behavioural problems in the children have recently been reported in studies from the US and Canada [ 135 , 136 ].

So far only few prospective studies from the EU addressing associations between urinary levels of pesticides and neurodevelopment in children from the general population have been published. Three studies are based on the PELAGIE cohort in France and present results for organophosphates and pyrethroids respectively [ 81 , 82 , 137 ]. While no adverse effects on cognitive function in six-year-old children were related to maternal urine concentrations of organophosphates during pregnancy, the concentration of pyrethroid metabolites was associated with internalising difficulties in the children at 6 years of age. Also, the children’s own urinary concentrations of pyrethroid metabolites were related to decrements in verbal and memory functions and externalising difficulties and abnormal social behaviour. While this sole European study did not corroborate US birth cohort studies results showing that exposure during pregnancy to organophosphate insecticides at levels found in the general population may harm brain development in the foetus, the exposure levels measured in the PELAGIE cohort were considerably lower for both organophosphates and pyrethroids than those measured in other European studies as well as in studies from the US and Canada. For example, the median urine concentration of organophosphate metabolites in pregnant women in the PELAGIE cohort was 2 – 6 times lower than for pregnant women in other studies [ 85 , 122 , 138 ] and the concentration of the common pyrethroid metabolite 3-PBA was only detectable in urine samples from 30% of the women compared to 80–90% in other studies [ 88 , 139 ]. Thus, to supplement the French study and the previously mentioned Danish study of greenhouse worker’s children, additional studies that include more representative exposure levels for EU citizens are desirable.

Although exposure levels found in European countries are generally similar to or slightly higher than concentrations found in the US studies, the risk of adverse effects on neurodevelopment in European populations needs to be further characterised. The organophosphate insecticides contributing to the exposure might differ between the US and the EU, also in regard to oral and respiratory intakes. According to the European Food Safety Agency (EFSA), of all the organophosphate insecticides, chlorpyrifos most often exceeds the toxicological reference value (ARfD) [ 74 ]. A recent report utilised US data on adverse effects on children’s IQ levels at school age to calculate the approximate costs of organophosphate exposure in the EU. The total number of IQ points lost due to these pesticides was estimated to be 13 million per year, representing a value of about € 125 billion [ 140 ], i.e. about 1% of the EU’s gross domestic product. Although there is some uncertainty associated with this calculation, it most likely represents an underestimation, as it focused only on one group of pesticides.

Unfortunately, epidemiological evidence linking pesticide exposure and human health effects is rarely regarded as sufficiently reliable to take into account in the risk assessment conducted by regulatory agencies. For example, the conclusion from the epidemiological studies on chlorpyrifos is that an association of prenatal chlorpyrifos exposure and adverse neurodevelopmental outcomes is likely, but that other neurotoxic agents cannot be ruled out, and that animal studies show adverse effects only at 1000-fold higher exposures [ 141 ]. A recent decrease of the maximum residue limit for chlorpyrifos in several crops [ 142 , 143 ] was based on animal studies only [ 144 ], but the limits for the sister compound, chlorpyrifos-methyl were unchanged. This case highlights a major limitation to current approaches to protecting the general population against a broad variety of pesticides.

Production system and composition of plant foods

Fertilisation in organic agriculture is based on organic fertilisers such as farmyard manure, compost and green fertilisers, while some inorganic mineral fertilisers are used as supplements. Nitrogen (N) input is limited to 170 kg/ha * year [ 5 , 145 ]. In conventional agriculture, fertilisation is dominated by mineral fertiliser, although farmyard manure is also common in some countries. There is no general limit on N input. Typically, crop yield is limited by plant N availability in organic but not in conventional systems [ 146 ] Phosphorus (P) input is on average similar or slightly lower in organic systems [ 147 ].

In the absence of particular nutrient deficiency, focusing on single nutrients may be of limited value for evaluating the impact of a food or diet on human health [ 49 ]; studies of actual health effects, as discussed above, are generally more informative than studies of single nutrients.

Overall crop composition

Metabolomics [ 148 , 149 , 150 , 151 , 152 ], proteomics [ 153 , 154 ] and transcriptomics [ 155 , 156 ] studies in controlled field trials provide evidence that the production system has an overall influence on crop development, although there is no direct relevance of these studies for human health. Furthermore, the generally lower crop yield in organic systems [ 146 ] as such indicates an effect of management strategy on plant development.

Several systematic reviews and meta-analyses [ 25 , 157 , 158 , 159 ] with different scopes, inclusion criteria and statistical methods have summarised several hundred original studies reporting some aspect of plant chemical composition in relation to conventional and organic production, in search of overall trends across crops, varieties, soils, climates, production years etc. While the overall conclusions of these systematic reviews look contradictory at first sight, there is agreement between them in most of the detailed findings:

Nitrogen and phosphorus

Existing systematic reviews have consistently found lower total nitrogen (7% [ 157 ], 10% [ 159 ]) and higher phosphorus (standardised mean difference (SMD) 0.82 [ 25 ], 8% [ 157 ]) in organic compared to conventional crops. These findings lack direct relevance for human health. However, considering the differences in fertilisation strategies discussed above, and the fundamental importance of N, P [ 160 , 161 , 162 ], and the N:P ratio [ 163 ] for plant development, this may lend some plausibility to other observed effects of the production system on crop composition.

Systematic reviews generally agree that the concentration of macronutrients, vitamins, and minerals in crops is either not at all or only slightly affected by the production system. For example, ascorbic acid (vitamin C) has received most attention in this context. Meta-analyses report only small effect sizes of the organic production system on vitamin C content [ 25 , 158 , 159 ].

Polyphenols

(Poly)phenolic compounds are not essential nutrients for humans but may play a role in preventing several non-communicable diseases, including cardiovascular disease, neurodegeneration and cancer [ 164 ]. The detailed mechanisms are complex and not fully understood [ 164 ]. Several environmental and agronomic practices affect the phenolic composition of the crop, including light, temperature, availability of plant nutrients and water management [ 165 ]. Under conditions of high nitrogen availability, many plant tissues show a decreased content of phenolic compounds, although there are examples of an opposite relationship [ 165 ].

Meta-analyses report modest effect sizes of the production system on total phenolics content, e.g. an increase of 14 – 26% [ 25 , 158 , 159 ]. For some narrower groups of phenolic compounds, larger relative concentration differences (in percent) between organic and conventional crops have been reported [ 159 ]. However, such findings represent unweighted averages typically from small and few studies, and are therefore less reliable.

Collectively the published meta-analyses indicate a modestly higher content of phenolic compounds in organic food, but the evidence available does not constitute a sufficient basis for drawing conclusions on positive effects of organic compared to conventional plant products in regard to human health.

Cadmium and other toxic metals

Cadmium (Cd) is toxic to the kidneys, can demineralise bones and is carcinogenic [ 166 ]. Cd is present naturally in soils, and is also added to soils by P fertilisers and atmospheric deposition. Several factors, including soil structure and soil chemistry, humus content and pH, affect the plant availability of Cd [ 167 ]. The application of Cd-containing fertilisers increases Cd concentrations in the crops [ 167 , 168 ]. Low soil organic matter generally increases the availability of Cd for crops [ 169 ], and organically managed farms tend to have higher soil organic matter than conventionally managed farms [ 11 ].

The source of Cd in mineral fertilisers is the raw material phosphate rock. The European average Cd content in mineral fertilisers is reported as 68 mg Cd/kg P [ 170 ] or 83 mg Cd/kg P [ 171 ]. The content of Cd in farmyard manure is variable but apparently in many cases lower: Various types of animal manure in a German collection averaged between 14 and 37 mg Cd/kg P [ 172 ].

Smith-Spangler et al. [ 25 ] found no significant difference in the Cd content of organic and conventional crops (SMD = −0.14, 95% CI -0.74 – 0.46) in their meta-analysis, while Barański et al. [ 159 ] report significantly 48% higher Cd concentration in conventional compared to organic crops (SMD = -1.45, 95% CI -2.52 to −0.39) in another meta-analysis largely based on the same underlying original studies, albeit with different inclusion criteria. We contacted the authors of these meta-analyses in order to understand this discrepancy. An updated version of the Barański meta-analysis, in which some inconsistencies have been addressed and which has been provided by the original authors [ 173 ], shows a significant 30% (SMD = −0.56, 95% CI -1.08 to −0.04) elevations of Cd contents in conventional compared to organic crops; in subgroup analysis, this difference is restricted to cereal crops. No updated meta-analysis was available for Smith-Spangler’s analysis [ 25 ]; apparently, two large well-designed studies with tendencies towards a lower Cd content in organic crops were not considered [ 174 , 175 ] although they appear to fulfil the inclusion criteria. Also, a correction for multiple testing has been imposed, which may be overly conservative, given the prior knowledge that mineral fertilisers constitute an important source of Cd to soils and crops. It is unclear how these points would affect the results of Smith-Spangler’s meta-analysis.

There are short-term and long-term effects of Cd influx from fertilisers on the Cd content of crops [ 167 ] but no long-term study comparing Cd content in organic and conventional crops is available. In absence of such direct evidence, two long-term experiments indicate a higher slope in Cd concentration over time for minerally fertilised compared to organically fertilised cereal crops [ 176 , 177 ], after over 100 years of growing.

A lower Cd content of organic crops is therefore plausible due to a lower Cd content in the fertilisers used in organic farming, and potentially due to higher soil organic matter in organic farmland. The general population’s Cd exposure is close to, and in some cases above, the tolerable intake and therefore their exposure to Cd should be reduced. For non-smokers, food is the primary source of exposure, with cereals and vegetables being the most important contributors [ 168 ].

For other toxic metals including lead, mercury and arsenic, no differences in concentration in organic and conventional crops have been reported [ 25 , 159 ]. Uranium (U) is also present as a contaminant of concern in mineral P fertilisers [ 178 ], but less so in organic fertilisers [ 179 ], and consequently manure-based cropping systems have a lower U load than mineral-fertilised systems at equal P load [ 179 ]. Uranium appears to accumulate in mineral-fertilised soils [ 180 ], and agricultural activity may increase the U content of surface and groundwater [ 181 , 182 ]. However, no evidence was found comparing uranium contents of organic and conventional products.

Fungal toxins

Regarding fungal toxins in crops, one meta-analysis has reported a lower contamination of organic compared to conventional cereal crops with deoxynivalenol (DON), produced by certain fusarium species [ 25 ]. Although not fully understood, fungicide applications may alter fungal communities on cereal leaves, potentially weakening disease-suppressive species [ 183 , 184 ]. Also, crop rotations including non-cereal crops may contribute to lower infestation with fusarium [ 185 ], while N availability is positively associated with cereal DON content [ 186 ]. These factors give plausibility to the observed lower DON contamination in organic cereals. In the EU, the mean chronic exposure of toddlers, infants and children to DON is above the tolerable daily intake (TDI), with grains and grain-based products being the main contributors to total exposure. The TDI is based on decreased body weight gain observed in mice [ 187 ]. The production system does not have any observed effect on the concentration of ochratoxin A (OTA), another fungal toxin of importance in cereal production [ 25 ].

Animal-based foods

By regulation, herbivores in organic production receive at least 60% of their feed intake as roughage on a dry matter basis. Depending on the seasonal availability of pastures, roughage can be fresh, dried, or silage. Also omnivores in organic production receive roughage as part of their daily feed, and poultry has access to pasture [ 6 ]. Corresponding regulations are for the most part missing in conventional animal production. In consequence, feeding strategies in organic animal production include a higher fraction of roughage compared to conventional systems, e.g. for dairy cows [ 188 , 189 ].

Fatty acids

Much of the focus of existing research on compositional differences of organic and conventional animal-based foods is on the fatty acid composition, with a major interest in omega-3 FAs due to their importance for human health. Some studies also address the content of minerals and vitamins.

The FA composition of the feed is a strong determinant of the fatty acid composition of the milk, egg or meat [ 190 , 191 ]. Grass and red clover, typical roughage feeds, contain between 30% and 50% omega-3 FA of total FA, while the concentrate feeds cereals, soy, corn, and palm kernel cake all contain below 10% omega-3 FA of total FA [ 190 ]. Like humans, farm animals turn a small part of dietary alpha-linolenic acid into long-chain omega-3 fatty acids with the help of elongase and desaturase enzymes.

For cow’s milk, a recent meta-analysis reports conclusively an approximately 50% higher content of total omega-3 fatty acids (as percent of total fatty acids) in organic compared to conventional milk [ 192 ], generally confirming earlier reviews [ 25 , 189 ]. Also, the content of ruminant FAs (a group of natural trans FAs produced in the cow’s rumen) is higher in organic milk. The content of saturated fatty acids, mono-unsaturated fatty acids and omega-6 PUFA was similar in organic and conventional milk [ 192 ].

A considerable statistical heterogeneity in these findings is reported. Individual differences described above are based on results from between 11 and 19 included studies. The observed differences are plausible, because they are directly linked to differences in feeding regimens. It should also be noted that several other factors influence the fatty acid composition in milk [ 193 ]. Specifically, the season (indoor vs. outdoor) has an impact on the feeding regime [ 188 ] and therefore on the omega-3 content of milk. However, the content of omega-3 fatty acids is higher in organic milk during both the outdoor and indoor seasons [ 189 ].

For eggs, it is likewise well described that the FA composition of the feed [ 190 ] and consequently the access to pasture [ 194 , 195 ] such as in organic systems, is a strong determinant of the fatty acid composition of the egg. However, only few studies have compared the FA composition in organic and conventional eggs [ 196 ] and a systematic review is not available. A higher omega-3 content of organic eggs is plausible but has not been documented.

A total of 67 original studies report compositional aspects of meat (mainly beef, chicken, lamb, and pork) from organic and conventional husbandry and were recently summarised in a meta-analysis [ 197 ]. Based on 23 and 21 studies respectively, the content of total PUFA and omega-3 PUFA was found to be significantly higher (23 and 47%, respectively) in organic compared to conventional meats. Weighted by average consumption in Europe, choosing organic instead of conventional meat, while maintaining a constant consumption, increased the intake of PUFA and omega-3 FA from meat by 17 and 22%, respectively [ 198 ]. These findings are plausible, especially in the case of omega-3 PUFA, considering the known differences in feeding regimens in organic and conventional production. However, few studies were available for each analysis, leaving many analyses with high uncertainty and poor statistical power. Furthermore, fatty acid metabolism differs between ruminants and monogastric animals [ 190 ]. Also, the actual differences in feeding regimens between conventionally and organically raised animals may differ by species, and by country. The variation between studies and between species was large, and the overall reliability of these results is therefore lower compared to milk above. This meta-analysis therefore indicates a plausible increase in omega-3 contents in organic meats, but more well-designed studies are needed to confirm this effect [ 197 ].

Dairy products account for 4–5% of the total PUFA intake in most European populations, while meat and meat products contribute another 7–23% [ 199 ]. The contribution of milk fat to omega-3 PUFA intake (approximated as intake of α-linolenic acid) has been estimated at 5–16% [ 200 , 201 ], while meat contributes with 12–17% [ 201 , 202 ]. The effect of exchanging organic for conventional dairy products on omega-3 PUFA intake while maintaining a constant consumption has not been examined rigorously. From the intake and composition data presented here, it can be estimated that choosing organic products would increase the average dietary omega-3 PUFA intake by 2.5–8% (dairy) and by a less certain 2.5–4% (meat). A recent preliminary estimate based on FAO food supply data resulted in similar numbers [ 198 ]. For certain population groups and fatty acids, these numbers could be higher, and an increased omega-3 PUFA consumption is generally desirable, as some subpopulations have a lower-than-recommended intake of omega-3 PUFA [ 203 ]. However, overall, the effect of the animal production system on omega-3 PUFA intake is minor, and no specific health benefits can be derived. Furthermore, other dietary omega-3 PUFA sources, specifically certain plant oils and fish, are available that carry additional benefits [ 204 , 205 , 206 ]. The existence of specific health benefits of ruminant trans fatty acids (as opposed to industrial trans fatty acids) is indicated by some studies [ 207 ] but not strongly supported [ 208 ]. Taking into account the actually consumed amounts of ruminant trans fatty acids, this is likely lacking public health relevance [ 208 ].

Trace elements and vitamins

A recent meta-analysis points to a significantly higher content of iodine (74%) and selenium (21%) in conventional milk and of iron (20%) and tocopherol (13%) in organic milk based on six, four, eight and nine studies respectively [ 192 ]. Iodine deficiency during pregnancy and infancy leads to impairment of brain development in the offspring, while excess iodine intake is associated with similar effects, and the window of optimal iodine intake is relatively narrow [ 209 ]. Overall, iodine intake in Europe is low and mild deficiency is prevalent [ 210 ]. The preferred way of correcting deficiency is salt iodisation [ 210 , 211 ], because salt is consumed almost universally and with little seasonal variation [ 212 ].

Feed iodine supplementation is not linked by regulation to the production system in the EU, as iodine is listed as approved feed additive, and the maximum amount of supplementation is the same for all milk production. Optimum dairy cow supplementation should be seen in relation to other national strategies for human iodine intake. This should also take into account human subpopulations with low or no intake of dairy products.

For tocopherol, selenium and iron, a higher content is generally desirable, and in the case of selenium milk is an important source. However, the concentration differences between organic and conventional milk are modest and based on a few studies only.

Antibiotic resistant bacteria

Overly prevalent prophylactic use of antibiotics in animal production is an important factor contributing to increasing human health problems due to resistant bacteria. Antibiotic use is strongly restricted in organic husbandry, which instead aims to provide good animal welfare and enough space in order to promote good animal health.

Antibiotics constitute an integral part of intensive animal production today, and farm animals may act as important reservoirs of resistant genes in bacteria [ 213 , 214 ]. It is reported that a substantial proportion (50 – 80%) of antibiotics are used for livestock production worldwide [ 215 ]. On a “per kg biomass” basis, in 2014, the amount of antimicrobial drugs consumed by farm animals was slightly higher than the antimicrobial drugs used for humans in the 28 EU/EEA countries surveyed, with substantial differences between countries regarding volumes and types of substances [ 216 ].

In recent decades, there have been increasing concerns that the use of antibiotics in livestock would contribute to impairing the efficiency of antibiotic treatment in human medical care [ 217 ]. Despite the lack of detailed information on transmission routes for the vast flora of antibiotic-resistant bacteria and resistance genes, there is a global need for action to reduce the emerging challenges associated with the reduced efficiency of antibiotics and its consequences for public health, as well as for the environment more generally [ 218 , 219 ].

The use of antibiotics may increase the economic outcome of animal production [ 220 , 221 ], but the spreading of multi-resistant genes is not just a problem for the animal production sector alone. Negative effects are affecting parts of society not directly associated with livestock production. This means that the costs of side effects are borne by society in general and not primarily by the agricultural sector. However, the generalisation cannot be made that all antibiotic treatment in farm animals represents a hazard to public health [ 222 , 223 ].

The use of antibiotics in intensive livestock production is closely linked to the housing and rearing conditions of farm animals. Specific conditions for conventional livestock farming in different countries, as well as farmers’ attitudes, may differ between countries, e.g. conventional pig production at above EU animal welfare standards and farmers’ attitudes in Sweden [ 224 , 225 ]. Conventional production is typically aiming for high production levels with restricted input resources such as space, feed etc., and these conditions may cause stress in the individual animal as it is unable to cope with the situation, e.g. in pig production [ 226 , 227 ]. This means that higher stocking density, restricted space and barren environment are factors increasing the risk of the development of diseases, and therefore it is more likely that animals under these conditions need antibiotic treatments.

Organic production aims for less intensive animal production, which generally means that the animals have access to a more spacious and enriched environment, access to an outdoor range and restricted group sizes, and other preconditions [ 70 ]. This would ultimately decrease the need for preventive medication of the animals as they can perform more natural behaviours and have more opportunity to maintain a good health. However, in practice, the health status of organic livestock is complex and disease prevention needs to be adapted to the individual farm [ 228 ]. A report on the consequences of organic production in Denmark demonstrates that meeting the requirements of organic production has several positive consequences in relation to animal welfare and health [ 70 ].

According to EU regulations, routine prophylactic medication of animals in organic production is not allowed. However, diseases should be treated immediately to avoid suffering, and the therapeutic use of antibiotics is allowed, but with longer withdrawal periods than in conventional production [ 5 ]. Furthermore, products from animals treated more than three times during 12 months, or, if their productive lifecycle is less than 1 year, more than once, cannot be sold as organic [ 6 ]. This means that therapeutically the same antibiotics used in conventional farming may be used in organic farming, but under different conditions. For example, antibiotics mainly used for sub-therapeutic treatment as prophylaxis are never considered in organic production.

While the organic regulations aim for a low use of antibiotics in livestock production, the actual use of antibiotic drugs in European organic compared to conventional animal husbandry is not comprehensively documented. Scattered studies indicate that the antibiotic use generally is substantially higher in conventional compared to organic systems, especially for pigs (approximately 5 – 15-fold higher) [ 229 , 230 ]. In studies from Denmark [ 231 ] and the Netherlands [ 232 ], the antibiotic use in dairy cows was 50% and 300% higher in conventional compared to organic systems, although a Swedish study found no differences in disease treatment strategies between organic and conventional dairy farms, e.g. for mastitis [ 233 ]. While only sparingly documented (e.g. [ 234 , 235 ]), there is only little use of antibiotics in EU organic broiler production. This is a consequence of regulations prohibiting prophylactic use and prescribing long withdrawal periods before slaughter [ 6 , 236 ], in conjunction with the fact that it is not feasible to treat single animals in broiler flocks. In conventional broiler production, antibiotic use is common (e.g. [ 237 , 238 , 239 ]).

Recently, gene sequencing has revealed that the routes of transmission of resistance genes between human and farm animal reservoirs seem to be complex [ 213 , 222 , 240 ]. Nevertheless, a recent EFSA report found that “in both humans and animals, positive associations between consumption of antimicrobials and the corresponding resistance in bacteria were observed for most of the combinations investigated” [ 241 ], which has subsequently been strengthened [ 216 ]. In addition to direct transmission between animals and humans via contact or via food, resistant strains and resistance genes may also spread into the environment [ 242 ].

Previously, it has been postulated that a reduced need and use of antibiotics in organic livestock production will diminish the risk of development of antibiotic resistance [ 243 ], and this has also been demonstrated with regard to resistant E. coli in organic pigs compared to conventional pigs [ 244 ]. It has also been shown that the withdrawal of prophylactic use of antibiotics when poultry farms are converted from conventional to organic production standards leads to a decrease in the prevalence of antibiotic-resistant Salmonella [ 245 ].

Resistant bacteria may be transferred within the production chain from farm to fork [ 246 ]. It has been found that organic livestock products are less likely to harbour resistant bacteria in pork and chicken meat [ 25 ].

In pig production, particular attention has been paid to methicillin-resistant Staphylococcus aureus (MRSA), and in Dutch and German studies, for example, MRSA has been isolated in 30 and 55% respectively of all pigs tested [ 247 , 248 ]. Furthermore, it has been found that healthy French pig farmers are more likely to carry MRSA than control persons [ 249 ] and that they carry similar strains of MRSA to those found on their pig farms [ 250 ]. However, the prevalence of MRSA in pig production may differ between conventional and organic farms, and in a meta-study in 400 German fattening pig herds, the odds ratio (OR) for MRSA prevalence was 0.15 (95% CI 0.04, 0.55) in organic ( n  = 23) compared to conventional ( n  = 373) pig farms [ 248 ]. Multivariate adjustment for potential risk factors rendered this association non-significant, suggesting that it was carried by other factors, including factors that are regulated in or associated with organic production, such as non-slatted floors, no use of antibiotics, and farrow-to-finish herd types. Furthermore, even if there are considerable differences in antibiotic use between countries, it has been found that antibiotic resistance is less common in organic pigs compared to conventional pigs in France, Italy, Denmark, and Sweden [ 251 , 252 ].

Although it is rare for conventional farms to adopt knowledge about management and housing from organic production except when converting farms in line with organic standards, there may be options to improve animal health and welfare by knowledge transfer to conventional farms in order to reduce the use of antibiotics [ 253 ].

Within organic production, labelling requires full traceability in all steps in order to guarantee the origin of the organic products being marketed [ 5 ]. Application of the general principle of organic regulations about transparency throughout the food chain can be used to mitigate emerging problems of transmission of antimicrobial resistance. However, transition to organic production for the whole livestock sector would, on its own, be only part of a solution to the antibiotics resistance issue, because factors outside animal production, such as their use in humans, will be unaffected.

An assessment of the human health effects associated with diets based on organic food production must rely on two sets of evidence. The first set of evidence is the epidemiological studies comparing population groups with dietary habits that differ substantially in regard to choices of organic v. conventional products. These studies are to some extent complemented by experimental studies using animal models and in vitro models. The second set of data relies on indirect evidence such as chemical analyses of food products and their contents of nutrients and contaminants or antibiotic use and resistance patterns, in onsequence of agricultural production methods. Both sets of results are associated with certain strengths and weaknesses.

The few human studies that have directly investigated the effects of organic food on human health have so far yielded some observations, including indications of a lower risk of childhood allergies, adult overweight/obesity [ 18 , 46 ] and non-Hodgkin lymphoma (but not for total cancer) [ 37 ] in consumers of organic food. Owing to the scarcity or lack of prospective studies and the lack of mechanistic evidence, it is presently not possible to determine whether organic food plays a causal role in these observations. However, it has also been observed that consumers who prefer organic food have healthier dietary patterns overall, including a higher consumption of fruit, vegetables, whole grains, and legumes and a lower consumption of meat [ 18 , 29 , 37 ]. This leads to some methodological difficulties in separating the potential effect of organic food preference from the potential effect of other associated lifestyle factors, due to residual confounding or unmeasured confounders. These dietary patterns have in other contexts been associated with a decreased risk of several chronic diseases, including diabetes and cardiovascular disease [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. It is therefore expected that consumers who regularly eat organic food have a decreased risk of these diseases compared to people consuming conventionally-produced food, as a consequence of dietary patterns. These dietary patterns appear also to be more environmentally sustainable than average diets [ 254 ].

Food analyses tend to support the notion that organic foods may have some health benefits. Consumers of organic food have a comparatively low dietary exposure to pesticides. Although chemical pesticides undergo a comprehensive risk assessment before market release in the EU, there are important gaps in this risk assessment. In some cases, specifically for cognitive development during childhood as an effect of organophosphate insecticide exposure during pregnancy, epidemiological studies provide evidence of adverse effects [ 140 , 255 ]. Organic agriculture allows for lower pesticide residues in food and may be instrumental in conventional agriculture’s transition towards integrated pest management by providing a large-scale laboratory for non-chemical plant protection.

This review emphasizes that pesticide exposure from conventional food production constitutes a main health concern. A key issue that has only recently been explored in biomedical research is that early-life exposure is of major concern, especially prenatal exposure that may harm brain development. Most insecticides are designed to be toxic to the insect nervous system, but many higher species depend on similar neurochemical processes and may therefore all be vulnerable to these substances [ 129 ]. Besides insecticides, experimental studies suggest a potential for adverse effects on the nervous system for many herbicides and fungicides as well [ 99 ]. However, no systematic testing is available since testing for neurotoxicity – especially developmental neurotoxicity – has not consistently been required as part of the registration process, and allowable exposures may therefore not protect against such effects. At least 100 different pesticides are known to cause adverse neurological effects in adults [ 129 ], and all of these substances must therefore be suspected of being capable of damaging also developing brains. The need for prevention of these adverse outcomes is illustrated by the recent cost calculations [ 140 ] and the additional risk that pesticide exposures may lead to important diseases, such as Parkinson’s disease, diabetes and certain types of cancer.

The outcomes in children and adults and the dose-dependences are still incompletely documented, but an additional limitation is the lack of exposure assessments in different populations and also their association with dietary habits. The costs from pesticide use in regard to human health and associated costs to society are likely to be greatly underestimated due to hidden and external costs, as recently reviewed [ 256 ]. Also, gaps in the regulatory approval process of pesticides may lead to important effects being disregarded and remaining undetected.

In regard to nutrients, organic dairy products, and probably also meat, have an approximately 50% higher content of omega-3 fatty acids compared to conventional products. However, as these products only are a minor source of omega-3 fatty acids in the average diet, the nutritional significance of this effect is probably low (although this has not been proven). The nutritional content of crops is largely unaffected by the production system, according to current knowledge. Vitamins and minerals are found in similar concentrations in crops from both systems. One exception is the increased content of phenolic compounds found in organic crops, although this is still subject to uncertainty despite a large number of studies that have addressed this issue. Accordingly, although in general being favourable for organic products, the established nutritional differences between organic and conventional foods are small, and strong conclusions for human health cannot currently be drawn from these differences. There are indications that organic crops contain less cadmium compared to conventional crops. This is plausible, primarily because mineral fertiliser is an important source of cadmium in soils. However, notably, long-term farm pairing studies or field trials that are required for definitely establishing or disproving this relationship are lacking. Owing to the high relevance of cadmium in food for human health, this lack of research constitutes an important knowledge gap.

With respect to the development of antibiotic resistance in bacteria, organic animal production may offer a way of restricting the risks posed by intensive production, and even decreasing the prevalence of antibiotic resistance. Organic farm animals are less likely to develop certain diseases related to intensive production compared to animals on conventional farms. As a consequence, less antibiotics for treating clinical diseases are required under organic management, where their prophylactic use also is strongly restricted. This decreases the risk for development of antibiotic resistance in bacteria. Furthermore, the transparency in organic production may be useful for acquiring knowledge and methods to combat the rising issues around transmission of antimicrobial resistance within food production.

It appears essential that use of antibiotics in animal production decreases strongly or completely ceases in order to decrease the risk of entering a post-antibiotic era. The development and upscaling of rearing systems free or low in antibiotic use, such as organic broiler production, may be an important contribution of organic agriculture to a future sustainable food system.

Most of the studies considered in this review have investigated the effects of agricultural production on product composition or health. Far less attention has been paid to the potential effects of food processing. Processing may affect the composition of foods and the bioavailability of food constituents. It is regulated [ 5 ] and recognised [ 257 ] that food additives are restricted for organic products compared to conventional products. It is also recognised that the degree of food processing may be of relevance to human health [ 258 , 259 ]. In organic food processing, the processing should be done “with care, preferably with the use of biological, mechanical and physical methods” [ 5 ] but there are no specific restrictions or guidelines. With the exception of chemical additives, it is unknown whether certain food processing methods (e.g. fermentation of vegetables, pasteurisation of vegetables) are more prevalent in organic or conventional products or consumption patterns, or whether such differences are of relevance to human health.

The scopes of two recent reports, from Norway [ 260 ] and Denmark [ 70 ], in part overlap with the present work. Broadly, the reviewed results and conclusions presented in those reports are in line with this article. For several topics, important new evidence has been published in recent years. Consequently, in some cases stronger conclusions can be drawn today. Furthermore, the present review includes epidemiological studies of pesticide effects in the evidence base reviewed.

Over all, the evidence available suggested some clear and some potential advantages associated with organic foods. The advantages in general do not necessarily require organic food production as strictly defined in current legislation. Certain production methods, such as changes in the use of pesticides and antibiotics, can be implemented in conventional production, e.g. supporting a development towards a sustainable use of pesticides [ 261 ]. Thereby, practices and developments in organic agriculture can have substantial public health benefits also outside the organic sector.

Diet choices and the associated food production methods also have important impacts on environmental sustainability [ 254 ]. Consumption patterns of consumers preferring organic food [ 16 , 18 , 19 , 37 , 47 ] seem to align well with sustainable diets [ 2 ]. These consumption patterns also show some similarities with the Mediterranean Diet [ 262 , 263 , 264 , 265 ] and with the New Nordic Diet [ 266 , 267 , 268 , 269 ], with lower dietary footprints in regard to land use, energy and water consumption, and greenhouse gas emissions compared to concurrent average diets. Further evaluation is needed to assess the extent to which organic food systems can serve as example of a sustainable food systems [ 270 ].

For the development of healthy and environmentally-sustainable food systems in the future, production and consumption need to be considered in an integrated manner [ 2 , 271 ]. While an evaluation of overall impacts of different food systems on environmental sustainability would be highly desirable [ 270 ], the present review has attempted to assess the human health issues in regard to organic production methods and consumer preferences for organic food, both important aspects of sustainability.

Conclusions

Suggestive evidence indicates that organic food consumption may reduce the risk of allergic disease and of overweight and obesity, but residual confounding is likely, as consumers of organic food tend to have healthier lifestyles overall. Animal experiments suggest that growth and development is affected by the feed type when comparing identically composed feed from organic or conventional production. In organic agriculture, the use of pesticides is restricted, and residues in conventional fruits and vegetables constitute the main source of human exposures. Epidemiological studies have reported adverse effects of certain pesticides on children’s cognitive development at current levels of exposure, but these data have so far not been applied in the formal risk assessments of individual pesticides. The nutrient composition differs only minimally between organic and conventional crops, with modestly higher contents of phenolic compounds in organic fruit and vegetables. There is likely also a lower cadmium content in organic cereal crops. Organic dairy products, and perhaps also meats, have a higher content of omega-3 fatty acids compared to conventional products, although this difference is of likely of marginal nutritional significance. Of greater concern is the prevalent use of antibiotics in conventional animal production as a key driver of antibiotic resistance in society; antibiotic use is less intensive in organic production. Thus, organic food production has several documented and potential benefits for human health, and wider application of these production methods also in conventional agriculture, e.g., in integrated pest management, would therefore most likely benefit human health.

Abbreviations

3-phenoxybenzoic acid

Attention deficit hyperactivity disorder

Acceptable daily intake

Acceptable operator exposure level

Acute reference dose

Body mass index

Bovine spongiform encephalopathy

Center for the health assessment of mothers and children of Salinas

Confidence interval

Dialkyl phosphate

Dichlorodiphenyltrichloroethane

Deoxynivalenol

Escherichia coli

European Economic Area

European Food Safety Authority

European Union

Food and Agriculture Organization of the United Nations

Hazard index

Immunoglobulin G

Integrated pest management

Intelligence quotient

Maximum residue level

Methicillin-resistant Staphylococcus aureus

National health and nutrition examination survey

Ochratoxin A

Persistent, bioaccumulative, toxic

Perturbateurs endocriniens: étude longitudinale sur les anomalies de la grossesse, l’infertilité et l’enfance (endocrine disruptors: longitudinal study on disorders of pregnancy, infertility and children)

Polyunsaturated fatty acid

Relative risk

Standardized mean difference

Tolerable daily intake

United Kingdom

United States

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Acknowledgements

The present review was initiated after a workshop entitled “The impact of organic food on human health” organized by the European Parliament in Brussels, Belgium on 18 November 2015, in which several of the authors participated, and which resulted in a formal report to the European Parliament [ 199 ]. The present review is an updated and abbreviated version aimed for the scientific community. The authors would like to thank the following colleagues for critically reading and reviewing sections of the review: Julia Baudry, Nils Fall, Birgitta Johansson, Håkan Jönsson, Denis Lairon, Kristian Holst Laursen, Jessica Perry, Paula Persson, Helga Willer and Maria Wivstad. The authors would also like to thank Marcin Barański and Gavin Stewart for providing additional meta-analyses of cadmium contents in organic and conventional crops. The STOA staff is acknowledged for organising the seminar in Brussels.

The Science and Technology Options Assessment Panel of the European Parliament provided funding for writing this paper, travel support to the authors and coverage of incidental expenses.

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Swedish University of Agricultural Sciences (SLU), Centre for Organic Food and Farming (EPOK), Ultuna, Sweden

University of Southern Denmark, Department of Public Health, Odense, Denmark

Helle Raun Andersen & Philippe Grandjean

Swedish University of Agricultural Sciences (SLU), Department of Animal Environment and Health, Skara, Sweden

Stefan Gunnarsson

University of Copenhagen, Department of Nutrition, Exercise and Sports, Frederiksberg, Denmark

Johannes Kahl

Research Unit on Nutritional Epidemiology (U1153 Inserm, U1125 INRA, CNAM, Université Paris 13), Centre of Research in Epidemiology and Statistics Sorbonne Paris Cité, Bobigny, France

Emmanuelle Kesse-Guyot

Warsaw University of Life Sciences, Department of Functional & Organic Food & Commodities, Warsaw, Poland

Ewa Rembiałkowska

Scientific Foresight Unit (Science and Technology Options Assessment [STOA]), Directorate-General for Parliamentary Research Services (EPRS), European Parliament, Brussels, Belgium

Gianluca Quaglio

Harvard T.H. Chan School of Public Health, Department of Environmental Health, Boston, USA

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Contributions

AM, PG and GQ drafted the introduction. EKG drafted the human studies section. JK drafted the food consumption pattern aspects in the human studies section and in the discussion. AM and ER drafted the in vitro and animal studies section. HRA and PG drafted the pesticides section. AM and ER drafted the plant foods section. AM drafted the animal foods section. SG drafted the antibiotic resistance section. AM and PG drafted the discussion and conclusions. All authors commented on the entire draft and approved the final version.

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The authors have no conflict of interest to report. AM has participated as an expert witness in a court case in Sweden related to pesticide exposure from organic and conventional foods (Patent and Market Courts, case no. PMT11299–16), but did not benefit financially from this effort. PG is an editor of this journal but recused himself from participating in the handling of this manuscript.

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Mie, A., Andersen, H.R., Gunnarsson, S. et al. Human health implications of organic food and organic agriculture: a comprehensive review. Environ Health 16 , 111 (2017). https://doi.org/10.1186/s12940-017-0315-4

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Received : 22 May 2017

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Published : 27 October 2017

DOI : https://doi.org/10.1186/s12940-017-0315-4

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Nutrition-related health effects of organic foods: a systematic review

Affiliation.

• 1 Department of Epidemiology Population Health, London School of Hygiene & Tropical Medicine, London, UK. [email protected]
• PMID: 20463045
• DOI: 10.3945/ajcn.2010.29269

Background: There is uncertainty over the nutrition-related benefits to health of consuming organic foods.

Objective: We sought to assess the strength of evidence that nutrition-related health benefits could be attributed to the consumption of foods produced under organic farming methods.

Design: We systematically searched PubMed, ISI Web of Science, CAB Abstracts, and Embase between 1 January 1958 and 15 September 2008 (and updated until 10 March 2010); contacted subject experts; and hand-searched bibliographies. We included peer-reviewed articles with English abstracts if they reported a comparison of health outcomes that resulted from consumption of or exposure to organic compared with conventionally produced foodstuffs.

Results: From a total of 98,727 articles, we identified 12 relevant studies. A variety of different study designs were used; there were 8 reports (67%) of human studies, including 6 clinical trials, 1 cohort study, and 1 cross-sectional study, and 4 reports (33%) of studies in animals or human cell lines or serum. The results of the largest study suggested an association of reported consumption of strictly organic dairy products with a reduced risk of eczema in infants, but the majority of the remaining studies showed no evidence of differences in nutrition-related health outcomes that result from exposure to organic or conventionally produced foodstuffs. Given the paucity of available data, the heterogeneity of study designs used, exposures tested, and health outcomes investigated, no quantitative meta-analysis was justified.

Conclusion: From a systematic review of the currently available published literature, evidence is lacking for nutrition-related health effects that result from the consumption of organically produced foodstuffs.

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Research Article

Is it really organic? Credibility factors of organic food–A systematic review and bibliometric analysis

Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Agricultural Business and Economics, Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary

Roles Methodology, Supervision, Validation

Roles Conceptualization, Data curation, Methodology, Supervision, Validation, Writing – review & editing

• László Bendegúz Nagy, 
• Zoltán Lakner, 
• Ágoston Temesi

• Published: April 14, 2022
• https://doi.org/10.1371/journal.pone.0266855
• Reader Comments

Consumer trust and organic food product credibility play a crucial role in understanding consumer behavior. The aim of this review is to identify extrinsic factors which influence consumers’ perceived trust in organic food. The research was conducted based on the PRISMA guidelines. During our search, 429 articles were found, from which 55 studies were selected for further analysis. To assess the connection between the selected articles, a bibliometric analysis was done with VOSViewer and CitNetExplorer software. The following factors were identified as influencing the credibility of organic food: labeling, certification, place of purchase, country of origin, brand, price, communication, product category, packaging. From these, labeling, certification, and country of origin are well-researched factors in relation to credibility. The significance of the other discovered factors is supported; nonetheless, further research is needed to evaluate their effect on consumer trust.

Citation: Nagy LB, Lakner Z, Temesi Á (2022) Is it really organic? Credibility factors of organic food–A systematic review and bibliometric analysis. PLoS ONE 17(4): e0266855. https://doi.org/10.1371/journal.pone.0266855

Editor: Patrizia Restani, Università degli Studi di Milano, ITALY

Received: November 8, 2021; Accepted: March 28, 2022; Published: April 14, 2022

Copyright: © 2022 Nagy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files. The dataset used for bibliometric analysis was uploaded as Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The importance of organic food is well indicated by the steadily growing market. As sustainability is more and more in the focus of food product development, organic food is becoming a successful concept in the food industry [ 1 ]. Whilst in 2008, the organic food market reached 50,9 billion USD [ 2 ], the sales of organic food doubled in only a decade, up to 119 billion USD in 2019 [ 3 ].

This growth in organic food sales can be attributed to an increased demand for organic food. The vast majority of this demand originates from North America and Europe, nonetheless, local organic markets are rising in Asia, Latin America, and Africa [ 1 ]. On account of the increasing demand for organic food, consumer trust has gained great interest among researchers [ 4 ]. However, no review article has been written on this particular topic so far.

Credibility is a relatively new research field in the context of consumable products. Green et al. [ 5 ], Plasek & Temesi [ 6 ] and Küster-Boluda & Vila [ 7 ] examined credibility in the case of alternative medicine, functional food, and low-fat food, respectively. Other researchers have explored fields related to food products in terms of credibility. Anders et al. [ 8 ] examined it within third-party certification in the food supply chain, Kumar & Polonsky [ 9 ] researched it from food retailer perspective.

Organic food can be defined based on Kahl et al.’s [ 10 ] definition: “Organic food is produced within a regulated and certified production process.” According to them, food can be described by intrinsic or extrinsic quality attributes. These attributes are strongly related to consumer expectations and trust [ 11 ].

Organic food is considered as a credence good, because there is an information asymmetry between the consumers and producers [ 12 ]. In the case of credence quality, the consumer of a product can not fully evaluate the quality of a particular good [ 13 ]. In terms of organic food, it means that the presence or absence of the organic attributes is not detectable by consumers even after purchase and consumption of the product [ 12 ].

The most widely accepted definition of trust comes from Rousseau et al. [ 14 ]: “a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intention or behaviour of another.” From our viewpoint, it means that the consumers’ tolerance for ambiguity is increased as a result of an inner assurance or conviction [ 15 ]. According to Thorsøe et al. [ 15 ] there is a strong link and dependence between trust and credibility, because actors, such as producers or retailers, must be credible to generate trust in consumers, although they can not control the consumers’ perception, which can generate distrust.

Research methodology

Our purpose in this review is to find all extrinsic, product-related factors which determine credibility and trust in organic food products. To detect those factors, we used PRISMA guidelines for this review. PRISMA enables review authors to summarize evidence in a selected field accurately and reliably [ 16 ]. There is no existing review protocol for this kind of research field.

For this review, we used Web of Science and SCOPUS search engines, as those databases considered the widest and recommended sources in our research field [ 17 ]. We conducted the searches during October 2021, the last search was done on 15 th October 2021. To find all relevant articles about the credibility factors of organic food, we used several search phrases. The composition of search expressions had been supported by term frequency–inverse document frequency method (TF-IDF) on some randomly chosen text from the relevant field. The term “organic food” or “organic product” or “organic produce” or “organic” had to be in the title of the article, as well as “consumer” or “consumption”. These phrases narrowed down the scope of the articles mostly to consumer-related topics of organic food. In addition, the abstracts of the articles had to contain at least one of the following phrases: “trust”, “credence”, “credible”, “credibility”, “scepticism”, “beliefs”, “authenticity” or “communication”. With the above mentioned search phrases we ran pre-tests on the Web of Science search engine which proved to be accurate to describe our research topic. We did not limit the publication date of the studies, because the earliest study that we found on this particular topic was from 2002. For these search phrases, we found 212 results in Web of Science and 218 results in SCOPUS. From these, 162 records were duplicates, which were discarded (see Fig 1 ).

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https://doi.org/10.1371/journal.pone.0266855.g001

To screen and select the articles for our review, we used Covidence online software, which enabled us to evaluate articles by two authors independently in 2 steps. In the first step, we evaluated the remaining 268 articles by reading the abstract only. In this step, we excluded 106 studies, which were irrelevant to our topic. In some cases, it was not unequivocal from the abstract if an article was relevant, so these studies were selected for the full-text assessment.

In the second step, 162 articles were assessed for eligibility by reading the full-text. During this step, 107 studies were excluded for various reasons. The most common reason was being irrelevant for our research. These articles contained the required search words, although organic food consumption behavior was not assessed in the context of credibility or trust. 15 studies were excluded because of poor results, 8 articles were in a foreign language, 3 studies included a conceptual model with no results explained and 3 articles were not accessible.

Besides the systematic review, a bibliometric analysis was conducted on the selected articles to reveal the connection between the identified credibility factors. For this purpose, two different software packages were used. VOSviewer (version 1.6.15) software is capable of visualizing networks and forming clusters, which enables further analysis [ 18 ]. CitNetExplorer (version 1.0.0) can be used to study the development of a research field, which can support the literature review [ 19 ].

Only a few research has tried to tease out all possible credibility factors. Danner & Menapace [ 20 ] found 5 authenticity-related themes: organic label, origin, retail outlet/brand, packaging, product category. Tangnatthanakrit et al. [ 21 ] proposed 5 factors, which influence organic food trust: control, competence, characteristics, communication and community. Some studies list other factors as well, like natural taste, merchandising, knowledge, scarcity, and tourism [ 22 ], although there is no evidence behind these factors as to their influence on the credibility of organic food.

From the selected, manually analyzed 55 articles (see Table 1 ), we identified the following 9 exogenous factors which can influence the credibility of a food product: labeling, certification, place of purchase, country of origin, brand, price, communication, product category, and packaging.

https://doi.org/10.1371/journal.pone.0266855.t001

Bibliometric analysis

Of the selected 55 papers, more than half were published after 2016, which indicates the current interest in this research field (see Fig 2 ). Only 7 studies were conducted before 2010.

https://doi.org/10.1371/journal.pone.0266855.g002

In terms of location, most of the research was conducted in European countries. More than 1/3 of the articles report results from Asian countries, and only 8 papers write about North American consumers, which does not represent the actual size of the organic food market of these continents. There are 2 articles from Brazil and Australia each, which provide valuable results as well.

Fig 3 shows the connections and co-occurrence of the identified credibility factors. With the VOSviewer software, the terms related to credibility, trust, and the influencing factors were chosen from the abstracts. The size of each circle represents the number of occurrences in the selected articles, and co-occurrence is illustrated by the distance between the circles.

https://doi.org/10.1371/journal.pone.0266855.g003

Based on the connections of the 9 identified credibility factors, 4 clusters could be identified. The red cluster contains the most terms, and trust is the most relevant term in the selected papers. Trust is strongly related to organic label and shop, although retailer and brand are also significant to trust, which correlates with the findings of Padel & Foster [ 23 ]. In the blue cluster, labeling, certification, price, authenticity, and low trust are very closely related to each other. Retail chain and product category also belong to this cluster, which supports the results of Danner & Menapace [ 20 ].

Communication, which is mentioned by Tangnatthanakrit et al. [ 21 ], is in the middle of the light green cluster, and it is very close to labeling and concern, although concern belongs to the green cluster. Logo, inspection, and certification also appear in the light green cluster with the European Union, which shows that most of the research related to organic logos was about the EU organic logo. Concern, distribution, trust issue, and country are the main terms in the green cluster. These terms represent the connection between country of origin and consumer concerns. Although these clusters do not represent each credibility factor, this analysis is a good indicator of the connections between the factors.

The visualization capability of CitNetExplorer has been a useful tool because it allowed us to find the most relevant publications and investigate the intellectual roots of our research topic. With the CitNetExplorer, connections between the citations of the chosen 55 papers can be visualized, as seen in Fig 4 .

https://doi.org/10.1371/journal.pone.0266855.g004

Each circle represents a publication, and publications are labeled with the first author’s last name. Vertical location shows publication year, with old articles at the top and new publications at the bottom. In the horizontal direction, publications are arranged according to citation relationships. Highly cited publications that take into account direct and indirect citation relationships tend to be closer to each other horizontally. Publications that are less relevant with respect to other citations are further away [ 24 ].

Nine publications were cited 10 or more times, from which 3 papers are included in the review. The article by Padel & Foster [ 23 ] was cited most frequently, namely 21 times. They investigated qualitatively consumers purchasing decisions of organic food. From our perspective, their most important findings were that labeling, certification and the country of origin play an important role in the perceived trust of organic food, which tend to be the major factors in later publications as well.

Almost the same amount, 20 papers cited the review of Hughner et al. [ 25 ], in which they explore the reasons why people buy organic food. This publication does not mention trust related factors of organic food, although it gives important conclusions about the nature of organic food consumption.

Four articles were cited 13 times, from which 3 were published before 2010. Krystallis & Chryssohoidis [ 26 ] discussed the importance of labeling, certification and the place of purchase from the credibility perspective. Lea & Worsley [ 27 ] investigated Australian consumers’ beliefs about organic food. Aertsens et al.’s [ 28 ] review is discussing the personal determinants of organic food consumption.

Nuttavuthisit & Thøgersen’s [ 29 ] article was published in 2017, although it was cited 13 times, which shows the relevance of this paper to our topic. As they did a qualitative research about the consumer trust in Thailand, it offers important statements about the credibility factors of organic food in emerging countries.

The oldest cited publication is from 1973, written by Darby & Karni [ 13 ]. In their publication, they clarify the meaning of the credence attribute, which explains the high citation number.

Certification

Half of the selected articles—28 by number—mention certification as one of the most important factors influencing the credibility of organic food. Organic logos are discussed in this part because these logos represent the certification itself, and usually, it is a legal requirement as well.

Evaluating the selected research, it can be observed that generally, consumers have lower trust towards organic food with a certification from a developing country. For example, general trust in the certification system is low in Thailand [ 27 ], but it can create trust if consumers know about the certification body [ 30 ]. The preference for certification from a developed country and lack of trust in the local certifiers can be seen in the case of Brazilian [ 31 ], Russian [ 32 ], Indian [ 33 ], Vietnamese [ 34 ], and Chinese [ 35 ] consumers.

We observed some opposite results as well. Malaysian consumers trust their national organic logo, myOrganic [ 36 ]. In the case of oolong tea, Chinese consumers prefer Chinese organic certification [ 37 ].

In the case of European consumers, we can see a more nuanced picture. Janssen & Hamm [ 38 ] examined consumer reactions to organic logos in six European countries. Their results show that organic logos create consumer trust; well known and trusted logos are perceived by the consumers as having stricter standards and control system behind them. Consumers from the United Kingdom trust their national logo more than the European Union organic logo or an organic product without any logo [ 39 ]. Czech, Danish, German, Italian and UK consumers also have lower trust towards European Union organic logo compared to their national organic logo [ 40 ], although it is important to mention, that compulsory EU logo usage was recently implemented by the time of data collection of the research. Based on the research of Zander et al. [ 41 ], which was performed in six European countries, trust in the certification system and organic logo can be differentiated by types of consumers. Regular and occasional organic consumers trust organic certification regardless of its origin, on the other hand, consumers who have higher knowledge and involvement towards organic food have lower trust in global certifications.

The organic food market is different in the United States and Canada, although consumer attitudes are similar to the European market. Certification plays an important role in the credibility of organic food in the case of Canadian consumers [ 42 ]. Both Kim et al. [ 43 ] and Van Loo et al. [ 44 ] agree that in the case of consumers from the United States, an USDA organic logo creates more trust than any generic organic logo.

Overall, most of the research shows that certification has a significant role in the credibility of organic food, but Yin et al. [ 45 ] question the importance of it. According to them, certification has no impact on consumer trust in the case of milk products. Tangnatthanakrit et al. [ 21 ] obtained similar results during their research in Thailand.

Labeling is as important for a product to be credible as certification. Labeling is a general term in this case since it partly covers other factors as well, like certification, brand, or packaging. There is no clear distinction amongst the authors between labeling and organic logos; some research considers organic logos as part of the labeling. In this review, we consider labeling as information about the product displayed on the packaging, and organic logos were discussed separately in the previous sub-section.

According to Teng & Wang [ 46 ], Essoussi & Zahaf [ 42 ], Lee et al. [ 47 ], Chen & Lobo [ 48 ], Padel & Foster [ 23 ], and Sobhanifard [ 49 ] labeling is significant to the creation of consumer trust in the case of organic food. Most research shows a positive relationship between labeling and credibility, although a lot of them challenge it as well. For example, Thorsøe et al. [ 15 ] proved that Danish consumers trusted organic labeling, Meyerding & Merz [ 50 ] used an eye-tracking method and found evidence that the presence of an organic label created trust in the product. On the other hand, based on Činjarević et al. [ 51 ], Croatian consumers are skeptical about the organic claims on labeling; Tung et al. [ 52 ] agree that Taiwanese consumers do not trust organic labels.

Trust in labeling can change over time, as Vittersø & Tangeland’s [ 53 ] study in Norway shows. They compared data from 2000 and 2013, and found that Norwegian consumers had more trust in organic labeling in 2000 than in 2013. Also, the content of the labeling is not indifferent for credibility. Nutritional values on the labeling enhance trust in the organic labels, based on the research of Liang & Lim [ 54 ].

Place of purchase

Of the selected articles, nineteen pay attention to the place of purchase as a factor influencing credibility. The majority of those papers, namely 16 cover only retailers, 2 paper mention supermarkets, and only 1 inspects trust from the perspective of online shops. Unfortunately, we did not find any research on organic specialty shops, direct sale, or farmers’ market, although these sales channels can be important in the case of organic food.

We found miscellaneous results regarding supermarkets and organic food trust. Mostly in the United States, United Kingdom, and Canada, consumers have low trust in organic food if it is sold in a superstore [ 23 , 55 , 56 ]. Nonetheless, research has confirmed that positive consumer perception of a retailer has a positive impact on the credibility of the organic food sold there [ 57 – 61 ]. In their work, Pivato et al. [ 11 ] show a positive relationship between the corporate social responsibility (CSR) activities of a retailer and the trust in the organic food sold in their stores.

Many retailers are selling organic food under private labels, so there is a bit of an overlap between the place of purchase and the branding of a product. According to Perrini et al. [ 62 ] consumers are more likely to trust private-label organic products if they consider the retailer as socially responsible.

Organic food retail could not avoid the spread of e-commerce, although research is very limited in this field. Yue et al. [ 63 ] investigated the influence of online product presentation on organic chicken breast. Based on their research, the media richness of online product presentation and review lengths of organic products impact the trust in organic food.

Country of origin

The origin of organic food has significant importance for perceived credibility. This topic was partly discussed in subsection Certification, because organic food is usually certified in the country where it comes from. As in the case of certification, we can see differences between consumers of developed and developing countries, although based on Thøgersen et al. [ 64 ] country of origin is an even more important cue for consumers than organic labeling both in developed and developing countries.

According to Lee et al. [ 47 ], Yip & Janssen [ 65 ], and Thorsøe et al. [ 15 ] Taiwanese, Hong Kong, and Danish consumers have higher trust in local organic food compared to imported ones. Canadian and UK consumers are skeptical about imported organic food [ 23 , 56 ].

Based on the findings of Bruschi et al. [ 32 ], Chen et al. [ 35 ], Yin et al. [ 66 ] and Yormirzoev et al. [ 67 ], the opposite reaction can be seen by consumers from developing countries. Chinese consumers trust organic food from developed countries [ 35 , 66 ], Russian consumers trust European organic food [ 32 , 67 ]. These findings can be explained with the research of Pedersen et al. [ 68 ]. Based on their results, the image and trust in the exporting country affect the trust in the organic food they export.

Other factors

Brand, price, communication, and product category were also identified as influencing factors of credibility, although only a few articles discuss these factors.

Brand is a trust-building factor in the case of organic food. Yin et al. [ 45 ] found that well-known brands are trusted more compared to lesser-known brands. According to Steffen & Doppler [ 60 ], the branding of organic food creates more trust than certification. CSR activities of organic food companies can positively influence consumer trust of organic food [ 69 ]. The lack of known brands can cause trust issues in certain markets [ 33 ].

The effect of price on organic food authenticity is supported by the bibliometric analysis. Research has proved that the high price of organic food is a barrier to consumption [ 70 ]. On the other hand, Lee et al. [ 47 ] point out that premium price affects trust in organic food, and Yin et al. [ 45 ] proved that in the case of organic milk, low price reduced consumer trust in the product. This is true the other way around: consumers are not willing to pay more for organic food if they do not trust it [ 26 ].

Product-level and retail-level communication help to build trust toward organic food [ 71 , 72 ], although Perić et al. [ 73 ] disagree with it. According to them, 63% of Serbian and 50% of Croatian consumers do not believe advertisements on organic food, which derives from the general mistrust in the media and advertising. Müller & Gaus [ 74 ] investigated the effect of media on organic food trust. Based on their research, negative media harms the credibility of organic food products.

The credibility of certain organic product categories is questionable for consumers. According to Lockie et al. [ 75 ], processed organic food makes consumers suspicious whether it is in fact organic. Consumers’ trust can varies on fresh produce category. Based on Watanabe et al. [ 76 ], consumers trust organic vegetables better than organic fruit.

Packaging seems to influence consumers’ trust in organic food, although there is very limited research on this topic. Danner & Menapace [ 20 ] identified packaging as an influencing factor, although its impact on credibility was questioned only by the consumers of the German-speaking countries, whereas USA consumers did not find it a credibility issue. German, Austrian and Swiss consumers believe that in the case of organic fruit and vegetable, plastic packaging makes them appear ‘less organic’ [ 20 ]. In their review, Hemmerling et al. [ 70 ] confirm the theory that packaging seems to be not environmentally friendly in the eye of consumers, as it is against the idea of organic food, although packaging can also be useful because it can indicate the organic status of the product. Nuttavuthisit & Thøgersen [ 29 ] mention that consumers rely on the appearance of the packaging when they assess the credibility of organic food.

Conclusions and future perspectives

The goal of our research was to identify the factors which influence the perceived credibility of organic food products. In the review, we could find 9 different product-related factors, not equally well-researched, and there are blind spots where further research is needed.

The interest in organic food is growing, however we can see a shift from developed to developing countries in terms of geographical focus of the articles. This shift and geographical difference in consumer attitudes could be detected by almost all identified factors of organic food credibility.

Certification is one of the most important factor to build consumer trust, as certification covers all those activities where compliance with organic requirements are assessed, so that should be a guarantee for consumers. Existing research shows a clear pattern regarding the credibility of certification bodies in different countries. Certifications from developed countries are much more trusted compared to certifications from developing countries.

Labeling has the role to inform consumers about the product. Without this information, consumers can not be sure if a product is organic. Besides certification, labeling is crucial to inform consumers about the organic characteristics of a product, which transfers the credence attribute to a search attribute. The importance of labeling can be explained with the fact, that labels contain most of the information about the product, so consumers can assess the product from other perspectives (eg. nutritional values, origin, ingredients, etc), which might influence perceived trust.

Labeling is well researched factor, however there are some kind of loose products, where the lack of labeling is common practice, like fruit and vegetables or bakery products. In those cases, credibility might be questioned by consumers, so research on these products is desirable.

The results of the credibility aspects of the country of origin seem to correlate with the results on certification, and the findings are strongly related to the results of the bibliometric analysis. Organic products from developing countries can cause doubt in consumers both from developed and developing countries, which might indicate the general low institutional trust in these countries.

Research on the effect of place of purchase proves its importance, although it is incomplete in several areas. According to Ökobarometer [ 77 ], German consumers mostly buy organic food in supermarkets and discounters, although traditional markets, specialty shops, and direct purchase also play an important role in organic food retail. However, these sales channels were not taken into account in the existing research, thus further research is needed.

In the case of certification, labeling, and country of origin, the findings of existing research seem to provide enough evidence to draw a reliable conclusion. All of these factors play an important role in the perception of trust towards organic food.

Brand was less-researched in relation to credibility, but all evidence shows that it has a positive impact on the authenticity of organic food. Similarly, not much research has investigated the effect of price, communication, product category, and packaging of organic food on credibility, therefore further research is needed in connection to these factors. There are certain product attributes, which were not evaluated by previous papers, but the authors assumed that they might have a strong effect on organic food trust. As food packaging is getting in the scope of sustainability, it would be interesting to compare the influence of different type of packaging on the level of trust. Also, color of the package can influence consumers’ perceptions of organic food.

The main aim of this review was to cover all the credibility factors of organic food; however, there are many limitations of this work. Identification of the credibility factors was based on the selected papers, therefore there might be other factors influencing credibility in the case of organic food and other articles, which cover the topic of this review. The reviewed articles are covering a wide range of research methods and geographical locations, so the samples are not homogenous.

Supporting information

S1 file. prisma checklist..

https://doi.org/10.1371/journal.pone.0266855.s001

S2 File. List of reviewed articles.

https://doi.org/10.1371/journal.pone.0266855.s002

S3 File. Dataset for bibliometric analysis.

https://doi.org/10.1371/journal.pone.0266855.s003

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• 2. Willer H & Kilcher L. editors. The World Of Organic Agriculture. Statistics & emerging trends 2010. Research Institute of Organic Agriculture (FiBL) & IFOAM—Organic International; 2010.
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Organic foods: Are they safer? More nutritious?

Discover the difference between organic foods and their traditionally grown counterparts when it comes to nutrition, safety and price.

Once found only in health food stores, organic food is now a common feature at most grocery stores. And that's made a bit of a problem in the produce aisle.

For example, you can pick an apple grown with usual (conventional) methods. Or you can pick one that's organic. Both apples are firm, shiny and red. They both provide vitamins and fiber. And neither apple has fat, salt or cholesterol. Which should you choose? Get the facts before you shop.

What is organic farming?

The word "organic" means the way farmers grow and process farming (agricultural) products. These products include fruits, vegetables, grains, dairy products such as milk and cheese, and meat. Organic farming practices are designed to meet the following goals:

• Improve soil and water quality
• Cut pollution
• Provide safe, healthy places for farm animals (livestock) to live
• Enable natural farm animals' behavior
• Promote a self-sustaining cycle of resources on a farm

Materials or methods not allowed in organic farming include:

• Artificial (synthetic) fertilizers to add nutrients to the soil
• Sewage sludge as fertilizer
• Most synthetic pesticides for pest control
• Using radiation (irradiation) to preserve food or to get rid of disease or pests
• Using genetic technology to change the genetic makeup (genetic engineering) of crops, which can improve disease or pest resistance, or to improve crop harvests
• Antibiotics or growth hormones for farm animals (livestock)

Organic crop farming materials or practices may include:

• Plant waste left on fields (green manure), farm animals' manure or compost to improve soil quality
• Plant rotation to keep soil quality and to stop cycles of pests or disease
• Cover crops that prevent wearing away of soil (erosion) when sections of land aren't in use and to plow into soil for improving soil quality
• Mulch to control weeds
• Insects or insect traps to control pests
• Certain natural pesticides and a few synthetic pesticides approved for organic farming, used rarely and only as a last choice and coordinated with a USDA organic certifying agent

Organic farming practices for farm animals (livestock) include:

• Healthy living conditions and access to the outdoors
• Pasture feeding for at least 30% of farm animals' nutritional needs during grazing season
• Organic food for animals
• Shots to protect against disease (vaccinations)

Organic or not? Check the label

The U.S. Department of Agriculture (USDA) has set up an organic certification program that requires all organic food to meet strict government standards. These standards control how such food is grown, handled and processed.

Any product labeled as organic on the product description or packaging must be USDA certified. If it's certified, the producer may also use an official USDA Organic seal.

The USDA says producers who sell less than $5,000 a year in organic food don't need to be certified. These producers must follow the guidelines for organic food production. But they don't need to go through the certification process. They can label their products as organic. But they can't use the official USDA Organic seal.

Products certified 95 percent or more organic may display this USDA seal.

The USDA guidelines describe organic foods on product labels as:

• 100% organic. This label is used on certified organic fruits, vegetables, eggs, meat or other foods that have one ingredient. It may also be used on food items with many ingredients if all the items are certified organic, except for salt and water. These may have a USDA seal.
• Organic. If a food with many ingredients is labeled organic, at least 95% of the ingredients are certified organic, except for salt and water. The items that aren't organic must be from a USDA list of approved additional ingredients. These also may have a USDA seal.
• Made with organic. If a product with many ingredients has at least 70% certified organic ingredients, it may have a "made with organic" ingredients label. For example, a breakfast cereal might be labeled "made with organic oats." The ingredient list must show what items are organic. These products can't carry a USDA seal.
• Organic ingredients. If a product has some organic ingredients but less than 70% of the ingredients are certified organic , the product can't be labeled as organic. It also can't carry a USDA seal. The ingredient list can show which ingredients are organic.

Does 'organic' mean the same thing as 'natural'?

No, "natural" and "organic" are different. Usually, "natural" on a food label means that the product has no artificial colors, flavors or preservatives. "Natural" on a label doesn't have to do with the methods or materials used to grow the food ingredients.

Also be careful not to mix up other common food labels with organic labels. For example, certified organic beef guidelines include pasture access during at least 120 days of grazing season and no growth hormones. But the labels "free-range" or "hormone-free" don't mean a farmer followed all guidelines for organic certification.

Organic food: Is it safer or more nutritious?

Some data shows possible health benefits of organic foods when compared with foods grown using the usual (conventional) process. These studies have shown differences in the food. But there is limited information to prove how these differences can give potential overall health benefits.

Potential benefits include the following:

• Nutrients. Studies have shown small to moderate increases in some nutrients in organic produce. Organic produce may have more of certain antioxidants and types of flavonoids, which have antioxidant properties.
• Omega-3 fatty acids. The feeding requirements for organic farm animals (livestock) usually cause higher levels of omega-3 fatty acids. These include feeding cattle grass and alfalfa. Omega-3 fatty acids — a kind of fat — are more heart healthy than other fats. These higher omega-3 fatty acids are found in organic meats, dairy and eggs.
• Toxic metal. Cadmium is a toxic chemical naturally found in soils and absorbed by plants. Studies have shown much lower cadmium levels in organic grains, but not fruits and vegetables, when compared with crops grown using usual (conventional) methods. The lower cadmium levels in organic grains may be related to the ban on synthetic fertilizers in organic farming.
• Pesticide residue. Compared with produce grown using usual (conventional) methods, organically grown produce has lower levels of pesticide residue. The safety rules for the highest levels of residue allowed on conventional produce have changed. In many cases, the levels have been lowered. Organic produce may have residue because of pesticides approved for organic farming or because of airborne pesticides from conventional farms.
• Bacteria. Meats produced using usual (conventional) methods may have higher amounts of dangerous types of bacteria that may not be able to be treated with antibiotics. The overall risk of contamination of organic foods with bacteria is the same as conventional foods.

Are there downsides to buying organic?

One common concern with organic food is cost. Organic foods often cost more than similar foods grown using usual (conventional) methods. Higher prices are due, in part, to more costly ways of farming.

Food safety tips

Whether you go totally organic or choose to mix conventional and organic foods, keep these tips in mind:

• Choose a variety of foods from a mix of sources. You'll get a better variety of nutrients and lower your chance of exposure to a single pesticide.
• Buy fruits and vegetables in season when you can. To get the freshest produce, ask your grocer what is in season. Or buy food from your local farmers market.
• Read food labels carefully. Just because a product says it's organic or has organic ingredients doesn't mean it's a healthier choice. Some organic products may still be high in sugar, salt, fat or calories.
• Wash and scrub fresh fruits and vegetables well under running water. Washing helps remove dirt, germs and chemical traces from fruit and vegetable surfaces. But you can't remove all pesticide traces by washing. Throwing away the outer leaves of leafy vegetables can lessen contaminants. Peeling fruits and vegetables can remove contaminants but may also cut nutrients.

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• Organic production and handling standards. U.S. Department of Agriculture. https://www.ams.usda.gov/publications/content/organic-production-handling-standards. Accessed March 30, 2022.
• Introduction to organic practices. U.S. Department of Agriculture. https://www.ams.usda.gov/publications/content/introduction-organic-practices. Accessed March 30, 2022.
• Organic labeling at farmers markets. U.S. Department of Agriculture. https://www.ams.usda.gov/publications/content/organic-labeling-farmers-markets. Accessed March 30, 2022.
• Labeling organic products. U.S. Department of Agriculture. https://www.ams.usda.gov/publications/content/labeling-organic-products. Accessed March 30, 2022.
• Use of the term natural on food labeling. U.S. Food and Drug Administration. https://www.fda.gov/food/food-labeling-nutrition/use-term-natural-food-labeling. Accessed March 30, 2022.
• Demory-Luce D, et al. Organic foods and children. https://www.uptodate.com/contents/search. Accessed March 30, 2022.
• Pesticides and food: Healthy, sensible food practices. U.S. Environmental Protection Agency. https://www.epa.gov/safepestcontrol/pesticides-and-food-healthy-sensible-food-practices. Accessed March 30, 2022.
• Vegetable and pulses outlook: November 2021. U.S. Department of Agriculture. https://www.ers.usda.gov/publications/pub-details/?pubid=102664. Accessed March 30, 2022.
• Changes to the nutrition facts label. U.S. Food and Drug Administration. https://www.fda.gov/food/food-labeling-nutrition/changes-nutrition-facts-label. Accessed March 30, 2022.
• Rahman SME, et al. Consumer preference, quality and safety of organic and conventional fresh fruits, vegetables, and cereals. Foods. 2021; doi:10.3390/foods10010105.
• Brantsaeter AL, et al. Organic food in the diet: Exposure and health implications. Annual Review of Public Health. 2017; doi:10.1146/annurev-publhealth-031816-044437.
• Vigar V, et al. A systematic review of organic versus conventional food consumption: Is there a measurable benefit on human health? Nutrients. 2019; doi:10.3390/nu12010007.
• Mie A, et al. Human health implications of organic food and organic agriculture: A comprehensive review. Environmental Health. 2017; doi:10.1186/s12940-017-0315-4.
• Innes GK, et al. Contamination of retail meat samples with multidrug-resistant organisms in relation to organic and conventional production and processing: A cross-sectional analysis of data from the United States National Antimicrobial Resistance Monitoring System, 2012-2017. Environmental Health Perspectives. 2021; doi:10.1289/EHP7327.

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Organic Foods

Are organic foods healthier and safer? Learn more in our easy-to-understand videos on the latest research.

You may be surprised to learn that a review of hundreds of studies found that organic foods don’t seem to have significantly more vitamins and minerals. They do, however, appear to have more nontraditional nutrients, like polyphenol antioxidants , perhaps because conventionally grown plants given high-dose synthetic nitrogen fertilizers may divert more resources to growth rather than defense. This may be why organic berries, for example, appear to suppress cancer growth better than conventional berries in vitro.

Based on its elevated antioxidant levels, organic produce may be considered 20 to 40 percent healthier, the equivalent of adding one or two servings’ worth to a five-a-day regimen. But people don’t just buy organic foods because they’re healthier—what about safety?

Conventional produce appears to have twice the levels of cadmium, one of three toxic heavy metals in the food supply, along with mercury and lead. What about pesticide residues? Buying organic foods may reduce your exposure to pesticides, but not eliminate them entirely. Pesticide residues have reportedly been detected in 11 percent of organic crop samples due to accidental or fraudulent use, cross-contamination from neighboring nonorganic fields, or the lingering presence of persistent pollutants like DDT in the soil.

What about organic meat , eggs , and dairy ? The USDA organic standards don’t allow these animals to be fed or injected with antibiotics or steroids. All foods of animal origin—organic or not—naturally contain sex steroid hormones, though, such as estrogen, but the hormones naturally found even in organic cow’s milk may play a role in acne , diminished male reproductive potential , and premature puberty . And, in a comparison between meat from animals raised conventionally versus organically, all conventional chicken samples were contaminated with multidrug-resistant bacteria, but the majority of organic samples were, too.

For substantiation of any statements of fact from the peer-reviewed medical literature, please see the associated videos below.

Image Credit: Jessica Spengler / Flickr. This image has been modified.

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All videos for organic foods.

The Best Dietary Detox

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Does choosing organic over conventional foods protect against cancer? The effects of pesticides on cancer risk.

Ochratoxin in Breakfast Cereals

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Is Organic Meat Less Carcinogenic?

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What are the eight preparation methods to reduce exposure to carcinogens in cooked meat?

The Role of Pesticides and Pollution in Autism

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Arsenic in Rice Milk, Rice Krispies, & Brown Rice Syrup

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Which Brands & Sources of Rice Have the Least Arsenic?

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What is the optimal timing and dose of nitrate-containing vegetables, such as beets and spinach, for improving athletic performance?

Diet and Climate Change: Cooking Up a Storm

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If we increased our consumption of conventionally-produced fruits and vegetables, how much cancer would be prevented versus how much cancer might be caused by the additional pesticide exposure?

Test tube studies show advantages of organic produce, such as better cancer cell growth suppression, but what about in people, not Petri dishes?

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Organic food consumption appears to reduce exposure to pesticide residues and antibiotic-resistant bacteria.

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Regenerative Agriculture Can Solve Big Issues In Food Production. But Who Will Pay For It?

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Agronomist examining organic corn crops in summer.

According to “ The Hidden Cost of UK Food ,” a report by the Sustainable Food Trust (SFT), the costs of damage caused by our food production systems aren’t paid for by the businesses that cause them, nor through the retail price of food. Instead, they’re passed on to the public through taxation, lost income due to ill health, and the price of mitigating and adapting to climate change and environmental degradation.

Tackling measurements

“Clearly, we need a change in policy where agricultural subsidies are used to encourage a shift to more sustainable forms of production,” said Patrick Holden, founder and CEO of the SFT. He was speaking at the recent Regenerative Agriculture Summit Europe along with other experts who were discussing how to finance such a shift. “There is a need for a third income stream for farmers to make changes to their practices. If farmers were paid for their positive externalities, that would shift the balance of financial advantage toward regenerative farming.”

Holden also addressed another big challenge, namely, the lack of harmonized measurement and auditing frameworks to better understand the impact of regenerative farming practices on climate, nature, and social outcomes.

“There is a great need for collaboration among banks, asset managers, and other stakeholders to harmonize what is measured and how it is done,” he said, citing the chaotic conditions at his own farm as it undergoes five different audits per year using five different frameworks.

One of Holden’s suggestions is to create an auditing system driven by the European Commission and the UK government. The idea is to send licensed auditors to farms on behalf of banks and asset managers to assess their impact on climate, nature, and social outcomes. Their role would be to collect baseline data.

Taking on new roles

Holden’s fellow panelists agreed that a uniform flow of data is needed from the farm up to the asset manager, the bank, and the insurance company. Without the right data, it is impossible for banks to manage risk, provide debt, and align stakeholders.

Nicoline van Gerrevink, Executive Director of Food System Transition at Rabobank, explained that banks are essentially backward-looking institutions, meaning they perform their risk analyses on historical data. The data must be built up for a number of years before it can be used in bank models.

According to a study of the Dutch central bank, Rabobank’s portfolio has around twice as much dependency on Nature than other Dutch financial institutions because of its food and agricultural portfolio.

“We need a system to classify farmers so that you can track the difference in credit risk. It's not just about their financial results, but how they run their farms,” van Gerrevink explained. “We need to assess their resilience and ability to future proof by mitigating climate and transition risks. At the moment, the credit and sustainability ratings for our farmer clients are separate scores. But going forward these scores will become integrated. At Rabobank, we already provide incentives to farmers that are classified as sustainable frontrunners.”

Banks are helping to finance the transition by providing debt which must be repaid. The panelists agreed that the traditional role of banks is changing significantly, because most customers simply can't afford any more debt. A new model is needed as banks can no longer lend their way through such a transformation.

Indeed, the lack of capital available for the food transition as described in the recent World Bank report , is concerning. While there is approximately US$80 billion in climate finance available globally, only 2.4% is directed toward the agriculture and forestry sectors. This limited allocation is particularly worrisome, given that these sectors play a crucial role in addressing both climate mitigation and adaptation, especially in developing countries where livelihoods depend heavily on these areas.

Banks can begin by advising customers how to make their business more resilient in the long term. Banks must demonstrate leadership and act as conveners to bring people together to address the issue collaboratively. One suggestion is to learn from the energy transition and other sectors undergoing transformational shifts.

Finding new strategies

On the other end of the equation are the investors. SLM Partners , for example, supports the production of grains, forages, and specialty crops by replacing synthetic inputs with organic ones. The company fosters practices with recognized beneficial impacts on soil, climate and biodiversity such as crop nutrition and multiyear crop rotations. Its core strategy is to acquire conventional farmland and partner with local farmers to implement regenerative and organic farming models.

João Roseiro, Europe agronomy director at SLM, cited two investment examples that are working well. The first is a buy-and-lease model used in the United States, where land is bought and then leased to farmers at lower rates to support the transition to organic productions systems. The second is an aligned interest financing system used in Portugal and Spain, where SLM finances sustainable operations on local properties purchased by the company, and operated by local operators.

“While supporting small farmers is crucial, the only way to achieve global impact is through large-scale investment,” he concluded.

While the cost of producing food sustainably is certainly a factor, if farmers, banks, investors, and consumers all align to support regenerative practices, the return on the investment will benefit people and the planet.

When it comes to data analytics, the good news is that many players in the food supply chain are already digitalizing farming processes and services. "The SAP Intelligent Agriculture solution helps agribusiness companies increase efficiency, improve data quality, and connect existing data sets to gain insights and support auditing tasks," said Anja Strothkaemper, vice president of agribusiness and commodity management at SAP. Strothkaemper was speaking at the same event on the benefits of harnessing data for regenerative agriculture.

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• Open access
• Published: 14 October 2024

Effects of winter soil warming on crop biomass carbon loss from organic matter degradation

• Haowei Ni 1 , 2   na1 ,
• Han Hu 1 , 2   na1 ,
• Constantin M. Zohner   ORCID: orcid.org/0000-0002-8302-4854 3   na1 ,
• Weigen Huang 1 , 2   na1 ,
• Ji Chen 4 , 5 , 6 ,
• Yishen Sun 1 , 2 ,
• Jixian Ding 1 ,
• Jizhong Zhou   ORCID: orcid.org/0000-0003-2014-0564 7 ,
• Xiaoyuan Yan   ORCID: orcid.org/0000-0001-8645-4836 1 ,
• Jiabao Zhang   ORCID: orcid.org/0000-0001-6922-0480 1 ,
• Yuting Liang   ORCID: orcid.org/0000-0001-5443-4486 1 &
• Thomas W. Crowther   ORCID: orcid.org/0000-0001-5674-8913 3  

Nature Communications volume  15 , Article number:  8847 ( 2024 ) Cite this article

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Global warming poses an unprecedented threat to agroecosystems. Although temperature increases are more pronounced during winter than in other seasons, the impact of winter warming on crop biomass carbon has not been elucidated. Here we integrate global observational data with a decade-long field experiment to uncover a significant negative correlation between winter soil temperature and crop biomass carbon. For every degree Celsius increase in winter soil temperature, straw and grain biomass carbon decreased by 6.6 ( ± 1.7) g kg -1 and 10.2 ( ± 2.3) g kg -1 , respectively. This decline is primarily attributed to the loss of soil organic matter and micronutrients induced by warming. Ignoring the adverse effects of winter warming on crop biomass carbon could result in an overestimation of total food production by 4% to 19% under future warming scenarios. Our research highlights the critical need to incorporate winter warming into agricultural productivity models for more effective climate adaptation strategies.

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Introduction.

Over the past decade, rapid global warming has posed a significant threat to global food security 1 , 2 . According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change 3 , ongoing global warming has led to a reduction in crop yields and negatively impacted crop biomass 4 . As an integral part of ensuring food security, crop biomass directly provides essential food calories for humans 5 and indirectly contributes to protein sources through animal feed 6 . With a projected world population of 10 billion by 2050, global food demand is expected to increase by ~ 56% compared to 2010 levels 7 , 8 . In this context, the decline in crop biomass caused by global warming will make meeting future growth in food demand an increasingly challenging task 9 , 10 . Therefore, in view of the irreversible nature of climate change, it is imperative to grasp the specific ways in which climate change affects crop biomass to protect global food security.

The majority of current research has focused on the impacts of changes in mean annual temperatures on crop yields 4 , 11 , 12 . However, climate warming is more pronounced during winter 3 , 13 , 14 . Studies have revealed that winter temperatures in northern mid- and high-latitude areas are increasing at a rate exceeding 0.5 °C per decade 15 . This increase is nearly 1.8 times faster than the rise in mean annual temperatures, particularly in high-latitude regions 15 , 16 . Winter warming is expected to heighten the risk of reduced winter crop yields by breaking dormancy 17 , 18 , advancing phenology 19 , shortening the growing season 20 and photosynthetic activity 21 , and exacerbating the incidence of pests and pathogens 22 . Despite limited research on how winter warming affects non-winter crops, it is important to note that winter warming can change soil temperature and moisture 16 , which can affect soil fertility 23 and influence the growth of these crops.

Soil fertility is a fundamental factor that supports plant growth, playing a crucial role in determining the primary patterns of global crop yields in conjunction with climate 24 , 25 . As a cornerstone of soil fertility, soil organic matter (SOM) can affect crop biomass by sustaining soil moisture and nutrient availability 26 , thereby promoting root development. Previous studies have indicated that winter warming can stimulate soil respiration by increasing soil temperatures and altering soil moisture dynamics, which can accelerate SOM decomposition 27 , 28 , 29 . The effects of winter warming on soil temperatures and moisture can vary by latitude, potentially influencing soil respiration differently across regions. In high-latitude regions, while crops are not cultivated during winter, intensified winter warming may influence crop growth in the subsequent year through soil-mediated processes 30 , 31 . Therefore, further investigation is necessary to elucidate the mechanism by which winter warming affects crop biomass, particularly considering the involvement of soil processes.

Here, we compiled a global database comprising 309 observations of straw carbon (C) and 1358 observations of grain C contents from 161 field sites worldwide. This database helps us to investigate the potential impact of winter warming on crop biomass through soil processes (Supplementary Fig.  1 ). To further explore this relationship and its underlying mechanism, we conducted a decade-long field experiment across three distinct climatic zones in China: the cold temperate zone (47°26′ N), the warm temperate zone (35°00′ N), and the mid-subtropical zone (28°15′ N). The experiment included two components: an in situ study (Supplementary Fig.  2 ) and a soil translocation study. We hypothesised that under consistent climatic conditions and crop types, the reduction in SOM induced by warmer winters would diminish the soil’s nutrient retention capacity, subsequently leading to a decrease in crop biomass C content. We anticipated this effect would be particularly pronounced at mid-to-high latitudes. To test this hypothesis, the decade-long in situ study was designed to investigate the impacts of winter warming on crop biomass C across different climatic zones, while the soil translocation study simulated accelerated SOM decomposition by relocating soils from high-latitude regions to mid- and low-latitude areas. The whole experimental design allowed us to comprehensively assess the potential impacts of winter warming on crop biomass C while maintaining consistency in climate conditions, crop types and agricultural management practices. Our findings underscore the significant adverse impact of winter warming on crop biomass, which should not be overlooked.

To evaluate the impacts of winter warming on crop biomass C, we employed both a global-scale meta-analysis and our own decade-long field experiments. At the global scale, we utilised a linear mixed-effects model with crop biomass C as the dependent variable, winter soil temperature as a fixed effect, and climate type as a random effect on the slopes and intercepts (Supplementary Table  1 ). Our analysis revealed that all three crops demonstrated negative responses to winter warming, with maize and rice showing more significant negative impacts compared to wheat (Fig.  1a, b ). This variation can be attributed to the coincidence of wheat’s growth period with winter, which may help alleviate some of the adverse effects of winter warming. When both crop type and climate type were considered as random effects, for every 1 °C increase in winter soil temperature, the global average C content in straw and grain decreased by 6.62 ± 1.65 g kg −1 and 10.21 ± 2.31 g kg − 1 , respectively ( P  < 0.05; Fig.  1c, d and Supplementary Table  2 ). The negative correlation still held across fertilisation treatments (Supplementary Table  3 ). Consistent with the results of the global meta-analysis (Fig.  1 ), our field experiments also showed a significant negative correlation between winter soil temperature and crop biomass C (Supplementary Fig.  3 ). Notably, whether, in the global analysis or the field experiments, the decline rate in straw and grain C was more pronounced at mid-to-high latitudes than at low latitudes ( P  < 0.05; Supplementary Figs.  3 , 4 and Supplementary Tables  4 , 5 ). These results highlight the detrimental impacts of winter warming on global crop biomass C, particularly at mid-to-high latitudes.

a Global straw C content for maize, wheat and rice. b Global grain C content for maize, wheat, and rice. c Global straw C content for three crops combined. d Global grain C content for three crops combined. Crop biomass C comprises straw and grain C content. Boxplots show the distribution of straw and grain C content in the compiled global dataset, with observation counts noted at the base of each box and mean values indicated by dots. The solid line in the box plot indicates the median (50th percentile), the ends of the box indicate the upper quartile (75th percentile, Q3) and lower quartile (25th percentile, Q1), and the whiskers indicate the minimum and maximum values based on the quartiles. Scatterplots depict the relationship between changes in crop biomass C (ΔStraw C and ΔGrain C) and variations in winter soil temperature (ΔWinter soil temperature), derived from differences between two separate years with identical climate classification and crop types (see Methods for detailed calculation process). Scatter points are adjusted using fixed and random effects from a linear mixed-effects model. The fitted lines represent predictions from the linear mixed-effects model, with confidence intervals via bootstrap resampling ( n  = 999). The slope represents the coefficient estimate for the fixed effects in the model, and SE denotes the standard error. For ( a ), P- values for maize, wheat, and rice are 0.0008, 8.33e-11, and 0.0009, respectively. For ( b ), P- values for maize, wheat, and rice are 4.65e-06, 1.20e-05, and 2.2e-16, respectively. For ( c ) and ( d ), the P- values for the combined crops are 1.82e-05 and 9.58e-06, respectively. Winter soil temperature is characterised as the mean annual soil temperature during winter.

The random forest models indicated that SOM is the secondary influential factor on crop biomass C, following temperature changes, in both the global analysis and field experiments (Supplementary Figs.  5 – 7 ). To further elucidate the role of SOM, we conducted a soil translocation experiment by relocating Mollisols from high-latitude regions to mid- and low-latitude areas (Fig.  2a ). This work spanned from 2005 to 2015 and ensured consistency between the translocated soils and the local soils regarding climatic conditions, sowing times, photoperiod, crop types and varieties, as well as fertilisation management and other agricultural practices. We aimed to test the hypothesis that winter warming accelerates the decomposition of SOM, thereby exacerbating the loss of crop biomass C.

a Schematic of the ten-year in situ and soil translocation field experiments conducted in Hailun (47°26′ N), Fengqiu (35°00′ N) and Yingtan (28°15′ N). Mollisols from the high-latitude Hailun region were translocated to the experimental plots in Fengqiu (Trans1) and Yingtan (Trans2), respectively. Mollisols are highlighted in black, and in situ soils (Inceptisoils in Fengqiu and Ultisols in Yingtan) are shown in orange and red, respectively. b , c Scatterplots show linear regression models depicting the correlations between straw or grain C content and winter soil temperature (each site n  = 30). The fitted lines represent the linear regression models, and the shaded area denotes 95% confidence intervals around the mean values. For ( b ), P- values for Hailun (in situ), Fengqiu (Trans1 and in situ), and Yingtan (Trans2 and in situ) are 7.5e-13, 0.0232, 0.0174, 0.00438 and 0.0412, respectively. For ( c ), the corresponding P- values are 2.1e-12, 0.00782, 0.0106, 0.00107 and 0.0197, respectively. Asterisk (*) denote that statistically significant differences between regression slopes ( P  < 0.05). Slope comparisons between the in situ and translocation models are performed by generating 999 bootstraps resamples for each model to obtain distributions of slope coefficients, followed by a two-sided t test. Winter soil temperature is characterised as the mean annual soil temperature during winter.

Our results revealed that the decline rates in SOM for the translocated soil from Hailun to Fengqiu and from Hailun to Yingtan were 0.97 and 1.13 g kg −1 per °C, respectively ( P  < 0.05, Supplementary Fig.  8 ). These rates were significantly higher than those observed in the local soils of Fengqiu and Yingtan, which were 0.47 and 0.26 g kg − 1 per °C, respectively. Furthermore, the decline rates of straw C and grain C in the translocated Mollisols were notably higher than those in the local soils ( P  < 0.05, Fig.  2b, c ). These findings suggest that the rapid decline in SOM may contribute to the negative impacts of winter warming on crop biomass C, implying that winter warming may influence crop biomass C indirectly through soil processes.

To elucidate the mechanisms underlying how winter warming affects crop biomass C via soil processes, we utilised structural equation modelling (SEM) to evaluate the effects of soil physicochemical properties, mineral protection, micronutrient availability, enzymatic activity, and microbial diversity on changes in crop biomass C (Fig.  3 ). Our SEM analysis indicated that the interaction among winter soil temperature, soil geochemistry, and microbial characteristics could account for 80% of the variability in crop biomass C at high latitude, 42% at mid-latitude, and 44% at low latitude.

a Hailun (in situ). b , c Soils translocated to Fengqiu and Yingtan, respectively. Solid arrows represent hypothesized causal relationships, with positive and negative impacts shown by orange and blue arrows, respectively. Dashed arrows signify nonsignificant associations. The thickness of the arrows corresponds to the magnitude of the effect. All variables are normalised. Soil attributes include SOM, soil moisture, pH, and micronutrients (available Fe:Zn ratio). Mineral components include organo-complexed Fe/Al and amorphous Fe/Al oxides (Fe p , Al p , Fe o , and Al o ). Diversity is measured by the Shannon index for prokaryotes and eukaryotes (H′). Hydrolase activity includes α-1,4-glucosidase and β-1,4-glucosidase, denoted as S-α-GC and S-β-GC, respectively. Crop biomass C consists of straw and grain C contents. Standardised path coefficients are labelled adjacent to the arrows. Only significant coefficients are displayed (* P  < 0.05, ** P  < 0.01, and *** P  < 0.001).

An increase in winter soil temperature resulted in a significant decrease in soil mineral activity (path coefficient = − 0.82 to − 0.52, P  < 0.001; Fig.  3 ), thereby reducing the mineral protection of SOM. The decline in SOM further led to a decrease in micronutrients (path coefficient = 0.61–0.93, P  < 0.001), significantly impacting crop biomass C content negatively. In addition, the influence of soil moisture content varied markedly across different latitudes, which could be associated with the occurrence of freeze-thaw cycles in the region. In high latitudes, the increase in soil moisture content during winter adversely affected microbial diversity (Fig.  3a ); whereas in mid to low latitudes, the absence of freeze-thaw activity allowed moisture content to enhance microbial extracellular enzymatic activities or diversity (Fig.  3b ). These findings suggest that winter warming leads to depletion of SOM and micronutrients, which ultimately resulting in a reduction in crop biomass C.

Drawing from a synthesis of global datasets and unique, decade-long soil latitudinal translocation experiments, our study elucidated the impact of winter warming on crop biomass C and the underlying soil processes (Fig.  4 ). The pronounced increase in winter soil temperatures attenuates the protective effect of minerals on SOM, while concurrently enhancing microbial proliferation and the extracellular enzyme activity 32 . This elevated winter warmth accelerates the degradation of SOM, potentially leading to the premature release of essential nutrients crucial for plant growth from the SOM reserves 33 . A significant decrease in SOM markedly curtails the availability of micronutrients (Supplementary Fig.  9 ) such as Fe, Zn, Mn, and Cu—cofactors integral for enzymatic reactions essential to plant carbohydrate synthesis 34 and overall growth 35 . Consequently, the depletion of these micronutrients could induce enduring adverse effects on crop carbohydrate synthesis, potentially manifesting in subsequent years or beyond, ultimately resulting in further reductions in crop biomass C.

The red arrow signifies an intensified process, while the blue arrow denotes a weakened process. The Orange upwards arrow within a variable represents an increase, and the green downwards arrow indicates a decrease. Crop biomass C encompasses both straw C and grain C contents.

The adverse effects of winter warming on crop biomass C were more pronounced at high latitudes compared to middle and low latitudes. This discrepancy can primarily be attributed to the higher frequency of freeze-thaw cycles at high latitudes, which leads to a more significant depletion of SOM and associated nutrients under warmer conditions 36 , 37 . Our findings revealed that SOM loss accelerated with rising winter soil temperature. Specifically, for each degree of Celsius increase in winter soil temperature, high-latitude regions experienced a SOM loss of 0.9 g kg −1 , which is approximately 1.5 times greater than that observed at middle latitudes and 1.7 times greater than that observed at low latitudes (Supplementary Fig.  8 ).

In addition to the influence of climate patterns on freeze-thaw cycles, other factors, such as soil type and crop variety, may modulate the impacts of winter warming, particularly at mid-to-high latitudes 8 . For instance, clay-rich soils in these regions may exhibit distinct thermal dynamics compared to sandy soils prevalent at lower latitudes 38 . Such variations in soil properties can significantly affect the rate of SOM decomposition and nutrient release, thereby altering the overall consequences of winter warming on agricultural productivity.

To ensure the impact of winter warming on crop biomass C is appropriately addressed in the context of pending global warming, it is crucial to recognise its potential effects. Incorporating the influence of winter warming into projections suggests that the anticipated reductions in crop productivity due to future global warming could be more significant than previously estimated, with decreases ranging from 4% to 19% (Fig.  5 ). These impacts are especially notable in mid-to-high latitude regions, where reductions could span from 8% to 19%, overlapping with several of the globe’s primary agricultural regions 39 . Ignoring these discrepancies could pose significant risks to current food security and potentially destabilise and exacerbate the global food supply chain in forthcoming years.

The projected loss in crop C is calculated as the difference between actual crop C and previously estimated crop C, with negative values indicating declines due to winter warming. Larger negative values correspond to greater losses. This comparison underscores the impact of underestimating the effects of winter warming on crop biomass C. The detailed calculation procedure is provided in the Methods. Changes in previously estimated total crop C and actual crop C are shown in Supplementary Fig.  12 .

Furthermore, it is imperative to recognise the distinction between the mean annual soil temperature and the mean annual air temperature 16 . Most current studies have relied on air temperature to forecast future food production, introducing potential uncertainties into these predictions. Our experimental data revealed that winter soil temperatures were ~ 1.4 °C higher than the corresponding air temperatures (Supplementary Fig.  10 ). Soil temperature acts as an “amplifier” for fluctuations in air temperature. Furthermore, root zone temperature is influenced by soil moisture, suggesting that soil water availability may impact the relationship between soil temperature and crop yield. Given the significant variations in soil temperature and moisture throughout the soil profile, integrating these factors by soil depth is essential for assessing the effects of climate warming on future food security.

Taken together, our study provides initial evidence of the influence of winter warming on crop biomass at regional and global scales. The results indicate a significant decrease in crop biomass due to winter warming, with high-latitude regions being particularly susceptible. This reduction is primarily driven by the degradation of SOM and the subsequent loss of micronutrients. Furthermore, our study indicates a notable decrease in SOM associated with winter warming, which may have implications for the global C cycle. This observed reduction in SOM implies that winter warming could affect the soil’s capacity as a C sink, possibly contributing to increased atmospheric CO 2 concentrations. Given these findings, adaptation strategies should be reevaluated to account for the impacts of winter warming on crop yields and C sequestration. Breeding programmes may need to focus on developing crops with enhanced photosynthetic efficiency to compensate for the reduced growing season and decreased soil nutrients. While our study focuses on inorganic fertilisers, it is essential to consider the role of organic fertilisers in future agricultural practices. Nutrient management practices such as organic fertilizer input can promote crop growth and biomass accumulation, potentially offering a sustainable approach to maintaining crop yields under changing environmental conditions. These adjustments are crucial for sustaining agricultural productivity, ensuring global food security, and supporting climate change adaptation and mitigation efforts.

Global data compilation

Using the Web of Science ( http://apps.webofknowledge.com ), Google Scholar ( https://scholar.Google.com ) and the China National Knowledge Infrastructure Database ( http://www.cnki.net ), we searched for all peer-reviewed articles on crop biomass C published before October 31, 2023, including straw and grain C content. The keywords used were “straw carbon”, “straw starch”, “grain carbon”, “grain starch”, “seed carbon” or “seed starch”. To avoid potential bias from cropping practices, the data were screened based on the following criteria. (1) Straw C, grain C and grain starch data were collected from in situ field studies. (2) Only control, fertiliser application or undisturbed treatments were selected. (3) The crops were maize, wheat or rice. (4) To prevent any short-term disturbance, crop data covering at least one full growth cycle were included. (5) In our global data collection, we specifically included studies that employed inorganic chemical or mineral fertilisers, excluding those that used organic fertilisers due to the potential for organic matter in these fertilisers to directly increase SOM and thereby interfere with the results. Finally, we compiled a dataset that included 309 straw C observations from 76 previous papers and 1358 grain C observations from 85 papers. Please refer to the Supplementary Data for additional details.

Only the starch content of the grain was included as grain C in our dataset. This is because few studies have investigated both starch and protein contents in grains. The protein content is significantly lower (~ 10%) than the starch content (~ 75% to 80%) 40 , 41 , 42 . We converted the grain starch content (%) to the grain C content (%) via the following equation:

where grain starch content represents the proportion of starch in the grain, and 72/162 is the relative weight of C in starch based on its molecular formula (C 6 H 10 O 5 ) n .

Data on crop type, climate type, latitude, longitude, experiment time, straw C content, grain starch content, SOM, fertilisation rates, different temperatures (mean annual temperature, mean annual soil temperature, mean growing-season temperature, mean growing-season soil temperature, mean winter temperature, mean winter soil temperature) and different soil moistures (mean annual soil moisture, mean growing-season soil moisture, mean winter soil moisture) were extracted from the selected articles. In addition, for some observations, these data are not reported in the text. We filled in the missing data using the following global database. Grain C content was calculated using Eq. ( 1 ). Soil organic carbon (SOC), pH, total nitrogen (N), total phosphorus (P), total potassium (K), cation exchange capacity, base saturation, sand, silt and clay data were obtained from the gridded Global Soil Dataset at a 0.083° spatial resolution ( http://globalchange.bnu.edu.cn/research/soilw ) 43 . SOM was converted by multiplying the SOC by a conversion factor of 1.724. Microbial biomass C and N were obtained from the ORNL DAAC for Biogeochemical Dynamics ( https://daac.ornl.gov/ ) 44 . The aridity indices were obtained from the CGIAR-CSI . The monthly air temperatures, soil temperatures and soil moisture were obtained from the Global Land Data Assimilation System (gov/datasets?keywords=GLDAS), the National Centres for Environmental Prediction ( https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS ) and the NASA Earth Observatory ( https://ldas.gsfc.nasa.gov/gldas/ ) at a 0.083° spatial resolution. The monthly temperature was used to calculate the site-level temperatures (including mean annual temperature, mean annual soil temperature, mean growing season temperature, mean growing season soil temperature, mean winter temperature, and mean winter soil temperature). The monthly moisture was used to calculate the site-level moisture (including mean annual soil moisture, mean growing-season soil moisture, and mean winter soil moisture). The software Engauge Digitiser (version 11.2) was used to extract the data from the graphs.

To determine the key variables affecting global crop biomass C, we employed a random forest model to evaluate the influence of 27 environmental variables. These variables encompassed various climate factors, soil geochemical properties, and microbial activity, all of which collectively shape the crop straw and grain C content (Supplementary Fig.  5 ). The random forest model revealed that while soil temperature remains a dominant factor influencing crop biomass C, soil moisture also plays a significant role (Supplementary Figs.  5 , 6 ). This result was consistent across different crop types, including maize, wheat, and rice (Supplementary Fig.  6 ). In addition, considering the effects of different latitudes on crop biomass C, we divided the global database into two subdatasets, namely, mid- to high-latitude (> 30°) and low-latitude (≤ 30°).

Relationship between temperature and crop biomass C

Based on the random forest results, we further explored the important contributions of different temperatures to crop biomass C via hierarchical partitioning (Supplementary Fig.  11 ). The results indicated that the global winter temperature accounted for the largest proportion of the variation in crop biomass C (16.5% to 32.9%). This trend is consistent across different crop types, which also showed that winter temperature exerts the most substantial influence on crop biomass C.

Furthermore, the mixed effects model was employed to investigate the effects of temperature fluctuations on crop biomass C 45 . The model allows for nested covariance structures, especially for each climate and each crop type relationship nested within the overall relationship. In addition, this approach addresses unbalanced designs when measuring temperature in the field. For example, as the study sites are dispersed globally, variations in temperature across different locations are influenced by both geographic factors (such as latitude and altitude) and climate change. To minimise the impact of various climatic regions on temperature fluctuations, we determined the climate type at the site level using the Köppen climate classification. In addition, there may be variations in the response of different crop types to temperature shifts. Therefore, we incorporated climate and crop type as random effects to eliminate the impact of variations in geographic location and crop type on temperature. This approach ensures that the contributions of each factor are accurately reflected, reducing the risk of overstating the influence of temperature. When analysing different crops, only climate type is considered as a random effect.

Before conducting the mixed effects model, we divided our dataset into subdatasets based on the target variables (straw C, grain C), the crop types (maize, rice, and wheat) and the climate types (a total of 10 climate types). Due to limitations in long-term observational data at the same location globally over time scales, we employed differences from different years within the same climate zone to reflect changes in winter soil temperature 46 . This approach allows us to control for site-specific factors that may influence crop biomass C and focus exclusively on the effects of temperature variations. Therefore, in Fig.  1 , due to limited long-term observational data at the same location globally over time scales, we used differences from different years within the same climate zone to reflect changes in winter soil temperature. We ensured consistency between treatments (including control, fertiliser application, and undisturbed) when calculating the differences, thereby preventing treatment differences from interfering with the results. Figure  2 shows the field experiments we conducted, demonstrating temperature and moisture changes over 10 years at the same location.

For each subdataset, we subtracted all the data from dataset X j in year j from the data from dataset X i in the year i (where i  >  j ) to acquire the difference dataset ∆ X ij . We then repeated the prior process until all the years had differenced and aggregated all the subsets to obtain the total difference dataset ∆ X .

To determine the most appropriate model for the dataset, we identified the optimal model by calculating and comparing the AIC and BIC of the various models (Supplementary Table  6 ). To further ascertain whether random effects that corresponded to the variations in both the slope and intercept among crops and climates were needed, we evaluated the improvement in model fit between the null model (no random effect) and three alternative models (random effect on the intercept only, random effect on the slope only, and random effect on the slope and intercept). By comparing the Akaike information criterion (AIC) values of these models, the random-effects structure that best described each dataset included random variation in both the slope and intercept. Consequently, to assess the significance of the fixed effects (averages across climate and crop types for the slope and intercept of the crop biomass C in response to temperature), a random-effects structure including random variation in both the slope and intercept was employed. We utilised bootstrapping to determine the confidence interval and applied the t test to compare the slopes generated from the mixed-effects models related to the different models 47 .

Field experiment and soil sampling

The experimental sites were located at the National Field Science Research Stations of the Chinese Academy of Sciences (NFSRS) in Hailun (126°38′ E and 47°26′ N, cold temperate climate zone with soil type Mollisols); Fengqiu (114°24′ E and 35°00′ N, warm temperate climate zone with soil type Inceptisols); and Yingtan (116°55′ E and 28°15′ N, subtropical climate zone with soil type Ultisols). The mean annual temperature and precipitation were 1.5 °C and 550 mm at the Hailun station, 13.9 °C and 605 mm at the Fengqiu station, and 17.6 °C and 1795 mm at the Yingtan station, respectively.

To investigate the effect of climate warming on crop biomass C, we set up a series of in situ blocks with a size of 1.4 m in length × 1.2 m in width × 1.0 m in depth at three experimental stations in October 2005. These blocks were surrounded by 20 cm thick cement mortar brick walls, paved underneath with quartz sand (3 cm in thickness) and covered on the inside with a tarpaulin to isolate it from its surroundings.

We collected profiles of the three soils in layers at each station. The soil was stratified every 20 cm per layer during excavation to ensure an intact soil matrix. The soil layers were subsequently transported to the Hailun, Fengqiu and Yingtan experimental stations, where they were poured into the brick cement ponds in the experimental block in the original order of the soil layers (Supplementary Fig.  2 ). To simulate accelerated SOM decomposition, we translocated the Mollisols soil profiles from the Hailun station southward to the Fengqiu and Yingtan stations (Fig.  2a ). The cultivation in the translocated soils matched the local soils in terms of climatic conditions, sowing times, photoperiod, crop types and varieties, as well as fertilisation and other agricultural practices. Maize was planted every year beginning in the spring of 2006 in the regular fertiliser treatment (150 kg N ha -1 , 75 kg P ha -1 and 60 kg K ha -1 in the form of urea, (NH 4 ) 2 HPO 4 and KCl, respectively). All P and K fertilisers and half of the N fertiliser were applied before maize cropping. The other half of the N fertiliser was applied as a top dressing at the large trumpet stage of maize growth. Three biological triplicates were performed for each treatment.

From 2006 to 2015, in situ soil samples were collected at three sites each year between August and October following the maize harvest. At each site, three composite soil samples were collected, along with three aboveground plant samples, for a total of 9 plant and soil samples across all three sites. A total of 90 plants and 90 soil samples were collected in situ over the decade. In addition, three aboveground plant samples and three soil samples were collected at the Fengqiu and Yingtan stations within the translocation experimental sites, resulting in the cumulative collection of 60 plant and 60 soil samples over ten years. For each experimental block, maize straw and grain were collected and weighed. These samples were packaged and transported to the laboratory for drying, grinding and nutrient analysis. We examined winter soil temperature and moisture in the top 0–20 cm, collecting soil samples from this consistent depth. Five soil cores (2 cm in diameter, 0–20 cm depth) were collected from each block, using a five-point sampling method (one core at the centre and four points at the corners of a square plot). The cores were thoroughly mixed to generate a composite soil sample. The samples were sealed in polyethylene wrappers, stored on ice and transported to the laboratory. Soils for geochemical analyses were stored at 4 °C, and soils for DNA extraction were stored at − 80 °C. Furthermore, the soil pH was determined with a glass electrode at a water-to-soil ratio of 2.5:1 (v/w). The SOC content was analysed via oxidation reactions with potassium dichromate 48 . The SOM content was estimated using the van Bemmelen factor (1.724) multiplied by the SOC value and is reported as a percentage. The monthly temperature, soil temperature, and soil moisture were measured at three sites throughout the year with a digital thermometer (Trime TDR, TES-1310, Ltd.) 49 . In addition, we calculated the mean annual temperature, mean annual soil temperature, mean growing season temperature, mean growing season soil temperature, mean winter temperature and mean winter soil temperature. The mean growing-season temperature, mean growing-season soil temperature and mean growing-season soil moisture represent the mean values during the crop reproductive periods at the Hailun, Fengqiu, and Yingtan experimental sites. Moreover, the mean winter temperature, mean winter soil temperature and mean winter soil moisture indicate the three-month average during minimum temperature in Hailun, Fengqiu, and Yingtan, respectively.

Soil mineral and micronutrient measurements

We utilised two distinct extraction methods—sodium pyrophosphate and acidic ammonium oxalate—to isolate different forms of aluminium (Al)- and iron (Fe)-bearing minerals. The extracted forms of Fe and Al, designated Fe p , Al p , Fe o , and Al o 50 , were subsequently subjected to inductively coupled plasma‒mass spectrometry (ICP‒MS) using a NexION 350x ICP–MS spectrometer (PerkinElmer, USA). Fe p includes organo-complexed Fe and dispersible colloidal Fe 50 , 51 . Al p corresponds to Al in humus complexes and, in most soils, can be used to estimate Al in such complexes 50 . Fe o often includes nanogoethite, ferrihydrite, and other short-range-ordered phases 52 . Acidic ammonium oxalate-extractable Al (i.e., Al O ) is short-range-ordered Al and organo-complexed Al in soils 53 . Moreover, micronutrients (including available Fe, Mn, Cu, and Zn) were extracted from soil samples using diethylenetriaminepentaacetic acid 54 . The micronutrient content in the extracted supernatant was subsequently quantified using an atomic absorption spectrophotometer (Pin AAciie 900 F, PE, USA).

Straw and grain C content measurements

Dry combustion is a method widely used for determining plant organic C content. After collecting plant samples in the field, we used a drying oven to desiccate the straw and grain at 70 °C until a constant weight was achieved. The dried straw and grain were then pulverised using a high-speed universal grinder. Crop biomass C was then determined by high-temperature combustion using an elemental analyser (Vario EL cube, Elementar Analysensysteme GmbH) 55 . It should be noted that for a set of 20 samples, calibration with a standard reference material was carried out to correct for potential errors due to atmospheric variations. At least three analyses were performed for each sample, and if the standard deviation of the C content exceeded 0.3%, a retest was performed.

Extracellular enzyme activity assays

Soil α-glucosidase and β-glucosidase activities were measured using a 4-methylumbelliferone substrate, which was split into high-fluorescence cleavage products upon hydrolysis 56 . Briefly, 1 g of fresh soil was added to 91 ml of Milli-Q water and homogenised with a magnetic stirrer for 3 min. For the hydrolases, the resulting suspension (200 μl) was dispensed into 96-well microplates with 50 μl of 4-methylumbbelliferone in pH buffers. Sixteen replicate wells were set up for each sample and for each standard concentration. The assay plate was incubated in the dark at 25 °C for 3 h to simulate the average soil temperature. Enzyme activities were corrected using fluorescence quenching. Fluorescence was measured using a microplate reader (EnSpire 2300 Multilabel Reader, Perkin Elmer, Waltham, MA, USA) with 355-nm excitation and 460-nm emission filters. The activities were expressed as μmol d −1 g −1 soil.

Microbial community characterisation

Microbial genomic DNA was extracted from soil samples using the MoBio Kit in combination with liquid nitrogen freeze-thawing 57 . In brief, for each soil sample, microbial DNA was extracted from 1.5 g of soil using grinding and freeze-thawing methods 57 and purified with a PowerSoil DNA Isolation Kit (MoBio Laboratories) following the manufacturer’s protocol. The concentration and purity of the extracted DNA were tested using a NanoDrop 2000 (Thermo Fisher Scientific, USA). The quality requirements were as follows: concentration ≥ 20 ng μL − 1 , total concentration ≥ 500 ng, and OD260/280 = 1.8–2.0. DNA samples were stored at − 80 °C until use.

We used a two-step PCR amplification method for library preparation of the 16S rRNA gene (V4 region) and the 18S rRNA gene (V9 region) to improve sequence representation and quantification 58 , 59 . During the first amplification step, 10 ng of DNA from each sample was PCR-amplified for 10 cycles in triplicate in a 25 μl reaction volume with primers without adaptors. The obtained PCR products were purified and dissolved in 50 µl of deionized water. This initial amplification step avoided potential amplification bias caused by long tails of adaptors and other added components. During the second amplification step, 15 µl of the PCR products from each sample were amplified using the primers with all adaptors, barcodes and spacers in triplicate for an additional 15 cycles. A low total number of cycles (25–30 cycles) ensures that the PCR amplification is not saturated and limits amplification artifacts. Finally, the triplicate amplified products were combined, purified and quantified for subsequent sequencing using the same MiSeq instrument with 2 × 250 base pair kits. The primer sequences were trimmed from the paired-end sequences and subsequently merged using FLASH 60 . Any merged sequences with an ambiguous base or a length of < 245 bp for the 16S rRNA gene or < 330 bp for the 18S rRNA gene were discarded. These high-quality 16S rRNA gene or 18S rRNA gene sequences were processed to generate amplicon sequence variants (ASVs; also known as unique sequence variants and zero-radius operational taxonomic units (OTUs)) by UNOISE3 61 .

Projected loss of total crop C calculations

Total crop C (kg ha − 1 ) 62 was defined as the product of crop biomass (kg ha − 1 ) and crop biomass C content (%) in our study, as shown in Eq. ( 2 ). Total crop C encompasses both straw and grain. Previous studies suggest that crop biomass C content remains relatively stable within certain limits, with straw and grain C content approximately 40% and 42% 63 , 64 , 65 , respectively. By combining global meta-analyses with long-term experimental data, straw and grain C content change was observed with factors such as climate, soil properties, and management practices, leading to significant differences between actual total observed crop C and previous estimated total crop C.

where i represents different crop components, including straw and grain, and j represents the calculation method, including actual observed crop biomass C and previous estimated crop biomass C.

Linear regression analysis was conducted on decade-long field experiment data, using the time of the experiment as the explanatory variable and total crop C as the response variable. The regression model is described by Eq. ( 3 ):

where \(\alpha\) represents the intercept and \(\beta\) is the estimated coefficient in the linear regression model.

Using the first year as the baseline, total straw and grain C changes were estimated over the decade by subtracting the total crop C of the first year from that of the tenth year of the field experiment, as shown in Eq. ( 4 ):

where 10 represents the 10 th year, and 1 represents the 1 st year in the decade-long field experiment.

The projected loss of total crop C was assessed by subtracting the change in the previous estimated total crop C from the change in actual total crop C over the decade and then dividing by the average actual total crop C over the ten-year period (Supplementary Fig.  12 ), as calculated by Eqs. ( 5 ) and ( 6 ):

Data analyses

To evaluate the importance of various environmental factors on crop biomass C, we utilised the ‘randomForest’ function of the ‘randomForest’ R package to construct a random forest model for the global datasets 66 . Hierarchical partitioning analysis was then performed using the ‘glmm.hp’ function from the ‘glmm.hp’ R package to assess the effect of different temperatures on crop biomass C 67 . Before characterising the relationship between temperature and crop biomass C, we needed to determine the best model for the global dataset. Then, we constructed linear, nonlinear, mixed linear effects, and mixed nonlinear effects models using the ‘glm’ function from the ‘stats’ package 68 , the ‘nlsLM’ function from the ‘minpack.lm’ package 69 , and the ‘lme’ and ‘nlme’ functions from the ‘nlme’ package 70 . By calculating and comparing the AIC and BIC of each type of model, we identified the optimal model. After determining the type of model, first, a range of null models was established, including linear regression and mixed effects models, with climate type, crop type, or both considered random effects. Second, based on the minimum AIC, a mixed effects model with intercepts and slopes as random effects were identified. Finally, the model was operationalized using the ‘lme’ function from the ‘nlme’ R package 70 , designating crop biomass C as the dependent variable, temperature as the fixed effect, and both climate and crop type as random effects. The linear mixed-effects model was fitted successfully, and its residual distribution was tested for normality using the Shapiro‒Wilk test. In addition, the significance of the difference between the model and the null model was ascertained using an ANOVA chi-squared test, and confidence intervals for the model were calculated using the bootstrap method. Given the close correlation between MWST and SOM, we controlled for the MWST variable in our analyses to accurately evaluate the importance of SOM on crop biomass C. We utilised a mixed-effects model, in which climatic conditions and crop type served as random effects, to assess whether SOM significantly influenced the model residuals between MWST and crop biomass C (Supplementary Fig.  13 and Supplementary Tables  2 , 7 ). Furthermore, to eliminate the interference of MWST on the relationship between SOM on crop biomass C, we excluded the MWST variable from the model and employed a random forest model on the remaining variables (Supplementary Fig.  14 ). The results demonstrated that the reduction in SOM continues to lead to a decrease in crop biomass C, even after excluding the influence of MWST. This explicitly confirms that MWST does not underestimate the significant contribution of SOM to crop biomass C. Statistical analyses of the global dataset and data visualisation were performed in R (version 4.2.2; http://www.r-project.org/ ). For long-term field experiments, the assumptions of t tests (two-sided), and linear regression models were validated using tests for normality and homogeneity of variance. Linear regression models were used to explore the correlation between different temperatures and both crop biomass C and SOM. The beta coefficients for the effects of temperatures on straw and grain carbon content were estimated using 999 bootstrap resamples. After one-way ANOVA was completed, Tukey’s post-hoc test was used to compare model differences across temperatures, and Duncan’s New Multiple Range Test was used to compare decreasing rates of crop biomass C in response to rising winter soil temperature across three in situ regions. Finally, structural equation modelling (SEM) was conducted to investigate the direct and indirect effects of winter temperature, mineral protection, soil properties, microbial properties and enzyme activities on crop biomass C. This approach can distinguish between direct and indirect effects that one variable may have on another and is, therefore, useful for exploring complex relationships in global ecosystems. SEM analyses were carried out using AMOS 21.0 (AMOS Development Corporation, Chicago, IL, USA), with model fit assessed by the χ2 test and the root mean square error of approximation 71 .

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The raw data, including the meta-dataset and decade-long field experiment data, necessary to support the conclusions of this study are available on Figshare ( https://doi.org/10.6084/m9.figshare.26771899.v2 ) 72 or can be found in Supplementary Data  1   Source data are provided in this paper.

Code availability

The code for the meta-analysis in this paper is provided from Supplementary Code  1 and is available on Figshare ( https://doi.org/10.6084/m9.figshare.27129078.v3 ) 73 .

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Acknowledgements

The authors received funding from the National Natural Scientific Foundation of China (42425703, 42377121 to Y.L.), National Key R&D Programme of China (2021YFD1900400 to Y.L.), Jiangsu Natural Science Foundation (BK20240015 to Y.L.), Innovation Programme of Institute of Soil Science (ISSASIP2201 to Y.L.) and Youth Innovation Promotion Association of Chinese Academy of Sciences (2016284 to Y.L.).

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These authors contributed equally: Haowei Ni, Han Hu, Constantin M. Zohner, Weigen Huang.

Authors and Affiliations

State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

Haowei Ni, Han Hu, Weigen Huang, Yishen Sun, Jixian Ding, Xiaoyuan Yan, Jiabao Zhang & Yuting Liang

University of Chinese Academy of Sciences, Beijing, China

Haowei Ni, Han Hu, Weigen Huang & Yishen Sun

Department of Environmental Systems Science, Institute of Integrative Biology, ETH, Zurich, Switzerland

Constantin M. Zohner & Thomas W. Crowther

State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, China

Department of Agroecology, Aarhus University, Tjele, Tjele, Denmark

iCLIMATE Interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, Denmark

School of Biological Sciences, University of Oklahoma, Oklahoma, Oklahoma, USA

Jizhong Zhou

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Y.L., T.C. and J.Zhang conceptualised the study. J.C., C.Z., H.N., H.H., Y.L., Y.S. and X.Y. developed the methodology. H.N., H.H., W.H., Y.S., J.C., J.D., J.Zhou, and Y.L. conducted the investigation. H.N., H.H., W.H. and J.D. curated the data. H.N., H.H., C.Z., W.H. and J.C. performed the formal analysis. Y.L., T.C., X.Y. and J. Zhang supervised the project. Y.L., H.N., H.H. and W.H. wrote the initial draft, and H.N., H.H., C. Z., W.H., J.C., Y.S., J.D., J. Zhou, X.Y., J.Zhang, Y.L. and T.C. reviewed and edited the manuscript.

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Ni, H., Hu, H., Zohner, C.M. et al. Effects of winter soil warming on crop biomass carbon loss from organic matter degradation. Nat Commun 15 , 8847 (2024). https://doi.org/10.1038/s41467-024-53216-2

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Is it really organic? Credibility factors of organic food–A systematic review and bibliometric analysis

László bendegúz nagy.

Department of Agricultural Business and Economics, Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary

Zoltán Lakner

Ágoston temesi, associated data.

All relevant data are within the paper and its Supporting Information files. The dataset used for bibliometric analysis was uploaded as Supporting Information files.

Consumer trust and organic food product credibility play a crucial role in understanding consumer behavior. The aim of this review is to identify extrinsic factors which influence consumers’ perceived trust in organic food. The research was conducted based on the PRISMA guidelines. During our search, 429 articles were found, from which 55 studies were selected for further analysis. To assess the connection between the selected articles, a bibliometric analysis was done with VOSViewer and CitNetExplorer software. The following factors were identified as influencing the credibility of organic food: labeling, certification, place of purchase, country of origin, brand, price, communication, product category, packaging. From these, labeling, certification, and country of origin are well-researched factors in relation to credibility. The significance of the other discovered factors is supported; nonetheless, further research is needed to evaluate their effect on consumer trust.

Introduction

The importance of organic food is well indicated by the steadily growing market. As sustainability is more and more in the focus of food product development, organic food is becoming a successful concept in the food industry [ 1 ]. Whilst in 2008, the organic food market reached 50,9 billion USD [ 2 ], the sales of organic food doubled in only a decade, up to 119 billion USD in 2019 [ 3 ].

This growth in organic food sales can be attributed to an increased demand for organic food. The vast majority of this demand originates from North America and Europe, nonetheless, local organic markets are rising in Asia, Latin America, and Africa [ 1 ]. On account of the increasing demand for organic food, consumer trust has gained great interest among researchers [ 4 ]. However, no review article has been written on this particular topic so far.

Credibility is a relatively new research field in the context of consumable products. Green et al. [ 5 ], Plasek & Temesi [ 6 ] and Küster-Boluda & Vila [ 7 ] examined credibility in the case of alternative medicine, functional food, and low-fat food, respectively. Other researchers have explored fields related to food products in terms of credibility. Anders et al. [ 8 ] examined it within third-party certification in the food supply chain, Kumar & Polonsky [ 9 ] researched it from food retailer perspective.

Organic food can be defined based on Kahl et al.’s [ 10 ] definition: “Organic food is produced within a regulated and certified production process.” According to them, food can be described by intrinsic or extrinsic quality attributes. These attributes are strongly related to consumer expectations and trust [ 11 ].

Organic food is considered as a credence good, because there is an information asymmetry between the consumers and producers [ 12 ]. In the case of credence quality, the consumer of a product can not fully evaluate the quality of a particular good [ 13 ]. In terms of organic food, it means that the presence or absence of the organic attributes is not detectable by consumers even after purchase and consumption of the product [ 12 ].

The most widely accepted definition of trust comes from Rousseau et al. [ 14 ]: “a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intention or behaviour of another.” From our viewpoint, it means that the consumers’ tolerance for ambiguity is increased as a result of an inner assurance or conviction [ 15 ]. According to Thorsøe et al. [ 15 ] there is a strong link and dependence between trust and credibility, because actors, such as producers or retailers, must be credible to generate trust in consumers, although they can not control the consumers’ perception, which can generate distrust.

Research methodology

Our purpose in this review is to find all extrinsic, product-related factors which determine credibility and trust in organic food products. To detect those factors, we used PRISMA guidelines for this review. PRISMA enables review authors to summarize evidence in a selected field accurately and reliably [ 16 ]. There is no existing review protocol for this kind of research field.

For this review, we used Web of Science and SCOPUS search engines, as those databases considered the widest and recommended sources in our research field [ 17 ]. We conducted the searches during October 2021, the last search was done on 15 th October 2021. To find all relevant articles about the credibility factors of organic food, we used several search phrases. The composition of search expressions had been supported by term frequency–inverse document frequency method (TF-IDF) on some randomly chosen text from the relevant field. The term “organic food” or “organic product” or “organic produce” or “organic” had to be in the title of the article, as well as “consumer” or “consumption”. These phrases narrowed down the scope of the articles mostly to consumer-related topics of organic food. In addition, the abstracts of the articles had to contain at least one of the following phrases: “trust”, “credence”, “credible”, “credibility”, “scepticism”, “beliefs”, “authenticity” or “communication”. With the above mentioned search phrases we ran pre-tests on the Web of Science search engine which proved to be accurate to describe our research topic. We did not limit the publication date of the studies, because the earliest study that we found on this particular topic was from 2002. For these search phrases, we found 212 results in Web of Science and 218 results in SCOPUS. From these, 162 records were duplicates, which were discarded (see Fig 1 ).

To screen and select the articles for our review, we used Covidence online software, which enabled us to evaluate articles by two authors independently in 2 steps. In the first step, we evaluated the remaining 268 articles by reading the abstract only. In this step, we excluded 106 studies, which were irrelevant to our topic. In some cases, it was not unequivocal from the abstract if an article was relevant, so these studies were selected for the full-text assessment.

In the second step, 162 articles were assessed for eligibility by reading the full-text. During this step, 107 studies were excluded for various reasons. The most common reason was being irrelevant for our research. These articles contained the required search words, although organic food consumption behavior was not assessed in the context of credibility or trust. 15 studies were excluded because of poor results, 8 articles were in a foreign language, 3 studies included a conceptual model with no results explained and 3 articles were not accessible.

Besides the systematic review, a bibliometric analysis was conducted on the selected articles to reveal the connection between the identified credibility factors. For this purpose, two different software packages were used. VOSviewer (version 1.6.15) software is capable of visualizing networks and forming clusters, which enables further analysis [ 18 ]. CitNetExplorer (version 1.0.0) can be used to study the development of a research field, which can support the literature review [ 19 ].

Only a few research has tried to tease out all possible credibility factors. Danner & Menapace [ 20 ] found 5 authenticity-related themes: organic label, origin, retail outlet/brand, packaging, product category. Tangnatthanakrit et al. [ 21 ] proposed 5 factors, which influence organic food trust: control, competence, characteristics, communication and community. Some studies list other factors as well, like natural taste, merchandising, knowledge, scarcity, and tourism [ 22 ], although there is no evidence behind these factors as to their influence on the credibility of organic food.

From the selected, manually analyzed 55 articles (see Table 1 ), we identified the following 9 exogenous factors which can influence the credibility of a food product: labeling, certification, place of purchase, country of origin, brand, price, communication, product category, and packaging.

Bibliometric analysis

Of the selected 55 papers, more than half were published after 2016, which indicates the current interest in this research field (see Fig 2 ). Only 7 studies were conducted before 2010.

In terms of location, most of the research was conducted in European countries. More than 1/3 of the articles report results from Asian countries, and only 8 papers write about North American consumers, which does not represent the actual size of the organic food market of these continents. There are 2 articles from Brazil and Australia each, which provide valuable results as well.

Fig 3 shows the connections and co-occurrence of the identified credibility factors. With the VOSviewer software, the terms related to credibility, trust, and the influencing factors were chosen from the abstracts. The size of each circle represents the number of occurrences in the selected articles, and co-occurrence is illustrated by the distance between the circles.

Based on the connections of the 9 identified credibility factors, 4 clusters could be identified. The red cluster contains the most terms, and trust is the most relevant term in the selected papers. Trust is strongly related to organic label and shop, although retailer and brand are also significant to trust, which correlates with the findings of Padel & Foster [ 23 ]. In the blue cluster, labeling, certification, price, authenticity, and low trust are very closely related to each other. Retail chain and product category also belong to this cluster, which supports the results of Danner & Menapace [ 20 ].

Communication, which is mentioned by Tangnatthanakrit et al. [ 21 ], is in the middle of the light green cluster, and it is very close to labeling and concern, although concern belongs to the green cluster. Logo, inspection, and certification also appear in the light green cluster with the European Union, which shows that most of the research related to organic logos was about the EU organic logo. Concern, distribution, trust issue, and country are the main terms in the green cluster. These terms represent the connection between country of origin and consumer concerns. Although these clusters do not represent each credibility factor, this analysis is a good indicator of the connections between the factors.

The visualization capability of CitNetExplorer has been a useful tool because it allowed us to find the most relevant publications and investigate the intellectual roots of our research topic. With the CitNetExplorer, connections between the citations of the chosen 55 papers can be visualized, as seen in Fig 4 .

Each circle represents a publication, and publications are labeled with the first author’s last name. Vertical location shows publication year, with old articles at the top and new publications at the bottom. In the horizontal direction, publications are arranged according to citation relationships. Highly cited publications that take into account direct and indirect citation relationships tend to be closer to each other horizontally. Publications that are less relevant with respect to other citations are further away [ 24 ].

Nine publications were cited 10 or more times, from which 3 papers are included in the review. The article by Padel & Foster [ 23 ] was cited most frequently, namely 21 times. They investigated qualitatively consumers purchasing decisions of organic food. From our perspective, their most important findings were that labeling, certification and the country of origin play an important role in the perceived trust of organic food, which tend to be the major factors in later publications as well.

Almost the same amount, 20 papers cited the review of Hughner et al. [ 25 ], in which they explore the reasons why people buy organic food. This publication does not mention trust related factors of organic food, although it gives important conclusions about the nature of organic food consumption.

Four articles were cited 13 times, from which 3 were published before 2010. Krystallis & Chryssohoidis [ 26 ] discussed the importance of labeling, certification and the place of purchase from the credibility perspective. Lea & Worsley [ 27 ] investigated Australian consumers’ beliefs about organic food. Aertsens et al.’s [ 28 ] review is discussing the personal determinants of organic food consumption.

Nuttavuthisit & Thøgersen’s [ 29 ] article was published in 2017, although it was cited 13 times, which shows the relevance of this paper to our topic. As they did a qualitative research about the consumer trust in Thailand, it offers important statements about the credibility factors of organic food in emerging countries.

The oldest cited publication is from 1973, written by Darby & Karni [ 13 ]. In their publication, they clarify the meaning of the credence attribute, which explains the high citation number.

Certification

Half of the selected articles—28 by number—mention certification as one of the most important factors influencing the credibility of organic food. Organic logos are discussed in this part because these logos represent the certification itself, and usually, it is a legal requirement as well.

Evaluating the selected research, it can be observed that generally, consumers have lower trust towards organic food with a certification from a developing country. For example, general trust in the certification system is low in Thailand [ 27 ], but it can create trust if consumers know about the certification body [ 30 ]. The preference for certification from a developed country and lack of trust in the local certifiers can be seen in the case of Brazilian [ 31 ], Russian [ 32 ], Indian [ 33 ], Vietnamese [ 34 ], and Chinese [ 35 ] consumers.

We observed some opposite results as well. Malaysian consumers trust their national organic logo, myOrganic [ 36 ]. In the case of oolong tea, Chinese consumers prefer Chinese organic certification [ 37 ].

In the case of European consumers, we can see a more nuanced picture. Janssen & Hamm [ 38 ] examined consumer reactions to organic logos in six European countries. Their results show that organic logos create consumer trust; well known and trusted logos are perceived by the consumers as having stricter standards and control system behind them. Consumers from the United Kingdom trust their national logo more than the European Union organic logo or an organic product without any logo [ 39 ]. Czech, Danish, German, Italian and UK consumers also have lower trust towards European Union organic logo compared to their national organic logo [ 40 ], although it is important to mention, that compulsory EU logo usage was recently implemented by the time of data collection of the research. Based on the research of Zander et al. [ 41 ], which was performed in six European countries, trust in the certification system and organic logo can be differentiated by types of consumers. Regular and occasional organic consumers trust organic certification regardless of its origin, on the other hand, consumers who have higher knowledge and involvement towards organic food have lower trust in global certifications.

The organic food market is different in the United States and Canada, although consumer attitudes are similar to the European market. Certification plays an important role in the credibility of organic food in the case of Canadian consumers [ 42 ]. Both Kim et al. [ 43 ] and Van Loo et al. [ 44 ] agree that in the case of consumers from the United States, an USDA organic logo creates more trust than any generic organic logo.

Overall, most of the research shows that certification has a significant role in the credibility of organic food, but Yin et al. [ 45 ] question the importance of it. According to them, certification has no impact on consumer trust in the case of milk products. Tangnatthanakrit et al. [ 21 ] obtained similar results during their research in Thailand.

Labeling is as important for a product to be credible as certification. Labeling is a general term in this case since it partly covers other factors as well, like certification, brand, or packaging. There is no clear distinction amongst the authors between labeling and organic logos; some research considers organic logos as part of the labeling. In this review, we consider labeling as information about the product displayed on the packaging, and organic logos were discussed separately in the previous sub-section.

According to Teng & Wang [ 46 ], Essoussi & Zahaf [ 42 ], Lee et al. [ 47 ], Chen & Lobo [ 48 ], Padel & Foster [ 23 ], and Sobhanifard [ 49 ] labeling is significant to the creation of consumer trust in the case of organic food. Most research shows a positive relationship between labeling and credibility, although a lot of them challenge it as well. For example, Thorsøe et al. [ 15 ] proved that Danish consumers trusted organic labeling, Meyerding & Merz [ 50 ] used an eye-tracking method and found evidence that the presence of an organic label created trust in the product. On the other hand, based on Činjarević et al. [ 51 ], Croatian consumers are skeptical about the organic claims on labeling; Tung et al. [ 52 ] agree that Taiwanese consumers do not trust organic labels.

Trust in labeling can change over time, as Vittersø & Tangeland’s [ 53 ] study in Norway shows. They compared data from 2000 and 2013, and found that Norwegian consumers had more trust in organic labeling in 2000 than in 2013. Also, the content of the labeling is not indifferent for credibility. Nutritional values on the labeling enhance trust in the organic labels, based on the research of Liang & Lim [ 54 ].

Place of purchase

Of the selected articles, nineteen pay attention to the place of purchase as a factor influencing credibility. The majority of those papers, namely 16 cover only retailers, 2 paper mention supermarkets, and only 1 inspects trust from the perspective of online shops. Unfortunately, we did not find any research on organic specialty shops, direct sale, or farmers’ market, although these sales channels can be important in the case of organic food.

We found miscellaneous results regarding supermarkets and organic food trust. Mostly in the United States, United Kingdom, and Canada, consumers have low trust in organic food if it is sold in a superstore [ 23 , 55 , 56 ]. Nonetheless, research has confirmed that positive consumer perception of a retailer has a positive impact on the credibility of the organic food sold there [ 57 – 61 ]. In their work, Pivato et al. [ 11 ] show a positive relationship between the corporate social responsibility (CSR) activities of a retailer and the trust in the organic food sold in their stores.

Many retailers are selling organic food under private labels, so there is a bit of an overlap between the place of purchase and the branding of a product. According to Perrini et al. [ 62 ] consumers are more likely to trust private-label organic products if they consider the retailer as socially responsible.

Organic food retail could not avoid the spread of e-commerce, although research is very limited in this field. Yue et al. [ 63 ] investigated the influence of online product presentation on organic chicken breast. Based on their research, the media richness of online product presentation and review lengths of organic products impact the trust in organic food.

Country of origin

The origin of organic food has significant importance for perceived credibility. This topic was partly discussed in subsection Certification, because organic food is usually certified in the country where it comes from. As in the case of certification, we can see differences between consumers of developed and developing countries, although based on Thøgersen et al. [ 64 ] country of origin is an even more important cue for consumers than organic labeling both in developed and developing countries.

According to Lee et al. [ 47 ], Yip & Janssen [ 65 ], and Thorsøe et al. [ 15 ] Taiwanese, Hong Kong, and Danish consumers have higher trust in local organic food compared to imported ones. Canadian and UK consumers are skeptical about imported organic food [ 23 , 56 ].

Based on the findings of Bruschi et al. [ 32 ], Chen et al. [ 35 ], Yin et al. [ 66 ] and Yormirzoev et al. [ 67 ], the opposite reaction can be seen by consumers from developing countries. Chinese consumers trust organic food from developed countries [ 35 , 66 ], Russian consumers trust European organic food [ 32 , 67 ]. These findings can be explained with the research of Pedersen et al. [ 68 ]. Based on their results, the image and trust in the exporting country affect the trust in the organic food they export.

Other factors

Brand, price, communication, and product category were also identified as influencing factors of credibility, although only a few articles discuss these factors.

Brand is a trust-building factor in the case of organic food. Yin et al. [ 45 ] found that well-known brands are trusted more compared to lesser-known brands. According to Steffen & Doppler [ 60 ], the branding of organic food creates more trust than certification. CSR activities of organic food companies can positively influence consumer trust of organic food [ 69 ]. The lack of known brands can cause trust issues in certain markets [ 33 ].

The effect of price on organic food authenticity is supported by the bibliometric analysis. Research has proved that the high price of organic food is a barrier to consumption [ 70 ]. On the other hand, Lee et al. [ 47 ] point out that premium price affects trust in organic food, and Yin et al. [ 45 ] proved that in the case of organic milk, low price reduced consumer trust in the product. This is true the other way around: consumers are not willing to pay more for organic food if they do not trust it [ 26 ].

Product-level and retail-level communication help to build trust toward organic food [ 71 , 72 ], although Perić et al. [ 73 ] disagree with it. According to them, 63% of Serbian and 50% of Croatian consumers do not believe advertisements on organic food, which derives from the general mistrust in the media and advertising. Müller & Gaus [ 74 ] investigated the effect of media on organic food trust. Based on their research, negative media harms the credibility of organic food products.

The credibility of certain organic product categories is questionable for consumers. According to Lockie et al. [ 75 ], processed organic food makes consumers suspicious whether it is in fact organic. Consumers’ trust can varies on fresh produce category. Based on Watanabe et al. [ 76 ], consumers trust organic vegetables better than organic fruit.

Packaging seems to influence consumers’ trust in organic food, although there is very limited research on this topic. Danner & Menapace [ 20 ] identified packaging as an influencing factor, although its impact on credibility was questioned only by the consumers of the German-speaking countries, whereas USA consumers did not find it a credibility issue. German, Austrian and Swiss consumers believe that in the case of organic fruit and vegetable, plastic packaging makes them appear ‘less organic’ [ 20 ]. In their review, Hemmerling et al. [ 70 ] confirm the theory that packaging seems to be not environmentally friendly in the eye of consumers, as it is against the idea of organic food, although packaging can also be useful because it can indicate the organic status of the product. Nuttavuthisit & Thøgersen [ 29 ] mention that consumers rely on the appearance of the packaging when they assess the credibility of organic food.

Conclusions and future perspectives

The goal of our research was to identify the factors which influence the perceived credibility of organic food products. In the review, we could find 9 different product-related factors, not equally well-researched, and there are blind spots where further research is needed.

The interest in organic food is growing, however we can see a shift from developed to developing countries in terms of geographical focus of the articles. This shift and geographical difference in consumer attitudes could be detected by almost all identified factors of organic food credibility.

Certification is one of the most important factor to build consumer trust, as certification covers all those activities where compliance with organic requirements are assessed, so that should be a guarantee for consumers. Existing research shows a clear pattern regarding the credibility of certification bodies in different countries. Certifications from developed countries are much more trusted compared to certifications from developing countries.

Labeling has the role to inform consumers about the product. Without this information, consumers can not be sure if a product is organic. Besides certification, labeling is crucial to inform consumers about the organic characteristics of a product, which transfers the credence attribute to a search attribute. The importance of labeling can be explained with the fact, that labels contain most of the information about the product, so consumers can assess the product from other perspectives (eg. nutritional values, origin, ingredients, etc), which might influence perceived trust.

Labeling is well researched factor, however there are some kind of loose products, where the lack of labeling is common practice, like fruit and vegetables or bakery products. In those cases, credibility might be questioned by consumers, so research on these products is desirable.

The results of the credibility aspects of the country of origin seem to correlate with the results on certification, and the findings are strongly related to the results of the bibliometric analysis. Organic products from developing countries can cause doubt in consumers both from developed and developing countries, which might indicate the general low institutional trust in these countries.

Research on the effect of place of purchase proves its importance, although it is incomplete in several areas. According to Ökobarometer [ 77 ], German consumers mostly buy organic food in supermarkets and discounters, although traditional markets, specialty shops, and direct purchase also play an important role in organic food retail. However, these sales channels were not taken into account in the existing research, thus further research is needed.

In the case of certification, labeling, and country of origin, the findings of existing research seem to provide enough evidence to draw a reliable conclusion. All of these factors play an important role in the perception of trust towards organic food.

Brand was less-researched in relation to credibility, but all evidence shows that it has a positive impact on the authenticity of organic food. Similarly, not much research has investigated the effect of price, communication, product category, and packaging of organic food on credibility, therefore further research is needed in connection to these factors. There are certain product attributes, which were not evaluated by previous papers, but the authors assumed that they might have a strong effect on organic food trust. As food packaging is getting in the scope of sustainability, it would be interesting to compare the influence of different type of packaging on the level of trust. Also, color of the package can influence consumers’ perceptions of organic food.

The main aim of this review was to cover all the credibility factors of organic food; however, there are many limitations of this work. Identification of the credibility factors was based on the selected papers, therefore there might be other factors influencing credibility in the case of organic food and other articles, which cover the topic of this review. The reviewed articles are covering a wide range of research methods and geographical locations, so the samples are not homogenous.

Supporting information

Funding statement.

The author(s) received no specific funding for this work.

Data Availability