research articles on food security in india

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Measuring Food Insecurity in India: A Systematic Review of the Current Evidence

Fiona h. mckay.

1 School of Health and Social Development, Faculty of Health, Deakin University, Victoria, Australia

2 Institute for Health Transformation, Faculty of Health, Deakin University, Victoria, Australia

Paige van der Pligt

3 Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia

Associated Data

Purpose of review.

India is home to an estimated 200 million malnourished people, suggesting widespread food insecurity. However, variations in the methods used for determining food insecurity status mean there is uncertainty in the data and severity of food insecurity across the country. This systematic review investigated the peer-reviewed literature examining food insecurity in India to identify both the breadth of research being conducted as well as the instruments used and the populations under study.

Recent Findings

Nine databases were searched in March 2020. After excluding articles that did not meet the inclusion criteria, 53 articles were reviewed. The most common tool for measuring food insecurity was the Household Food Insecurity Access Scale (HFIAS), followed by the Household Food Security Survey Module (HFSSM), and the Food Insecurity Experience Scale (FIES). Reported food insecurity ranged from 8.7 to 99% depending on the measurement tool and population under investigation. This study found variations in methods for the assessment of food insecurity in India and the reliance on cross-sectional studies.

Based on the findings of this review and the size and diversity of the Indian population, there is an opportunity for the development and implementation of an Indian-specific food security measure to allow researchers to collect better data on food insecurity. Considering India’s widespread malnutrition and high prevalence of food insecurity, the development of such a tool will go part of way in addressing nutrition-related public health in India.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13668-023-00470-3.

Introduction

Food insecurity has been identified as a “pressing public health concern” in India [ 1 •]. At the household level, food security exists when all members, at all times, have access to enough food for an active, healthy life [ 2 ••]. Individuals who are food secure do not live with hunger or fear starvation. Across urban settings, the prevalence of food insecurity has been found to range from 51 to 77%, yet over 70% of India’s population resides rurally, where data concerning food insecurity is limited [ 3 ].

The concept of food security consists of six main dimensions: availability, access, utilization, stability, agency, and sustainability. The first three dimensions are interlinked and hierarchical. Food availability is concerned with ensuring that sufficient quantities of food of appropriate quality are supplied through domestic production or imports (including food aid). Access to food is necessary but not sufficient for access. Access is concerned with ensuring adequate resources, or entitlements, are available for the acquisition of appropriate foods for a nutritious diet. Access is necessary but not sufficient for utilization. Utilization is concerned with the ability of an individual to access an adequate diet, clean water, sanitation, and health care to reach a state of nutritional well-being. The three other concepts have become increasingly accepted as important, as risks such as climatic fluctuations, conflict, job loss, and epidemic disease can disrupt any one of the first three factors. Stability refers to the constancy of the first three dimensions. Agency is recognized as the capacity of individuals or groups to make their own food decisions, including about what they eat, what and how they produce food, and how that food is distributed within food systems and governance. Finally, sustainability refers to the long-term ability of food systems to provide food security and nutrition in a way that does not compromise the economic, social, and environmental bases that generate food security and nutrition for future generations [ 4 ••].

Two hundred million people living in India are estimated to be malnourished [ 5 •]. Poverty, a lack of clean drinking water, and poor sanitation have been identified as common factors contributing to malnutrition in India [ 1 •]. Yet to date, despite high rates of malnutrition pointing toward widespread food insecurity [ 6 ], the link between food insecurity and malnutrition in India has seldom been explored. Of the limited data available, associations have been found between household food insecurity and child stunting, wasting, and being underweight [ 7 ], highlighting the urgency of food insecurity as a public health priority.

Considering the high rates of child stunting, wasting, and overall malnutrition in India, exploring past and emerging research which has both assessed and addressed food insecurity is a crucial step in better understanding nutrition-related health at the population level. Currently, to the best of our knowledge, there is no published systematic review which has explored household food insecurity in India. To understand the factors that contribute to food insecurity at the household level, the related health and nutrition outcomes, and to conceptualize potential strategies which target food insecurity in India, a systematic review of published research undertaken to date which has focused on food insecurity in India is urgently needed. This review seeks to (1) systematically investigate the peer-reviewed literature that purports to investigate food insecurity in India, (2) identify the breadth of research being conducted in India, including the instruments used and the populations under study, and (3) provide an overview of the severity of food insecurity in India as presented by these studies.

A systematic search was undertaken to identify all food security research conducted at the household level in India. The search was conducted in March 2020. Key search terms were based on the FAO [ 8 ] definition of food security: “food access*,” OR “food afford*,” OR “food insecur*,” OR “food poverty*,” OR “food secur*,” OR “food suppl*,” OR “food sufficien*,” OR “food insufficien*,” OR “hung*” AND “household*” OR “house*” AND “India.” Searched databases included Academic Search Complete, CINAHL Complete, Global Health, MEDLINE, Embase, SCOPUS, ProQuest, PsychInfo, and Web of Science. To gain a full collection of articles that reported on research investigating household food security in India, no limits were placed on publication dates. Only peer-reviewed articles published in English were considered; unpublished articles, books, theses, dissertations, and non-peer-reviewed articles were excluded. This review adheres to the PRISMA statement [ 9 , 10 ], see Fig. ​ Fig.1 for 1  for a flowchart describing the process of screened included and excluded articles.

Flow chart of articles meeting search criteria, number of articles excluded, and final number of articles meeting inclusion criteria for review

Two authors (FHM and AS) and a research assistant reviewed all articles to identify relevant studies. Articles underwent a three-step review process (see Fig. ​ Fig.1). 1 ). All articles were downloaded into EndNote X7, duplicates were identified and removed, and the article titles, journal titles, year, and author names were then exported to Microsoft Excel 365 to facilitate reviewing. Articles were first screened by title and abstract based on the inclusion and exclusion criteria described above by two authors independently. Any article that clearly did not meet the inclusion criteria was removed at this stage, any that did, or possibly could meet the inclusion criteria on further inspection, were retained. The full text of the remaining articles was obtained, and at least two authors (FHM and AS) or a research assistant independently read all 161 articles that remained at this stage to determine if the article met the inclusion criteria. Any articles at this stage that clearly did not meet the inclusion criteria were removed. Any disagreements on those that were retained were discussed and settled by consensus between the authors.

Articles that discussed food insecurity in general but collected no new data (for example, Gopalan [ 11 ] and Gustafson [ 12 ]) were excluded, as were previously conducted reviews in the region (for example, del Ninno, Dorosh [ 13 ], Harris-Fry, Shrestha [ 14 ]). As this review was primarily interested in studies that purported to measure food insecurity in India, studies that discussed food insecurity, either as the standard measured construct or as a construct created by the authors but termed food insecurity, were included. While there are many non-government organizations and inter-government organizations that work to measure food or nutritional insecurity, the construct of “hunger,” the associated conditions of malnutrition (either with overweight or obesity) or conditions that might indicate malnutrition (including anemia or under-5 mortality), these reports generally do not include a complete description of the method used to collect data if data were collected at the household level and often use the sale or production of crops as a proxy; as such, these reports have been excluded from this review.

Data were extracted from each article by the three authors. Data were extracted into a Microsoft Excel 365 spreadsheet that allowed for the capture of specific information across all included articles. Data extracted at this stage included the following: location; population group; findings; measured food security (Y/N); method for determining food insecurity; and prevalence of food insecurity.

The search identified 1018 articles, of which 395 were duplicates. The titles and abstracts of the remaining 616 articles were read, with 518 articles excluded as they did not refer, either directly or indirectly, to food insecurity research in India, leaving 161 articles for further investigation. The full text of the 161 articles was reviewed; 108 articles were excluded as they did not meet the inclusion criteria. The remaining 53 articles were included in this review.

Most articles ( n  = 48, 90%) were cross-sectional studies; three were longitudinal, with data covering 27 years [ 15 ], 11 years [ 16 ], and 4 years [ 17 ], and one was a randomized controlled trial [ 18 ]. Eight studies employed a mixed methods approach, seven were qualitative, and the remaining 38 were quantitative studies. Participant numbers ranged in size from the smallest study with 10 participants [ 19 ] to population-level studies with over 100,000 participants [ 15 , 20 ]. See the supplementary material for an overview of the studies included.

Most food insecurity research was conducted in the state of West Bengal, where 9 studies were conducted, followed by 6 studies each in Maharashtra and the union territory of Delhi (see Fig. ​ Fig.2). 2 ). India consists of 28 states and 8 union territories; this review found research from 17 states and five union territories, as well as four nationwide studies showing good coverage across the country.

Distribution of studies exploring food insecurity in India

Measuring Food Insecurity

All studies included in this review purported to measure food insecurity directly, with the main aim of the majority ( n  = 45, 85%) of articles to determine the prevalence of food insecurity. These articles employed a range of measurement tools to achieve this aim. The most common way to measure food insecurity was via the Household Food Insecurity Access Scale (HFIAS) which was employed in 17 studies. The second most common method employed to measure food insecurity was via the Household Food Security Survey Module (HFSSM), employed in 13 studies. Other measures of food insecurity include the Food Insecurity Experience Scale (FIES), used in three studies, the Comprehensive Nutrition Survey in Maharashtra used in two studies, and the Radimer/Cornell used in one study. The remaining 17 studies used a proxy measure, either one devised by the authors or by using data from the India National Sample Survey (NSS). See Table ​ Table1 1 for an overview of these measurement tools.

Food insecurity measurement tools

The prevalence of food insecurity in these studies ranged from 8.7 to 99%; 13 studies stated that they measured food insecurity but did not report food insecurity results. The most common way for food insecurity to be measured in India was through employing Household Food Insecurity Access Scale (HFIAS). This experiential scale was designed to be used cross-culturally and consists of nine questions, with frequency questions asked if participants experience the condition. Responses to these questions are scored so that “never” receives a score of 0, “rarely” is scored 1, “sometimes” is scored 2, and “often” is scored 3, so that when summed, the lowest possible score is 0 and the highest is 27. A higher score represents greater food insecurity, with continuous scores typically divided into four categories, representing food-secure and mildly, moderately, and severely food-insecure households according to the scheme recommended by the HFIAS Indicator Guide [ 21 ]. The scale is based on a household’s experience of problems regarding access to food and represents three aspects of food insecurity found to be universal across cultures [ 22 – 24 ]. This scale measures feelings of uncertainty or anxiety about household food supplies, perceptions that household food is of insufficient quality, and insufficient food intake [ 21 ]. The questions asked in the HFIAS allow households to assign a score along a continuum of severity, from food secure to food insecure. Food insecurity measured via the HFIAS ranged from 77.2% in a population of 250 women who resided in an urban area in South Delhi [ 25 ] to 8.7% in Indian children [ 26 ].

The second most common measurement tool identified in this search is the US Household Food Security Survey Module (HFSSM). This tool was developed to measure whether households have enough food or money to meet basic food needs and what their behavioral and subjective responses to that condition were [ 27 ]. The HFSSM module consists of a set of 18 items, 8 of which are specific to households with children. It captures four types of household food insecurity experiences: (1) uncertainty and worry, (2) inadequate food quality, and insufficient food quantity for (3) adults and (4) children [ 28 ]. It is available in an 18-item and 6-item forms and allows households to be assigned a category of food insecurity: high food security, marginal food insecurity, low food insecurity, and very low food insecurity. In accordance with the method proposed by Coleman-Jensen et al. [ 29 ], food security scores are combined to create one measure for the level of food security for a household. Food security status is determined by the number of food-insecure conditions and behaviors that the household reports. Households are classified as food secure if they report fewer than two food-insecure conditions. They are classified as food insecure if they report three or more food-insecure conditions, or two or more food-insecure conditions if they have children. Food-insecure households are further classified as having either low food security if they report between three and five food-insecure conditions (or three and seven if they have children), or very low food security if they have six or more food-insecurity conditions (eight if they have children). Studies that employed the HFSSM reported food insecurity ranging from 15.4 [ 30 – 32 ] to over 80% of study participants [ 33 ]. The HFSSM is a commonly used measure of food insecurity and can be used in several valid forms. Studies included in this review used the 4-, 6-, and 18-item versions of the HFSSM.

The Food Insecurity Experience Scale (FIES) module was used by three studies included in this review. The FIES questions refer to the experiences of the individual or household. This scale was created by the Food and Agriculture Organization of the United Nations (FAO) and has been tested for use globally [ 28 ]. The questions focus on self-reported food-related behaviors and experiences associated with increasing difficulties in accessing food due to resource constraints. The FIES allows for the calibration of other measures, including the HFIAS and the HSSM with the FIES against a standard reference scale allowing for comparability of the estimated prevalence rates of food insecurity [ 34 ], as well as a raw score that can be used by authors as a way to create discrete categories of food insecurity severity [ 35 ]. The three studies that employed the FIES all reported food insecurity within a range of 66–77%, despite different population groups, locations, and sample sizes.

One study employed the Radimer/Cornell scale, a widely used and validated scale [ 36 ]. The scale includes ten items that relate to food anxiety and the quantity and quality of food available. The instrument allows for the categorization of households into four categories of food insecurity: food security, household food insecurity, individual food insecurity, and child hunger.

The Comprehensive National Nutrition Survey (CNNS) was used in two studies. It is a state-specific (Maharashtra) nutrition survey with a focus on infants and children under two and their mothers. The CNSM measured household food security using nine questions [ 37 ]. The questions capture experiences of uncertainty or anxiety over food, insufficient quality, insufficient quantity, and reductions in food intake [ 38 ]. Households are categorized as food secure, mildly food insecure, moderately food insecure, or severely food insecure.

The National Sample Survey (NSS) organization conducts nationwide household consumer expenditure surveys at regular intervals in “rounds,” typically 1 year. These surveys are conducted through interviews with a representative sample of households [ 20 ]. This survey includes only one question about household daily access to food [ 39 ], and while it does provide a method for estimating food insecurity in India, it assumes that financial access equates to physical access to available food; as such, this survey is unlikely to be able to comprehensively capture the intensity of household food insecurity in India [ 40 ]. Four studies employed the NSS. Given that these studies did not specifically collect food insecurity data, the use of the NSS has been considered a proxy indicator here as it generally reflects the measurement of food availability or acquisition rather than food insecurity per se.

Other proxy measures were commonly used. The variety of proxy measures included information on calorie intake, purchasing power, the quantity of food consumed, and agricultural productivity. These proxy measures provide only a partial, usually indirect, measure of food insecurity [ 41 ]. There are also challenges with these measures, as the relationship between food and caloric quantity and household food security is unpredictable [ 42 ]. For example, in a study of households in Gujarat, Sujoy [ 43 ] found that around 85% of households are food insecure at some point in a typical year. This study employed a range of measures to explore the experiences of hunger and food insecurity and the strategies employed by these population groups to mitigate hunger. Exploring the food insecurity experiences of farmers in Bihar, Sajjad and Nasreen [ 44 ] found that 75% of households had very low food security. While not using a standard measure, Sajjad and Nasreen [ 44 ] interviewed households alongside interviews with government officials, food production, food costs, and food acquisition to form an index of food security that could be applied at the household level. A study by George and Daga [ 45 ] using calorie consumption as a proxy for food security identified 57% of participants were food insecure, with the suggestion that income and family size play a role in food security among children. Of the 17 studies that employed a proxy measure of food insecurity, 10 provided no indication of the level of food security in their results.

Population Groups Under Investigation

Studies identified in this review included a variety of population groups. Most studies ( n  = 30) focused on food insecurity at the household level; half of these studies employed one of the standard food insecurity measurement tools, while the other half relied on proxy measures.

Fourteen studies focused specifically on young children, and one on teenagers. These studies used a variety of methods to determine food insecurity among this population, with rates of food insecurity shown to range from 8.7 [ 26 ] to 80.3% [ 33 ]; within this range, most studies reported that food insecurity among children was in the range of 40 to 60%. Interestingly, while the study conducted by Humphries [ 26 ] reported lower levels of child food insecurity (8.7%) than the other studies included in this review, other findings of this study were consistent with other research reviewed. Across all studies that explored food insecurity among children and teenagers, findings suggest problematic infant and young child feeding practices, caregiving, and hygiene practices, with many studies reporting impaired growth in children and teenagers due to these practices.

Seven studies focused specifically on the experiences of women or used the experiences of women as an indicator of food insecurity in their households. All of these studies employed one of the standard measures of food insecurity, with food insecurity in these studies ranging from 32 [ 3 ] to 77.9% [ 46 ]. These studies identified a range of health outcomes related to food insecurity and hunger. For example, in a study of mothers of children under the age of 5, Das and Krishna [ 47 ] found that two-thirds of households were food insecure and that younger mothers were more likely to be food insecure, with the children of these mothers more likely to be underweight and stunted. Among mothers in a study by Chyne et al. [ 48 ], those who had low literacy levels, low income, and large family size were more likely to be food insecure, with many of the children of these mothers being vitamin A deficient, anemic, stunted, and/or wasted. This is consistent with the work of Chatterjee et al. [ 49 ] who found that food insecurity among women was associated with low income and a range of socioeconomic measures including education, employment, and relationship status.

Thirteen studies were conducted in slums. Four of these studies were conducted in slums in Delhi, finding that food insecurity among slum populations ranges between 12% among children aged 1–2 years [ 50 ] and 77% in households more broadly [ 25 ]. Three studies were located in slums in Kolkata, all conducted by Maitra and colleagues [ 30 – 32 ]. These studies found food insecurity to be 15.4%, finding that low income, household composition, and education are all predictors of household food insecurity. The remaining studies were conducted in slums in Jaipur [ 51 ], Mumbai [ 49 ], Varanasi [ 52 ], Vellore [ 53 ], and West Bengal [ 33 , 54 ]. Slums are an important setting for an exploration of food insecurity, especially in India, where 25% of the urban population resides in slums or slum-like settings. People living in slums have been found to have poorer quality of life, are generally lower income, and have lower educational attainment than non-slum-dwelling populations—all factors that are known to contribute to food insecurity [ 49 ].

Five studies explored food insecurity among people with an underlying health condition. Four of these explored food insecurity among people living with HIV/AIDS [ 55 – 58 ]. These studies found that food insecurity ranged from 16 to 99% with people who are food insecure and also living with HIV/AIDS more likely to experience depression and a lower quality of life [ 57 ] and that low income [ 58 ] and low education [ 55 ] are contributing factors to food insecurity, while ownership of a pressure cooker was found to be protective against food insecurity [ 56 ]. Finally, one study explored the experiences of food insecurity among people with tuberculosis [ 59 ]. This study found that around 34% of study participants were food insecure, with low income and employment being associated with food insecurity status.

India has seen massive growth and economic change over the past 2 decades; however, this increase in financial wealth has had little impact on food insecurity and population nutrition [ 60 ]. While India has increased production and, overall, the availability of food has increased [ 61 ], these increases have not yet translated into gains for the general population. Overall, India is seeing increasing income inequality which is having a negative impact on health [ 62 ]. As a result of the disconnect between economic growth and positive health outcomes, there has been an increased interest in food insecurity and nutrition in India over the past two decades, resulting in research that seeks to measure food insecurity.

The main finding of this study is the variation in the methods for the assessment of food insecurity prevalence in India and the reliance on cross-sectional studies to elicit food insecurity data. This may be explained by the fact that food security is notoriously difficult to measure. Initial descriptions of food insecurity were conceptualized through the lens of famine [ 63 ], meaning that solutions were often confined to domestic agriculture [ 41 ]. However, in an increasingly globalized world where countries easily sell and buy goods from each other, it is now important to consider food security in a holistic manner, incorporating the whole definition of food insecurity. By considering the six main dimensions of food security: availability, access, utilization, stability, agency, and sustainability, we can better understand the experiences and drivers of food security. However, as this review has found, few studies measure more than one dimension.

Studies included in this review utilized scales that focused on household food access or availability and were assessed through experience-based scales. Experiential food insecurity scales have been used since the 1990s [ 64 ], first used in the USA and later adopted for use in low- and middle-income countries [ 21 , 65 ]. Experiential measures are based on the notion that food insecurity is associated with a set of knowable and predictable characteristics that can be assessed and quantified [ 17 , 21 ]. This assumes that households will attempt to mitigate food insecurity through a generalizable or standard pattern of responses [ 17 , 22 ]. Strategies include reducing expenditure on education expenses [ 66 ], selling assets or seeking increased employment [ 67 ], and skipping meals or limiting the sizes of meals [ 68 ]. Measures of food insecurity that are based on experience seek to capture some of these strategies and actions, and compared to other metrics, such as agriculture production, caloric intake, or anthropometric measures, they enable direct measurement of the prevalence and severity of the extent of household food insecurity, as well as the perception of the quality of their diets [ 31 ].

Given the wide variety of measurement tools used, it is difficult to present a comprehensive understanding of food insecurity in India. What is clear is that some households are experiencing food insecurity but are not hungry, while others are both hungry and food insecure. Finding a way to identify and measure at-risk households and intervene to reduce hunger is essential to closing the economic-income gap in India. However, without a measure that can be used consistently across the country that takes into consideration each of the dimensions of food security and the diversity within the Indian population, this will not be possible.

Limitations

There are some limitations to this review that should also be acknowledged. While every attempt was made to ensure this review was comprehensive, additional articles may have been missed, particularly if articles were written in a language other than English. However, given that this is the first review of its kind, with the inclusion of several databases and broad key terms, the authors are confident that there is little information that is not presented here. The articles presented in this review are largely cross-sectional, and as such, the quality of the studies means that the conclusions drawn by their authors are limited to the study population and are not widely generalizable. The cross-sectional nature of many of the studies limited the potential impact of quality assessment; as such, no quality assessment was conducted. This is a limitation of both this review and the studies included, and in general, a reflection on the rigor with which food security research has been conducted in these settings. Given the variety of approaches taken to measure food insecurity as found in this review, there are challenges in comparing the outcomes of different studies; as such, this review has not sought to present a meta-analysis. If, in the future, there can be some consistency in the use of measurement tools by researchers and agencies, a meta-analysis may be appropriate. The authors do not feel this should invalidate these findings at this time.

An Indian-specific food security measure needs to be urgently developed and implemented so that food insecurity data can more accurately and consistently be collected and contrasted for the purpose of developing suitable responses to food insecurity. Considering India’s widespread malnutrition and high prevalence of food insecurity, future work should prioritize the development of such a tool in addressing nutrition-related public health in India.

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All authors have worked in paid and unpaid roles with not-for-profit food security organizations or with organizations that focus on pregnancy and/or nutrition outcomes. No other COI to declare.

This article does not contain any studies with human or animal subjects performed by any of the authors.

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Open Access

Peer-reviewed

Research Article

Sustainable food security in India—Domestic production and macronutrient availability

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom

Contributed equally to this work with: David Reay, Peter Higgins

Roles Conceptualization, Supervision, Writing – review & editing

Affiliation Moray House School of Education, University of Edinburgh, Edinburgh, United Kingdom

• Hannah Ritchie, 
• David Reay, 
• Peter Higgins

• Published: March 23, 2018
• https://doi.org/10.1371/journal.pone.0193766
• Reader Comments

India has been perceived as a development enigma: Recent rates of economic growth have not been matched by similar rates in health and nutritional improvements. To meet the second Sustainable Development Goal (SDG2) of achieving zero hunger by 2030, India faces a substantial challenge in meeting basic nutritional needs in addition to addressing population, environmental and dietary pressures. Here we have mapped—for the first time—the Indian food system from crop production to household-level availability across three key macronutrients categories of ‘calories’, ‘digestible protein’ and ‘fat’. To better understand the potential of reduced food chain losses and improved crop yields to close future food deficits, scenario analysis was conducted to 2030 and 2050. Under India’s current self-sufficiency model, our analysis indicates severe shortfalls in availability of all macronutrients across a large proportion (>60%) of the Indian population. The extent of projected shortfalls continues to grow such that, even in ambitious waste reduction and yield scenarios, enhanced domestic production alone will be inadequate in closing the nutrition supply gap. We suggest that to meet SDG2 India will need to take a combined approach of optimising domestic production and increasing its participation in global trade.

Citation: Ritchie H, Reay D, Higgins P (2018) Sustainable food security in India—Domestic production and macronutrient availability. PLoS ONE 13(3): e0193766. https://doi.org/10.1371/journal.pone.0193766

Editor: David A. Lightfoot, College of Agricultural Sciences, UNITED STATES

Received: September 13, 2017; Accepted: February 17, 2018; Published: March 23, 2018

Copyright: © 2018 Ritchie 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, or can be accessed at the UN FAO databases through the following URL: http://www.fao.org/faostat/en/#home .

Funding: The authors received funding from the Natural Environment Research Council (NERC) as part of its E3 DTP programme.

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

Introduction

In 2015, the United Nations (UN) committed to achieving zero hunger by 2030 as the second of the Sustainable Development Goals (SDGs). An important element of this goal is to end all forms of malnutrition, including agreed targets on childhood stunting and wasting. This represents an important progression beyond the Millennium Development Goals (MDGs), where food security was defined and measured solely on the basis of basic energy requirements (caloric intake), and prevalence of underweight children [ 1 ]. This new commitment has significant implications for the focus of research and policy decisions; it requires a broadening of scope beyond the traditional analysis of energy intake, and inclusion of all nutrients necessary for adequate nourishment.

India offers a potentially unique example in the development of models and mechanisms by which nutritional needs can be addressed sustainably. In 2016, India ranked 97 out of 118 on the Global Hunger Index (GHI)—this rates nations’ nutritional status based on indicators of undernourishment, child wasting, stunting and mortality [ 2 ]. Despite ranking above some of the world’s poorest nations, India’s reduction in malnourishment has been slow relative to its recent strong economic growth and puts it behind poorer neighbouring countries [ 3 ]; India has fallen from 80 th to 97 th since 2000.

India’s nutritional problems are extensive. In 2016, 38.7% of children under five were defined as ‘stunted’ (of below average height) [ 2 ], a strong indicator of chronic malnourishment in children and pregnant women, and a largely irreversible condition leading to reduced physical and mental development [ 4 ]. Malnourishment within the adult population is also severe, with approximately 15% of the total population defined as malnourished. The issue of malnutrition in India is complex, and determined by a combination of dietary intake and diversity, disease burden (intensified by poor sanitation and hygiene standards), and female empowerment and education [ 5 ]. Improvements in dietary intake alone will therefore by insufficient to eliminate malnutrition, however it forms an integral component alongside progress in other social and health indicators—particularly sanitation. Quantification of India’s micronutrient and amino acid profiles, and recommendations for addressing these deficiencies have been completed as a follow-up paper (Ritchie et al. in submission) to provide a more holistic overview of its nutritional position.

India’s nutritional and health challenges are likely to be compounded in the coming decades through population growth and resource pressures. Its current population of 1.26 billion is projected to increase to 1.6 billion by 2050, overtaking China as the world’s most populous nation [ 6 ]. India has also been highlighted as one of the most risk-prone nations for climate change impacts, water scarcity, and declining soil fertility through land degradation [ 7 ].

A number of studies have focused specifically on Indian food intake and malnutrition issues from survey assessments at the household level [ 8 ]. The emphasis within India’s agricultural policy and assessment of its success has traditionally been on energy (caloric) intake [ 9 ]. Since the Green Revolution in the 1970s, agricultural policies have been oriented towards a rapid increase in the production of high-yielding cereal crops with a focus to meet the basic calorific needs of a growing population. India has attempted to reach self-sufficiency predominantly through political and investment orientation towards wheat and rice varieties [ 10 ]. While production of staple crops has increased significantly, India’s agricultural policy focus on cereal production raises a key challenge in simultaneously meeting nutritional needs in caloric, high-quality protein and fat intakes. Few studies have addressed the system-wide balance between supply and demand of the three key macronutrients—calories, protein and fat; nor have they assessed the importance of protein quality through digestibility and amino acid scoring. This assessment is particularly significant for India as a result of its extensive and complex malnutrition issues. Whether India is capable of meeting these macronutrient needs in the future through domestic production improvements alone is of prime importance for study, as a result of its growing population and policy orientation towards self-sufficiency.

Improving the availability and access to food at the consumer level requires an understanding of how food is created and lost through its various pathways across the full agricultural supply chain. Here, for the first time, we have attempted to capture this high-level outlook from crop harvesting to residual food availability across the three macronutrient categories.

Mapping the current Indian food system

The Indian food system was mapped from crop production through to per capita food supply using FAO Food Balance Sheets (FBS) from its FAOstats databases [ 11 ]. FBS provide quantitative data (by mass) on production of food items and primary commodities, and their utilisations throughout the food supply chain. Such data are available at national, regional and global levels. Food Balance Sheet data for 2011 have been used, these being from the latest full data-set available. Some aspects of FBS data are available for the years 2012 and 2013, however such data are not complete across all commodities and value chain stages at the time of writing.

Food Balance Sheets provide mass quantities across the following stages of the supply chain: crop production, exports, imports, stock variation, re-sown produce, animal feed, other non-food uses, and food supplied (as kg per capita per year). Data on all key food items and commodities across all food groups (cereals; roots and tubers; oilseeds and pulses; fruit and vegetables; fish and seafood; and meat and dairy) are included within these balances.

While there are uncertainties in FAO data (see Supplementary Information for further discussion on FAO data limitations), FBS provide the only complete dataset available for full commodity chain analysis. Therefore, while not perfect, they provide an invaluable high-level outlook of relative contribution of each stage in the food production and distribution system. As shown in this study (see Results section below), a top-down model using FAO FBS has a discrepancy of <10% with national nutrition survey results at the household level.

FBS do not provide food loss and waste figures by stage in the supply chain. To maintain consistency with FAO literature, food loss figures have therefore been calculated based on South Asian regional percentages within FAO publications [ 12 ]. These percentage figures break food losses down across seven commodity groups and five supply chain stages (agricultural production, postharvest handling and storage, processing and packaging, distribution and consumption). The applied percentage values by commodity type and supply chain stage are provided in S1 Table .

In order to calculate the total nutritional value at each supply chain stage, commodity mass quantities were multiplied by FAO macronutrient nutritional factors [ 11 ]. In this analysis, energy content (kilocalories), protein, and fat supply were analysed. Protein quality is a key concern for India in particular as a result of its largely grain-based diet, with grains tending to have poorer digestibility and amino acid (AA) profiles than animal-based products and plant-based legume alternatives [ 13 ]. To best quantify limitations in protein quality in the Indian diet, protein intakes have therefore been corrected for digestibility using FAO digestibility values [ 14 ].

For consistency, and to provide a better understanding of the food system down to the individual supply level, all metrics have been normalised to average per person per day (pppd) availability using UN population figures and prospects data [ 6 ]. Whilst this provides an average per capita availability value, it does not account for variability in actual macronutrient supply within the population. To help adjust for this, we have also estimated the assumed distribution of supply of each macronutrient using the FAO’s preferred log-normal distribution and India-specific coefficient variation (CV) factor of 0.26 [ 15 ]. Whilst we recognise that food requirements vary between demographics based on age, gender and activity levels, the normalisation of food units to average per capita supply levels is essential in providing relatable measures of food losses within the system, and its measure relative to demographically-weighted average nutritional requirements (as described below) is appropriate in providing an estimation of the risk of malnourishment.

Estimated macronutrient supply has then been compared to recommended intake values. The FAO defines the “Average Daily Energy Requirement” (ADER)—for India’s demographic specifically—as 2269kcal pppd; ADER is defined as the average caloric intake necessary to maintain a healthy weight based on the demographics, occupation, and activity levels of any given population [ 16 ]. Protein requirements can vary between similar individuals; recommended daily amounts (RDA) are therefore typically given as two standard deviations (SD) above the average requirement to provide a safety margin, which some individuals would be at risk of falling below. The World Health Organization (WHO) define a ‘safe’ (recommended) intake in adults of 0.83 grams per kilogram per day (g/kg/d) of body mass for proteins with a digestibility score of 1.0 [ 17 ]. The average vegetarian Indian diet contains lower intakes of animal-based complete proteins; the Indian Institute of Nutrition therefore recommends a higher intake of 1 g/kg/d of total protein for Indians to ensure requirements of high-quality protein are met [ 18 ]. This is equivalent to 55 and 60 grams of protein per day in average adult females and males, respectively based on mean body weight [ 19 ]. Since our analysis attempts to correct for protein digestibility, WHO’s lower safe intake of 0.83g/kg/d would reduce to an equivalent of 50 grams of high-quality protein per day for an average 60 kilogram individual. Consequently in this study we have adopted this RDA value of 50 gpppd.

Dietary fat intake plays a key dietary role in the absorption of essential micronutrients. Several vital vitamins, including vitamin A, D, E and K are fat-soluble—insufficient intake can therefore result in poor micronutrient absorption and utilisation [ 20 ]. Inadequate fat intake can therefore exacerbate the widespread ‘hidden hunger’ (micronutrient deficiency) challenge in India [ 21 ] through poor nutrient absorption. However, daily requirements for fatty acids are less straightforward to determine, relative to energy or protein—there is no widely-agreed figure for total fat requirements for adequate nutrition [ 22 ]. The resolution of food balance sheet data does not allow us to adequately quantity the availability to the level of specific fatty acids. As a result, although we have mapped pathways of total fat availability through the food system in a similar manner to energy and protein, we have not here attempted to quantity the prevalence of potential insufficiency at the household level.

Mapping potential near-term and long-term scenarios

Our initial analysis identified two mechanisms potentially crucial in increasing food availability at the household level: reduction of harvesting, postharvest and distribution losses; and improvements in crop yields. Medium-term (through to 2030) and long-term (2050) scenarios have therefore been mapped based on use of these mechanisms. It should be noted that these scenarios are focused on domestic supply-side measures to enhance food availability as opposed to demand drivers related to consumer preferences. A summary of assumptions used in each scenario in this analysis is provided in S2 Table .

A 2030 baseline scenario (assuming yields stagnate and population growth continues in line with UN projections) and three alternative scenarios to 2030 were analysed:

Scenario 1 (halving food supply chain losses): it was assumed that a significant shift in post-harvest management practices, appropriate refrigeration, and efficient distribution allowed for a halving of food loss percentages at the production, postharvest, processing and distribution stages of the supply chain. This would make its relative losses more in line with those of more developed nations [ 12 ]. In this scenario consumption (household) waste was assumed to remain constant.

Scenario 2 (achieving 50% of attainable yield (AY) across all key crops): the halving of food chain losses in scenario 1 was assumed. In addition, it was assumed that all key crops managed to achieve 50% AY through better agricultural management, irrigation and fertiliser practices. ‘Attainable yield’ is defined as the yield achieved with best management practices including pest, nutrient (i.e. nutrients are not limiting) and water management.

Scenario 3 (achieving 75% AY across all key crops): assumptions as in scenario 2 except an attainment of 75%, rather than 50% AY, has been assumed through crop yield improvements.

Long-term (through to 2050) scenarios were as follows:

Scenario 1 (halving food supply chain losses): the same assumption of halving food loss percentages at the production, postharvest, processing and distribution stages of the supply chain was applied in this scenario. This will require a significant shift in post-harvest management practices, appropriate refrigeration, and efficient distribution, hence 50% reduction represents a magnitude which is more likely to be achieved in this long-term scenario than in the near-term.

Scenario 2 (achieving 75% AY across all key crops): the same assumption of a closure of the yield gap to 75% AY across all crop types, as in the near-term scenario 3, was applied.

Scenario 3 (achieving 90% AY across all key crops): it was assumed that all crop types managed to achieve closure of the yield gap to 90% AY.

To correct for 2030 and 2050 population estimates, all metrics were re-normalised to ‘per person per day’ (pppd) based on a projected Indian population estimate from UN prospects medium fertility scenarios [ 6 ].

To best demonstrate the food production potential of current agricultural support mechanisms, such as governmental policy and subsidy (which largely determine crop choices), the relative allocation of crop production was assumed constant. It was also assumed that production increases were achieved through agricultural intensification alone; this assumption was based on FAOstats data which has shown no increase in agricultural land area over the past decade, indicating a stagnation in agricultural extensification ( http://faostat.fao.org/beta/en/#home ).

Crop yield increases were derived based on closure of current farm yields (FY) to reported attainable yields (AY). FY is defined as the average on-farm yield achieved by farmers within a given region, and AY is defined as the economically attainable (optimal) yield which could be achieved if best practices in water and pest management, fertiliser application and technologies are utilised in non-nutrient limiting conditions). Estimates of crop yield improvements were based on given percentage realisations of maximum attainable yields (AY) attained from published Indian crop-specific figures [ 23 ]. These data are available across all key crop types. Baseline and AY values are provided in S3 Table .

Significant improvements in yield would predominantly be achieved through improved nutrient and water management. In the present study, scenarios were mapped based on achievement of 50% and 75% AY in the near-term. Fifty percent AY should be technically feasible by 2030: many crops have already reached these values, and those which have yet to do so, typically fall short by 3–5% (see S3 Table for baseline, and AY values). Attainment of 75% AY would be highly ambitious in the near-term, representing an increase of >20% in yield. However, 75% AY and higher may be feasible in the long-term if significant investment in agricultural management and best practice were to be realised in this sector.

Our scenarios to 2050 are therefore modelled on the basis of closure of the yield gap to 75% and 90% AY. To assess whether these estimates were realistic, necessary growth rates were cross-checked based on historical yield growth rates in India. Discussion on this comparison and the suitability of attainable yield valuables utilised in this study are available in the Supplementary Discussion.

Climate change impacts on crop yields remain highly uncertain; the importance of temperature thresholds in overall crop tolerance makes yield impacts highly dependent on GHG emission scenarios. This makes it challenging to accurately quantify 2050 climate impacts. As such, we applied average percentage changes in yields of Indian staple crops based on literature review [ 24 ] of field-based observations and climate model results. The studies utilised presented results for a doubling of atmospheric CO 2 from pre-industrial levels. This approximates to a business-as-usual (BAU) scenario for 2050 [ 25 ]. The yield-climate factors applied in this analysis are provided in S4 Table .

It is projected that, through economic growth and shifts in dietary preferences, meat and dairy demand in India will continue to increase through to 2050. It has been assumed that per capita demand in 2050 is in line with FAO projections; this represents an increase in meat from 3.1kg per person per year (2007) to 18.3kg in 2050, and an increase in milk and dairy from 67kg to 110kg per person per year [ 26 ]. We here assume that this increase in livestock production has been met through increased production of crop-based animal feed rather than pasture. The change in macronutrient demand for animal feed was calculated based on energy and protein conversion efficiency factors for dominant livestock types (beef cattle, dairy cattle, ruminants and poultry) [ 27 ].

Our analysis assumes that the per person allocation of crops for resowing and non-food uses, and the relative allocation of land for respective crop selection, is the same as in the initial baseline (2011) analysis.

Current food system pathways

The pathways of macronutrients from crop production to residual food availability are shown for calories, digestible protein and fat in Fig 1A–1C . Across all macronutrients, the relative magnitude of exports, imports and stock variation is small, and approximately balance as inputs and outputs to the food system. This result is in line with India’s orientation towards meeting food demand through self-sufficiency agricultural policies [ 28 , 29 ]. This study’s scenarios are therefore designed to assess whether this same emphasis on self-sufficiency in food supply through to 2050 could be achieved through waste reduction and crop yield improvements alone.

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Food pathways in (a) calories; (b) digestible protein; and (c) fat from crop production to residual food availability, normalised to average per capita levels assuming equal distribution. Red bars (negative numbers) indicate food system losses; blue bars indicate system inputs; green bars indicate meat and dairy production; and grey bars indicate macronutrient availability at intermediate stages of the chain.

https://doi.org/10.1371/journal.pone.0193766.g001

In 2011, India produced 3159kcal, 72g of digestible protein, and 86g of fat per person per day (pppd) ( Fig 1A–1C ). Across the system, this resulted in average food availability of 2039kcal, 48g digestible protein, and 49g fat pppd; this represents a loss across the food supply system of 35%, 33%, and 43% in calories, digestible protein, and fat respectively.

Our top-down supply model has been cross-checked against India’s National Sample Survey (NSS) data—this reports nutritional intakes bi-annually measured through national household surveys. In its 68 th Round (2011–12) report, the NSS reported average daily intakes of 2206kcal and 2233kcal in urban and rural areas, respectively; 60g of protein in both demographics; and 58g (urban) and 46g (rural) of fat [ 30 ]. Our top-down analysis therefore suggests slightly lower caloric availability than NSS intake figures (but with a discrepancy of <10%); and strong correlation regarding fat intake. Since NSS data reports total protein and take no account of quality or digestibility, our results of digestible protein are not directly comparable. However, with digestibility scores removed, our analysis suggests a total average protein availability of 57g pppd—within 5% of NSS intake results.

Despite the acknowledged uncertainties in FAO FBS datasets (see Supplementary discussion), the strong correlation (within 5–10%) between our top-down supply model and reported household intakes (bottom-up approach) gives confidence in the use of FBS data for high-level food chain analyses such as attempted here.

The largest sources of loss identified in the Indian food system for calories and protein lie in the agricultural production and post-harvest waste stages of the chain, with lower but significant losses in processing and distribution. Consumption-phase losses are comparatively small. Higher losses of fat occur predominantly due to the allocation of oilseed crops for non-food uses; this is in contrast to digestible protein where losses to competing non-food uses are negligible.

In contrast to the average global food supply system, the conversion of crop-based animal feed to meat and dairy produce in India appears comparatively efficient, with an input-output ratio close to one for calories and protein, and an apparent small production of fats [ 31 ]. It is one of the few agricultural systems in the world where the majority of livestock feed demand is met through crop residues, byproducts and pasture lands—its lactovegetarian preferences tend to favour pasture-fed dairy cattle over grain-fed livestock such as poultry (ibid).

Average per capita supply across all macronutrients falls below average per capita minimum requirements. The magnitude of this issue in India emerges via the population-intake distributions. With extension of average macronutrient availability to availability across the population distribution (using a log-normal distribution with CV of 0.26), 66% (826 million) and 56% (703 million) of the population are at risk of falling below recommended energy and protein requirements, respectively.

Potential future pathways

Scenario results for 2030..

Results from scenario analyses for potential food waste reduction and crop yield improvements are summarised in Table 1 . Note that we have assumed no change in income/dietary inequalities, hence the CV in distribution has remained constant.

https://doi.org/10.1371/journal.pone.0193766.t001

Under all scenarios, waste or yield improvements fail to keep pace with population growth through to 2030; average per capita caloric, digestible protein and fat availability all fall below the 2011 baseline. Under current levels of dietary inequality, distribution of availability highlights even greater potential malnourishment. The majority (>75%) of the population are at risk of falling below requirements in energy and protein availability in all scenarios. This represents severe malnutrition across India in 2030, even in the case of significant and ambitious yield and efficiency improvements.

Under these scenarios, India would fall far short of reaching the SDG2 target of Zero Hunger by 2030.

Scenario results for 2050.

India’s anticipated population growth, in addition to potential impacts of climate change on crop yields, could have severe implications on household macronutrient supply by 2050. Our 2050 baseline scenario demonstrates these potential impacts, assuming gains in crop yields were to stagnate at current levels. The full supply chain pathways are shown in Fig 2A–2C . Even at the top level of the supply chain (crop production phase) mean provision per person would fall below average requirements in all macronutrients (2198kcal, 49g protein, and 60g fat per person). Although reducing food system losses plays an important role in improving availability at the household level, this result highlights the necessity of also achieving substantial crop yield improvements at the top of the supply chain.

Food pathways in (a) calories; (b) digestible protein; and (c) fat from crop production to residual food availability, normalised to average per capita levels assuming equal distribution under 2050 baseline conditions. Red bars (negative numbers) indicate food system losses; blue bars indicate system inputs; green bars indicate meat and dairy production; and grey bars indicate macronutrient availability at intermediate stages of the chain.

https://doi.org/10.1371/journal.pone.0193766.g002

How these variables impact on availability at the household level in our 2050 baseline, and three scenarios is detailed in Table 2 , with baseline distributions provided in Supplementary Fig 1A–1C . As shown, even in the case of scenario 1 (halving of supply chain loss and waste), and scenario 2 (increase to 75% of AY), in 2050 greater than 80% of the population would potentially fall below average requirements in energy and protein. Only in the case of significant yield increases to 90% AY (scenario 3) would projected levels of malnourishment approach current levels. This would still leave 62% and 56% of the population at risk of falling below recommended caloric and protein requirements, respectively.

https://doi.org/10.1371/journal.pone.0193766.t002

Our analysis utilised a framework for evaluation of the whole food system (from crop production through to residual food availability) by normalising to consistent and relatively simplistic metrics (per person per day). This holistic approach is critical for identifying levers within the food system which can be targeted for improvements in food security and efficiency of supply. The basic framework is replicable and could therefore be adapted for analysis of any dietary component (for example, micronutrients or amino acids and at a range of scales (global, regional, or national). This allows for similar analyses to be carried out for any nation, potentially allowing for improved understanding of hotspots in the food system and opportunities for improved efficiency. As such, it could then allow national food strategies to focus on components which are likely to maximise improvements.

Overall, our analyses indicate weaknesses in India’s current reliance on domestic food production. Further calculation, based on FAO FBS, make this explicit: in 2011 India’s population was 17.8% of the global total, yet produced only 10.8%, 9%, and 11.8% of the world’s total calories, digestible protein and fat respectively. Based on calculations using FAOstats global crop production data and nutritional composition factors, in 2011 world crop production totalled 1.34x10 16 kcal; 3.62x10 14 g digestible protein; and 3.33x10 14 g fat. 2011 Indian production amounted to 1.44x10 15 kcal; 3.27x10 13 g digestible protein; and 3.93x10 13 g fat. Even in a highly efficient food system, self-sufficiency is impossible to achieve based on such production levels and the need to provide sufficient nourishment for all. Likewise, even if Indian population figures were to plateau, it is unlikely that domestic production alone would be sufficient to close the current food gap.

Current malnutrition levels—defined here as insufficient macronutrient availability—in India are already high. Sufficient nutrition requires adequate availability and intake of all three macronutrients. Impacts of insufficient protein and energy intake can often be difficult to decouple, and are often termed protein-energy malnourishment (PEM)—PEM has a number of negative consequences including reduced physical and mental development [ 32 ]; increased susceptibility to disease and infection; poorer recovery and increased mortality from disease; and lower productivity [ 33 ]. Our results indicate that India’s self-sufficiency model—a reliance on domestic crop yield increases and waste reduction strategies—will be insufficient to meet requirements across all three macronutrients. Levels of undersupply and consequent malnutrition would show a significant increase in both 2030 and 2050 scenarios.

This has important implications for forward planning to effectively address malnutrition. Policy incentives in Indian agriculture since the Green Revolution have predominantly been focused on achieving caloric food security through increased production of cereals (wheat and rice) [ 9 ]. This has resulted in a heavily carbohydrate-based diet (> 65–70% total energy intake [ 34 ]) which may be significantly lacking in adequate diversity for provision of other important nutrients [ 35 ]. Widespread lactovegetarian preferences have further reduced the scope for dietary diversity [ 36 ].

If trying to address caloric inadequacy alone, efforts to increase output of energy-dense crops (i.e. cereals, roots and tubers) may seem appropriate, and has largely been India’s focus to date [ 8 ]. Our analysis, however, strongly suggests the need to shift dietary composition away from reliance on carbohydrates towards a more diversified intake of protein and fats (with diversification also contributing to a reduction in micronutrient deficiency) [ 37 ]. Forward planning therefore needs to simultaneously address caloric inadequacy and malnourishment through balanced, increased supply and intake of high-quality proteins and fats.

Our examination of macronutrient supply in India indicates large inequalities in availability across the population. This is likely to be closely coupled to the high levels of income inequality and poverty which remain in India today [ 8 ]. Large inequalities in food supply and dietary intake will make it increasingly difficult for India to address its malnutrition challenges; our assessment of potential improvement scenarios highlight that, even in cases where average macronutrient supplies meet requirements, the high CV in distribution still leaves a large proportion of the total population at risk of malnourishment. Whilst the RDA values used in this analysis account for distribution in nutritional requirements of individuals, they do not account for the distribution in intake. To meet SDG2 (whereby all individuals’ requirements are met) at current levels of inequality, the national mean intake would therefore have to increase to 3600kcal pppd; 82g pppd digestible protein; and 105g pppd fat. This is well above current national pppd supply values, even if crop production-phase level were to be at the top of the food system.

It should be emphasised that this work is a largely computational, supply-driven analysis exploring the domestic capacity of India’s food. Our results are not intended to imply actual future scenarios of Indian malnutrition. Projections of acute food shortage implied within this analysis would be likely to drive market and policy interventions including enhanced trade, in addition to changes in consumer and producer responses. The interaction between supply and demand-side measures, commodity prices, trade, and governmental policy creates an important feedback loop for food pricing, affordability and production [ 38 ]. For example, the estimated reduction in per capita food supply and domestic food shortage would be expected to drive an increase in food prices [ 39 , 40 ]. Rising food prices (as are expected across a number of countries where food demand continues to grow [ 41 ]) create a number of producer and consumer impacts, including per capita food expenditure, reduced purchasing power for expensive commodities such as meat and dairy products [ 42 ], farmer incentives and agricultural investment. Analysis of the drivers of historical food price volatility and inflation in India suggests that both supply and demand-side factors (and the interaction between) play an important role [ 40 ].

The impact of feedbacks such as reduced meat and dairy demand (thereby reducing demands for feed, with further feedbacks on food supply and commodity prices) are not reflected within these scenarios, but will play an important role in determining food system dynamics. The impact of domestic food shortages, agricultural prices and balance within international markets is particularly pronounced in India where the agricultural sector accounts for the employment and income of a large percentage of the population [ 43 ]. Literature on the interactions between poverty, agriculture and food prices is extensive; many studies indicate that, since a large share of the world’s poor are rural, high food prices have a positive long-term impact on poverty reduction. However they have negative impacts on poverty and malnutrition in the short-term [ 39 , 44 – 48 ]. The lack of domestic capacity in India to meet the full nutritional needs (balancing caloric, protein and micronutrient requirements) of its population is likely to increase the demand for commodity imports. This in turn creates further feedbacks on domestic prices, farmer income and inevitably poverty reduction [ 46 ]. Further work on the economic dimension to Indian food security—within the context of value chain potential and efficiency evaluations in this study—is therefore crucial to develop better understanding of their interactions and policy responses.

Overall, our results highlighted several key points:

• production quantities at the farm level are very low relative to global average production;
• low import and export values produce an approximately balanced trade model; this correlates with India’s self-sufficiency focused agricultural and food policies;
• harvesting, post-harvest and distribution losses in the supply chain form a large proportion of total food system inefficiencies;
• a moderate amount of energy and fat (but not protein) is allocated to non-food uses, although this is significantly less than global average non-food allocation;
• India’s caloric and protein losses in the conversion of edible crops to livestock are small due to the dominance of pasture-fed livestock such as dairy cattle. The large nutritional gains achieved through increased milk consumption in India suggest this may be a beneficial trade-off in agricultural land for provision of high-quality protein.

Our examination of the food supply chain in India identified harvesting, handling and storage losses, and top-level crop production to be the key intervention phases for improving food security. The approach not only adds value in the identification of ‘hotspots’ of wastage and inefficiency, but also allows for an understanding of the magnitude of change required to produce a certain food supply chain-wide result. Our analysis highlighted that, despite being an important mechanism for improving food security, even a 50% reduction in food loss/waste (a challenge that is achievable but would take significant economic, infrastructural and educational investment) alone would be largely insufficient in ensuring food security in India.

Increased production at the agricultural level must therefore be a focus for both near and long-term food security. The viability of achieving yields close to 75% AY in the near-term (to 2030), across the range of available crops, needs to be more closely considered. For several staple crops, a yield increase upwards of 30% and 50% would be required for attainment of 75% and 90% AY, respectively (see S2 Table ). The challenge in reaching close to 90% AY (i.e. almost maximum yield) is substantial; many developed countries have not yet reached such levels [ 23 ].

The potential resource limits and environmental implications needed to achieve such yields also need to be given consideration in order to optimise crop selection and mitigate negative impacts. The yield gap could predominantly be closed through improved water and nutrient management [ 23 ]. Depleting groundwater resources through agricultural irrigation in India raises key concerns over long-term water security [ 49 ][ 50 ], and whether water availability is likely to impose a resource limit on yield attainment. Improved yields through increased fertiliser application raise similar sustainability concerns; nitrous oxide (N 2 O) is a key source of greenhouse gas (GHG) emissions, a major source being microbially-mediated emissions as a result of nitrogen fertiliser application to agricultural soils [ 51 ]. There may therefore be a significant GHG penalty in closing the current yield gap.

It should be noted that this study has considered only yield improvements through traditional crop varieties. Genetic variation and modification of crop strains may offer further potential for yield increases, in addition to increased resilience to pests, disease and climatic impacts [ 52 ]. However, with the exception of Bt Cotton, genetically modified (GM) crop varieties are banned from commercial crop production [ 53 ]. Despite the introduction of GM field trials in recent years, they continue to face significant resistance across a range of stakeholder groups [ 54 ].

Our analyses for 2050 highlight severe food security challenges for India, even in scenarios which assume attainment of 90% AY for all crops. In addition to the hotspots identified for further focus to achieve near-term improvements, long-term strategies require increased consideration of the impact of potential climatic changes. India’s staple crops–wheat and rice—show particular vulnerability; in the near-term, CO 2 fertilisation may offer some positive yield impacts, however, simulated climate models suggest this effect is likely to be cancelled out if global mean temperature increase reaches a 3°C threshold in wheat (2°C for rice) [ 55 ]. This suggests negative climate impacts may only begin to arise from mid-century onwards. Failure to build capacity and agricultural resilience in the interim could result in severe food deficits should a 2°C or 3°C warming threshold be breached. Planning strategies should therefore not only aim to adapt to gradual near-term impacts of a changing climate, but importantly focus on capacity-building for a resilient food system in a warmer post-2050 world.

Our 2050 scenarios are based on assumptions which are sensitive to change; we have assumed BAU climatic-yield factors, and increased meat and dairy intakes in line with FAO projections. Both of these assumptions could change based on global GHG mitigation progress, and governmental or social interventions on meat consumption. In addition, it is recognised that some potential climatic impacts could be reduced through shifts in crop production regions and seasonal cropping patterns [ 24 ]. While such changes may marginally change the scale of the food supply and malnutrition challenge, the overall conclusions remain the same. Climatic and livestock impacts may serve to exacerbate the issue, however, India would continue to face a severe risk of domestic food shortages regardless of these additional pressures.

To deliver effective recommendations for addressing macronutrient undersupply and malnutrition, two key components need to be further explored. Firstly, there needs to be better understanding of optimal crop selections to maximise production and consumer supply of energy, digestible protein and fats alike. This has to be analysed with key resource and environmental constraints in mind to deliver a more optimal and sustainable domestic food system. This should include consideration of options outwith traditional domestic agricultural practice, such as genetic modification, industrial biotechnology and biofortification [ 56 , 57 ].

Secondly, India’s role within global food markets needs to be more closely assessed. To successfully address malnutrition, India will likely have to fill the gap between domestic production and food demand through increased imports. Food imports can have a significant impact on domestic prices, and the dominance of agriculture as a primary source of employment in India may be a negative influence on farmer livelihoods [ 9 ]; and further, a large increase in food imports could potentially reduce energy-protein intake for the poorest 30% of the population [ 46 ]. This means appropriate economic and social analysis must be carried out to try to optimise import quantities and products which will have minimal domestic impacts. The importance of reducing economic and dietary inequalities makes this even more crucial.

In order to ensure a resilient food system, such analyses and recommendations should be made alongside consideration of potential climatic impacts in the medium- and long-term. This would allow for appropriate choices to be made in the near-term that are also sustainable in a changing climate. The implications of our analysis for health, social, and environmental policy is discussed in detail in our Supplementary Discussion.

Closing its current food supply and nutrition gap while meeting increasing population demand will require a combination of domestic measures to improve agricultural practice and subsequent yields, in addition to a well-planned increase in food imports.

Supporting information

S1 file. supplementary discussion..

https://doi.org/10.1371/journal.pone.0193766.s001

S1 Table. Loss and waste percentages by food chain stage and commodity group for South and Southeast Asia.

Due to poor data availability on India-specific food loss figures, regional average figures from the FAO were applied to derive estimates of macronutrient losses at each stage in the Indian commodity chain.

https://doi.org/10.1371/journal.pone.0193766.s002

S2 Table. Assumptions and sources for figures used within all scenarios from 2011 baseline to 2050 scenarios.

https://doi.org/10.1371/journal.pone.0193766.s003

S3 Table. Indian baseline and attainable yield (AY) values for key crop types.

Year 2000 and all attainable yield values have been derived from Mueller et al. (2012)[ 23 ][ 23 ][ 23 ][ 23 ][ 23 ](23)(23)(23)(23)(23)(23)(23)(23)(23)(23)(22)(21)(21)(21), and 2011 yield data derived from the FAOstats database ( http://faostat.fao.org/beta/en/#home ). The necessary percentage increase in yield from 2011 levels to reach each of the AY values has also been shown.

https://doi.org/10.1371/journal.pone.0193766.s004

S4 Table. Average estimated climatic impacts on Indian crop yields in 2050.

Average values have been assumed based on the range of historic studies on yield sensitivities and climatic models within literature review [ 24 ]. These models are projected on the basis of a doubling of CO2 from pre-industrial (which is approximately equivalent to a business-as-usual scenario).

https://doi.org/10.1371/journal.pone.0193766.s005

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• Open access
• Published: 09 January 2023

Food insecurity and its determinants among adults in North and South India

• Anjali Ganpule   ORCID: orcid.org/0000-0002-0821-0673 1 ,
• Kerry Ann Brown   ORCID: orcid.org/0000-0002-6803-5336 2 ,
• Manisha Dubey   ORCID: orcid.org/0000-0003-2879-903X 1 ,
• Nikhil Srinivasapura Venkateshmurthy   ORCID: orcid.org/0000-0003-4037-6371 1 , 3 ,
• Prashant Jarhyan   ORCID: orcid.org/0000-0002-5020-3995 3 ,
• Avinav Prasad Maddury   ORCID: orcid.org/0000-0002-0099-4370 3 ,
• Rajesh Khatkar   ORCID: orcid.org/0000-0002-1004-6702 3 ,
• Himanshi Pandey   ORCID: orcid.org/0000-0002-7076-049X 1 ,
• Dorairaj Prabhakaran   ORCID: orcid.org/0000-0002-3172-834X 1 , 3 , 4 &
• Sailesh Mohan   ORCID: orcid.org/0000-0003-1853-3596 1 , 3 , 5  

Nutrition Journal volume  22 , Article number:  2 ( 2023 ) Cite this article

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Food insecurity is a major public health problem worldwide. In India, there are limited food insecurity assessment studies using a conventionally accepted method like the Food Insecurity Experience Scale (FIES), developed by the Food and Agricultural Organization (FAO). This study aims to measure food insecurity using the FIES and explore its determinants and association with body mass index (BMI) among Indian adults. 

In a cross-sectional study, we used FIES to measure food security in a sample of 9005 adults residing in North and South India. Using questionnaires, socio-demographic factors, dietary intake and food security data were collected. The dietary diversity scores (FAO-IDDS) and food insecurity scores (FAO-FIES) were calculated. Body size was measured and BMI was calculated. 

The mean age of the study participants was 52.4 years (± 11.7); half were women and half resided in rural areas. Around 10% of the participants reported having experienced (mild or moderate or severe) food insecurity between October 2018 and February 2019. Dietary diversity (measured by FAO’s Individual Dietary Diversity Scores, IDDS) was low and half of the participants consumed ≤ 3 food groups/day. The mean BMI was 24.7 kg/m 2 . In the multivariate analysis, a lower IDDS and BMI were associated with a higher FIES. The place of residence, gender and wealth index were important determinants of FIES, with those residing in South India, women and those belonging to the poorest wealth index reporting higher food insecurity.

Food security is understudied in India. Our study adds important evidence to the literature. Despite having marginal food insecurity, high prevalence of low diet quality, especially among women, is disconcerting. Similar studies at the national level are warranted to determine the food insecurity situation comprehensively in India and plan appropriate policy actions to address it effectively, to attain the key Sustainable Development Goals (SDG).

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Introduction

Food security entails access to sufficient, safe and nutritious food that meets people’s dietary needs and food preferences, for leading an active and healthy life [ 1 ]. Despite India being among the fastest growing economies in the world and ranking second worldwide in farm output [ 2 ], the country still faces hunger and diet quality-related issues. Not surprisingly, India is ranked 101 out of 116 countries in the most recent Global Hunger Index report [ 3 ]. It shows that India is still lagging behind when it comes to meeting hunger-related United Nations Global Sustainable Development Goals (e.g., zero hunger (Goal 2), good health and well-being (Goal 3) and in supply of sufficient quantities of food to ensure adequate availability [ 4 ]. An examination of the food insecurity dynamics based on the National Sample Survey data on household consumer expenditure in India since year 2000 revealed that the overall rate of food insecurity has declined, but at a very slow pace [ 5 ]. Thus, monitoring the food insecurity situation and taking immediate policy actions is a public health priority for India.

In the past, multiple proxy measures like anthropometry [ 6 ], wealth index and literacy [ 7 ] have been used to assess food insecurity, mainly as food adequacy. However, food insecurity in the Indian context requires measurement of both food inadequacy [ 4 ] and micro-nutrient deficiency, considering that both are highly prevalent [ 8 ]. Studies around the world also demonstrate the need for this as food insecurity is closely linked to the quality of diets and malnutrition in all its forms [ 9 , 10 ]. Thus, measuring food insecurity using the Food Insecurity Experience Scale (FIES) [ 11 ], which captures both hunger and micronutrient deficiencies, is appropriate in the Indian context. The FAO developed the FIES tool in 2016 [ 11 ], which is globally accepted as a robust and cost-effective indicator or measure of food insecurity [ 11 , 12 ]. It allows the measurement of mild, moderate and severe food insecurity. Mild food insecurity is experienced when hunger is addressed through the intake of cereal-based foods but there is a lack of dietary diversity and variety of food, while severe food insecurity is experienced when people are hungry as they do not get enough food to eat. Validation studies of FIES in India were conducted in 2012 and 2014 among 3,000 individuals and published in the State of Food Security and Nutrition in the World report (SOFI) [ 13 ]. However, very few studies have used FIES to assess food insecurity in India [ 14 ]. Understanding the country-specific context, drivers, and determinants of food insecurity is important [ 15 ]. This can support the planning of targeted interventions as well as effective policies and programs.

Multiple studies show an association of under-and overnutrition with food insecurity [ 16 , 17 ]. Thus, there is a need to study its association with a nutritional outcome like BMI through country-specific studies [ 18 ], particularly in low-middle income countries (LMICs) [ 19 ]. The current study addressed these gaps in the evidence base by measuring the prevalence of food insecurity using FIES, studying its association with socio-demographic factors, economic factors, dietary diversity and BMI among residents of rural and urban households in north and south India.

Materials and methods

Study design.

The analysis presented in this paper is based on data from the UDAY cohort study’s baseline follow-up survey, conducted during October 2018-February 2019, among adult members of urban and rural households in Sonipat (north India) and Vizag (south India) (Fig.  1 ). The methodology of the surveys in the UDAY cohort has been published previously [ 20 ]. Briefly, the study enrolled 12,000 individuals aged ≥ 30 years and was established to improve the prevention, detection and management of diabetes and hypertension.

Flowchart of the study participants. Note: For the present study, cross-sectional data from a larger longitudinal study UDAY are presented. A flow diagram of participants in this longitudinal study has been published elsewhere (Mohan, Set al. 2018). There was no exclusion of the participants. All 9005 participants responded and were included in the study. Socio-demographic, dietary and food security data are available for all the participants based on which the results are presented. BMI data was available for 8718 participants

Measurements

Trained research staff carried out the measurements, which were closely monitored for quality assurance.

Demographics

Information on age, sex, residence (urban or rural), state (Haryana or Andhra Pradesh), household assets were collected through a questionnaire.

• Food insecurity

Food insecurity was measured using the FAO’s FIES eight-item scale, which asks participants to self-report food-related behaviours and experiences associated with increasing difficulties in accessing food due to resource constraints [ 11 ]. As per the standard protocol, participants who responded with a “yes” to 1) being worried about not having enough food or 2) were unable to eat healthy and nutritious food or 3) eating only a few kinds of food, were scored as having mild food insecurity. Those who responded with a “yes” to 4) to skip a meal or 5) ate less or 6) ran out of food, were scored as having moderate food insecurity, while those who responded with a “yes” to 7) were hungry but did not eat or 8) went without eating for a whole day, were scored as having severe food insecurity. The validity of FIES scores as a continuous variable was checked using the Rasch model, as suggested by the FAO (2016). Infit for all questions was within the limit (< 1.3), as recommended by FAO, except for an item (Whole day without eating. Infit:1.35). The outfit was within the limit (< 2.0) for all items except for one item (Whole day without eating. Outfit: 3.54). We dropped this item for further analysis as recommended. For the question “You went without eating for a whole day?” there were only 102/9005 responses and the Rasch model infit was > 1.3. Thus, as per the FAO protocol, after removing these responses, we calculated the proportion of participants experiencing total FIES scores (ranging from 1 to 7), which was used as a continuous variable for the multiple regression analysis.

• Dietary diversity

We conducted an individual food consumption survey using the food frequency questionnaire. Using these data, the individual dietary diversity score (IDDS) was calculated to assess the quality of diet [ 21 ]. Foods were grouped according to the characteristics and nutrient profile predetermined by the FAO for the IDDS as 1) All starchy staples 2) Legumes 3) Milk and milk products 4) Meat and fish 5) Eggs 6) Dark green leafy vegetables, and 7) Other fruits and vegetables. For a food group to be counted in the dietary diversity analysis, the minimum average quantity was set at ≥ 15 g/d. The maximum score of the IDDS was 7 instead of 9 as we did not separately recall for two groups: vitamin A-rich fruits vegetables and organ meats.

Body Mass Index (BMI)

Body weight was measured to the nearest 0.1 kg and height to the nearest 0.1 cm, following the standard procedure [ 22 ] and BMI was calculated as weight in kilograms divided by height in meters squared.

Wealth index

Wealth index was calculated separately for participants from rural and urban areas [ 23 ] using principal component analysis (PCA), which was based on the ownership of 12 household assets (radio, TV, computer, phone, fridge, bike, scooter, car, washing machine, sewing machine, house, and land), and 5 key housing characteristics (water supply, type of toilet and whether it is shared, cooking fuel, housing material, and source of lighting). The first component in the PCA was extracted and divided into quintiles- the first quintile being the poorest and the fifth being the richest.

Statistical analysis

Continuous variables are presented as means (standard deviation [SD]) and categorical variables as frequencies (%). Two sample t-test or Mann Whitney U tests were used based on the distribution of the data for examining the differences in the FIES by wealth index, IDDS and BMI. Multivariate linear regression analysis adjusted for age, sex, and place of residence (rural/urban) was done to study the association of various factors such as IDDS, BMI and wealth index with FIES. We performed mediation analysis using the Monte Carlo simulation (MCS) test to estimate the effect of IDDS on FIES through BMI. The statistical analysis was done using Stata version 16.1 (Stata Corp).

The STROBE-Nut checklist is provided as an additional file .

The study included 9005 participants with a mean age of 52.4 (± SD 11.7) years (Table 1 ). Around half the participants were women and resided in rural areas. Participants from Sonipat were richer compared to those residing in Vizag, as indicated by the wealth index.

Prevalence of food insecurity

About 10% of the participants experienced food insecurity. A higher proportion of participants reported mild FIES than moderate or severe FIES (Fig.  2 ). Women were more likely to report food insecurity than men (Table 1 ). Rural residents had higher food insecurity compared to their urban counterparts. Participants from Vizag reported significantly higher food insecurity compared to those in Sonipat.

Distribution of the study participants by levels of food insecurity. Legend: The figure describes distribution of participants by the levels of food security as mild, moderate and severe. It shows the food insecurity among men and women in Sonipat and Vizag

Dietary diversity was low (mean 3.5 ± SD 0.8). Overall dietary diversity was higher ( p  < 0.05) in Vizag (3.7 ± SD 0.9) compared to Sonipat (3.3 ± 0.8). Dietary diversity was lower in rural compared to urban areas (Table 1 ). About 90% of participants from Sonipat consumed vegetarian diets, while in Vizag > 80% consumed nonvegetarian diets consisting of eggs and fish, while meat was consumed less frequently. The IDDS food groups consumed daily were calorie-rich food groups, i.e., starchy staples, other fruits and vegetables. Protein-rich foods such as dairy were consumed daily (Fig.  3 ). Consumption of nutrient-rich food groups, i.e., green leafy vegetables, vitamin A and C-rich fruits and vegetables and non-vegetarian foods was low. A higher proportion of women consumed green leafy vegetables and legumes than men. In Vizag, men consumed nonvegetarian foods in higher proportions than women.

Distribution of the study participants by IDDS food groups. Legend: The figure reports the proportion of participants consuming various dietary diversity food groups in Sonipat and Vizag by gender and place of residence

Body mass index (BMI)

The mean BMI was 24.8 ± SD 5.7 kg/m 2 ( p  < 0.001 for all differences). Mean BMI was higher in women, participants from urban areas and in Sonipat ( p -value < 0.001) (Table 1 ).

Mediation and regression analysis

We studied the association between IDDS, BMI and FIES using mediation analysis. BMI and IDDS were directly and significantly associated with each other, while both were inversely associated with FIES. Thus, those who had higher IDDS and BMI reported less food insecurity. The indirect effect of IDDS on FIES (via BMI) was found to be around 35% ( p  < 0.01), indicating that the association between IDDS and FIES was indirectly mediated through BMI (Fig. 4 ). In multivariate linear regression analysis (adjusted for state, residence, age, sex and wealth index), IDDS and BMI were inversely associated with FIES. The age of the participants and urban/rural residence were not significant in the multivariate model, while the state of residence, sex, and wealth index were important determinants of FIES. Women reported experiencing significantly higher food insecurity than men. Further, those residing in Vizag and those belonging to the poorest wealth index had higher food insecurity (Table 2 ).

Mediation analysis between dietary diversity, body mass index and food insecurity scores. Legend: The figure shows the results of mediation analysis between BMI, IDDS and FIES. p -value for B1 is 0.113 (insignificant) and for B2 and B3, it is < 0.001 (significant). This indicates that IDDS is associated with food insecurity through BMI

The overall prevalence of food insecurity was low at about 10%. A relatively lower proportion (3%) of the participants reported moderate or severe food insecurity, while mild food insecurity was the highest, being reported by 6.4% of the participants. Dietary diversity was low with lesser consumption of nutrient-rich food groups like vegetables, fruits and protein-rich foods. Most of the participants met their daily calorific requirements through the consumption of starchy staples and starchy vegetables. The mean BMI was 24.7 kg/m 2 , which was directly associated with diet diversity scores. Both diet diversity and BMI were inversely associated with FIES. Further, we found gender and economic status to be significant determinants of FIES among the participants.

Compared to the levels reported in the SOFI report (2020), which shows a high prevalence (24%) of severe food insecurity, the prevalence of moderate or severe food insecurity was low in our study population. One likely reason for this difference could be that the participants in this study resided in economically stable states. Haryana ranks 12 th , while Andhra Pradesh ranks 27 th among 36 Indian states in the Human Development Index (HDI) of the Government of India 2021 [ 24 ]. Our finding of mild food insecurity even in economically stable states is disconcerting. Levels of food insecurity may be much higher in less economically stable states of India. It is thus necessary to establish a baseline and monitor the levels of food insecurity at regular intervals through periodic surveys in all states of India. This is required to plan rigorous and continuous remedial measures to address food insecurity effectively. Present-day threats like COVID-19 pandemic, which results in both health and economic downturns and shocks like climate change induced global warming, that affect all aspects of the food systems, underline the need for such a strategy, as populations can rapidly move between states of being food insecure or food secure.

We found that at the individual level, FIES appropriately measured both hunger and micronutrient deficiencies, and thus is applicable to the Indian context. The tool is globally accepted and recommended for monitoring achievements related the SDG goals [ 25 ]. It applies to both developed and developing countries as it is pre-tested and validated using data from 147 countries [ 26 ]. The findings of mild food insecurity also likely indicate limited access and availability of diverse healthy and nutritious foods. The association of FIES with economic status additionally hints at the affordability issues. Earlier studies have also reported that affordability and accessibility of healthy foods [ 27 , 28 ] can affect food insecurity.

There are efforts at the national level being undertaken to address these issues. For example, the Government of India has undertaken many reforms of the country’s social safety net programs to improve delivery on nutrition and food security targets [ 29 ]. The EAT right campaign of the Food Safety and Standards Authority of India (FSSAI 2021), has brought sustainability into the national nutrition agenda. Additionally, studies suggest the need to expand the food subsidy programs under the National Food Security Act (NFSA) [ 30 ], and the need to include the nutrient-rich food groups in these programs [ 31 ]. To improve consumer practices and awareness related to fruit and vegetable consumption, specific interventions [ 32 ] and nutrition education campaigns [ 33 , 34 ] have also been found to be effective to a certain extent. Overall, a comprehensive holistic approach with targeted interventions will be helpful for improving the consumption of nutrient-rich foods and attaining food security over time.

In the past, studies have reported inconsistent associations of food insecurity with undernutrition and overnutrition. For example, a meta-analysis from 12 countries reported that food insecurity increases the risk of underweight and stunting in children and adolescents [ 16 ]. A longitudinal mixed-method study among adults in the United States reported that food insecurity was associated with an increase in BMI [ 35 ]. In a review of 13 studies, which explored the relationship between food insecurity and overweight/obesity in LMICs, four found a positive association between food insecurity and obesity/overweight; five found no association; and the remaining study found a negative association [ 19 ]. Our study showed that those who had higher food insecurity had higher BMI. This was irrespective of the socio-demographic and economic factors.

One of the key findings is the effect of gender on the food insecurity experience. Women reported higher food insecurity than men. A systematic review and meta-analysis of gender differences in food security revealed that women-headed households reported higher food insecurity [ 36 ]. Even though women contribute to one-half of the world’s food production, they face many inequities, such as access to a lower amount of food and a lower proportion of nutrient-rich food. A few studies have reported gender differences in food and calorie allocation at the household level [ 37 , 38 ]. We found that women, especially from rural area, had lower consumption of nutrient-rich foods such as dairy, fruits-vegetables and nonvegetarian foods. These findings warrant gender-sensitive policies to ensure that all have equal access to nutrient-rich diets.

At present, food systems are facing challenges due to disruptions induced by the COVID-19 pandemic [ 39 ], which has resulted in decreased economic activity, widespread unemployment, and widening health inequalities [ 40 ]. To address such shocks that disrupt food systems, effective policies are necessary both at the local and global levels [ 41 ]. To achieve the Sustainable Development Goal of Zero Hunger by 2030 and to tackle food insecurity, a more responsive food system that meets people’s needs is warranted. This should be aligned with contextually relevant research and targeted policy efforts to make the food system more climate-resilient, nutrition-sensitive and sustainable [ 42 ]. Further, the Global Panel on Agriculture and Food Systems for Nutrition [ 43 ] suggests enhancing and repurposing food-based dietary guidelines and new measures of successes to guide policy decisions, and a new set of incentives to rebalance food prices, to simultaneously address challenges of affordability, availability, consumer demand, and sustainability, which have a direct and significant impact on food security. 

Our study reports mild food insecurity in adults from relatively well-developed states in India. It underlines the need for regular monitoring of the food insecurity situation in India along with the measurement of diet quality and malnutrition, using robust methods. Policies to reduce gender inequalities and increase public awareness about healthy and nutritious diets are warranted. 

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Body Mass Index

Food and Agricultural Organization

Food Insecurity Experience Scale

Individual Dietary Diversity Scores

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Acknowledgements

The authors acknowledge the contribution of the field data collectors and the study participants from Sonipat and Vizag for their cooperation and support.

This study was supported by The Sustainable and Healthy Food Systems (SHEFS) project, funded by the Wellcome Trust, UK (Grant number 205200/Z/16/Z) under the “Our Planet Our Health” programme.  The UDAY cohort study was supported by Eli Lilly through an unrestricted grant under the Lilly NCD Partnership programme. The funders had no role in the design, conduct of the study, or in the analysis and reporting of the study findings. The researchers who developed this manuscript were supported by the SHEFS project and did not receive any support from the Lilly NCD Partnership programme. The contents are solely the responsibility of the authors.

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Anjali Ganpule, Manisha Dubey, Nikhil Srinivasapura Venkateshmurthy, Himanshi Pandey, Dorairaj Prabhakaran & Sailesh Mohan

University of Exeter, Exeter, UK

Kerry Ann Brown

Public Health Foundation of India, New Delhi, India

Nikhil Srinivasapura Venkateshmurthy, Prashant Jarhyan, Avinav Prasad Maddury, Rajesh Khatkar, Dorairaj Prabhakaran & Sailesh Mohan

London School of Hygiene and Tropical Medicine, London, UK

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Contributions

AG and KB wrote the first draft of the paper. All authors reviewed the paper, provided comments on subsequent iterations, and approved the final version. NSV, PJ, AVM, RK, DP and SM designed and conducted the research. MD analysed the data and performed the statistical analysis. HP assisted in the data analysis and paper writing. DP and SM obtained the funding. The author(s) read and approved the final manuscript. 

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Correspondence to Sailesh Mohan .

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Ethics approval and consent to participate.

Ethics approval was obtained from the Institutional Ethics Committee (IEC) of the Public Health Foundation of India and Centre for Chronic Disease Control, New Delhi (IRB No: IRB00006330). Participants willing to participate and who provided informed written consent were included in the study. All the study procedures followed were in accordance with the standards of the institutional ethics committee.

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Supplementary Information

Additional file 1..

STROBE checklist.

Additional file 2:

Supplementary Table 1. Rasch infit and outfit for FIES scale.

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Ganpule, A., Brown, K.A., Dubey, M. et al. Food insecurity and its determinants among adults in North and South India. Nutr J 22 , 2 (2023). https://doi.org/10.1186/s12937-022-00831-8

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Review article, soil salinity and food security in india.

• 1 Department of Soil Science, Chaudhary Sarwan Kumar (CSK), Himachal Pradesh Krishi Vishvavidyalaya (HPKV), Palampur, India
• 2 Sher-e-Kashmir University of Agricultural Sciences and Technology, Jammu, India

India would require around 311 million tons of food grains (cereals and pulses) during 2030 to feed around 1.43 billion people, and the requirement expectedly would further increase to 350 million tons by 2050 when India's population would be around 1.8 billion. To achieve food security in the country, the attempts need to focus on both area expansion under agriculture as well as rise in crop productivity. Massive urbanization is putting pressure on agricultural lands, resulting in shrinking of land holdings. The possibility of area expansion under agriculture, therefore, exists in restoring the degraded lands. Nearly 147 million ha of land is subjected to soil degradation, including 94 million ha from water erosion, 23 million ha from salinity/alkalinity/acidification, 14 million ha from water-logging/flooding, 9 million ha from wind erosion and 7 million ha from a combination of factors due to different forces. Government of India has fixed a target of restoring 26 million ha of degraded lands, including salt-affected soils, by the year 2030 to ensure food security for the people. Around 6.74 million ha area in the country is salt-affected. Estimates suggest that every year nearly 10% additional area is getting salinized, and by 2050, around 50% of the arable land would be salt-affected. Saline soils occupy 44% area covering 12 states and one Union Territory, while sodic soils occupy 47% area in 11 states. The ICAR-Central Soil Salinity Research Institute and many State Agricultural Universities are engaged in studying salt-affected soils and developing reclamation technologies and strategies. Several innovative technologies have been developed and on-farm tested. Gypsum-based sodic soil reclamation, sub-surface drainage of water-logged saline lands, salt tolerant crop varieties and improved agroforestry techniques are some of the well-adapted technologies in the country. Reclamation of 2.18 million ha of salt-affected soils (2.07 million ha barren sodic soils and 0.11 million ha saline soils) has contributed more than 17 million tons of food grains per annum to the country's food basket, with additional annual income of Rs. 15.5 billion, and employment generation of 2.8 million man-days. Other technologies of management of salt-affected soils, viz. alternate land-use systems, saline aquaculture, cultivation of salt tolerant crop varieties, agro-forestry, phytoremediation, bioremediation etc. have positively impacted food and nutritional security, women empowerment, involvement of landless laborers and minimizing rural migration etc. The ongoing consistent research efforts for the management and reclamation of such soils would hopefully continue ensuring food security in the country. The Government needs to make policies favorable for implementation of reclamation technologies in the country.

Introduction

India supports nearly 18% of the world's human population and 15% of the world's livestock population on merely 2.4% of the world's geographical area ( Bhattacharyya et al., 2015 ). Since independence, India has made significant achievement in agriculture sector. Food grain production increased by about 5.5 times, from merely 50 million tons in 1950 to 275 million tons in 2017, making India not only self-sufficient but net exporter of food grains. According to Tiwari (2020) , with a record production of rice and wheat at 116.48 and 103.60 million tons, respectively, the country registered record food grain production of 285.17 million tons in 2018–19. While the increase in food grain production during 1949–65 was mostly due to area expansion under cultivation ( Narain, 1977 ; Vaidyanathan, 1986 ), after mid-sixties, the adoption of a package of high yielding inputs, including use of high yielding varieties, assured irrigation, use of plant protection measures and credit support was responsible for increased production ( Dantwala, 1986 ). It ushered green revolution in India.

In spite of the technological innovations in agriculture, which dramatically increased food production in the past few decades ( Godfray et al., 2010 ), food security globally is being challenged by several factors including climate change ( Parry et al., 1999 ; Rosenzweig et al., 2004 ; Godfray et al., 2010 ), unabated land and environmental degradation ( Oldeman, 1998 ; Pimentel, 2006 ), deforestation, intensive cropping, and biodiversity loss ( Foley et al., 2005 ; Lotze-Campen et al., 2008 ; Tscharntke et al., 2012 ), land use change ( Lotze-Campen et al., 2008 ; Godfray et al., 2010 ), fresh water scarcity ( Rijsberman, 2006 ; Lotze-Campen et al., 2008 ), increased population pressure, increased urbanization and huge food wastage ( Parfitt et al., 2010 ), dietary transition ( Rijsberman, 2006 ; Godfray et al., 2010 ), poverty and social inequality ( Elobeid et al., 2000 ) etc. Sustainability of rice-wheat cropping system in the Indo-Gangetic plains of India has been challenged, as evidenced by the stagnating rice-wheat yields and declining factor productivity during the last about three decades, by the fast receding water table, climate variability, deteriorating soil health, environmental pollution, and secondary salinization ( Aggarwal et al., 2004 ).

Population growth in India has also kept pace with food production. According to the 2017 revision of the World Population Prospects, India's population stands around 1.32 billion ( UNDESA, 2017 ), although, with the Government policies and public awareness, India's population growth rate has shown decline from 2.3% in late 1970s and early 1980s to around 1.13% in 2017 ( Halawar, 2019 ). Even at this growth rate, India is projected to be the world's most populous country by 2024. The massive population increase (despite the slowing down of the growth rate) and substantial income growth demand an extra about 2.5 million tons of food grains annually, besides significant increases in the supply of livestock, fish, and horticultural products. The growth in food grain productivity has stagnated around 2% per annum.

The changing lifestyle and food habits of the people, due to the sustained economic growth, literacy and awareness, are other challenges associated with food security in India. People in general are shifting from staple food grains toward high-value horticultural and animal products ( Kumar et al., 2007 ; Mittal, 2007 ). Although it may lower per capita food grain requirement, yet overall demand for food grains would increase for increasing population and increasing food needs of livestock and poultry. The grain requirement for rearing cattle and poultry etc. is comparatively high because of low and variable efficiency with which various animals convert grains into protein. Table 1 provides global average feed conversion efficiencies for different animal categories and production systems. To produce 1 kg of beef, pork, poultry, and herbivorous species of farmed fish (such as carp, tilapia, and catfish), it takes around 7, 4, 2, and <2 kg of grains, respectively. Currently, livestock supply 13% of energy to the world's diet but consume one-half the world's production of grains to do so ( Smith et al., 2013 ). India would require around 311 million tons of food grains (including pulses) during 2030, and the requirement would further increase to 350 million tons by 2050 ( Kumar et al., 2016 ). At the current growth rate in agricultural production, food security in India appears to be a big challenge.

Table 1 . Global average feed conversion efficiency per animal category and production system.

The projections of higher food requirements due to demographic, economic, and trade liberalization are exerting heavy pressures on India's limited land and water resources. It is estimated that nearly 174.4 million ha of land is potentially exposed to various degradation forces. Land degradation in some regions of India, especially in arid and semi-arid tracts (desertification), is touching irreversible limits. Land degradation has become a big challenge to policy makers who need to balance the multiple goals of poverty eradication, food security, and sustainable land management.

Soil salinization alone has rendered significant chunks of land unproductive or less productive. Soil salinization is a global and dynamic problem and is projected to increase in future under climate change scenarios, viz. rise in sea level and impact on coastal areas, rise in temperature and increase in evaporation etc. Precise statistics on the recent estimates of global extent of salt-affected soils are not available and different data sources provide variable information ( Shahid et al., 2018 ). The global figure of 954.83 million ha as reported by Szabolcs (1989) has been considered authentic. However, figures such as 932.2 million ha ( Sparks, 2003 ) and 952.2 million ha ( Arora et al., 2016 ) have also been reported. According to Mandal et al. (2018) , more recent estimates show an increasing trend in global salt-affected area with an area of 1,128 million ha. According to an estimate, 20% of total cultivated and 33% of irrigated agricultural lands worldwide are afflicted by high salinity ( Shrivasata and Kumar, 2015 ). Around 52 million ha lands are salt-affected in South Asia ( Mandal et al., 2018 ). Around 85% area worldwide is only slightly to moderately affected by high salt concentrations while the remainder 15% suffers from severe to extreme limitations for crop cultivation ( Wicke et al., 2011 ). In India, the salt-affected soils constitute nearly 5% of the net cultivated area, spreading from Jammu & Kashmir (Ladakh region) in north to Kanyakumari in south, and Andaman & Nicobar Islands in the east to Gujarat in the west.

Soil salinization, in addition to reducing net cultivable area, has serious implications for agricultural productivity and quality, the choice of cultivable crops, biodiversity, water quality, supply of water for critical human needs and industry, the longevity of infrastructure and the livelihood security of the people. For all important crops, average yields in salt stressed environments are only a fraction, somewhere between 20 and 50% of record yields ( Shrivasata and Kumar, 2015 ). Estimates suggest global economic losses due to soil salinization around US $ 27.3 billion per year ( Qadir et al., 2014 ).

Growing trend in the salt-affected soils in India is becoming a threat to national food security and economic development. A paradigm shift is, therefore, needed in the policy and methodology of food production in the country. Food security attempts need to focus on both area expansions under agriculture as well as rise in crop productivity. Restoration of degraded lands, including salt-affected soils, offers a potential opportunity of sustaining food security in the country. With this thing in mind, the Government of India has fixed a target of restoring 26 million ha of degraded lands by the year 2030.

Soil Salinity and Soil Salinization

Soil salinity is an index of the concentration of salts in soil and is usually expressed as electrical conductivity (EC). Soil salinization is a process by which there is build-up of salt concentration in soil to such a level that impacts on the agricultural production, environmental health, and economics and quality of life. Soil salinization involves a combination of processes like evaporation, salt precipitation and dissolution, salt transport, and ion exchange etc.

The salt-affected soils contain excessive concentrations of either soluble salts or exchangeable sodium or both due to inadequate leaching of base forming cations. The major soluble mineral salts are the cations: sodium (Na + ), calcium (Ca 2+ ), magnesium (Mg 2+ ), potassium (K + ) and the anions: chloride (Cl − ), sulfate ( SO 4 2 - ), bicarbonate ( HCO 3 - ), carbonate ( CO 3 2 - ), and nitrate ( NO 3 - ). Hyper-saline soil water may also contain boron (B), selenium (Se), strontium (Sr), lithium (Li), silica (Si), rubidium (Rb), fluorine (F), molybdenum (Mo), manganese (Mn), barium (Ba), and aluminum (Al), some of which can be toxic to plants and animals ( Tanji, 1990 ).

Soil salinization may occur through both natural and anthropogenic reasons. Out of 932.2 million ha salt-affected soils worldwide, the extent of human-induced salinization is 76.6 million ha ( Oldeman et al., 1991 ; Mashali, 1995 ; Shahid et al., 2018 ). Arid and semi-arid regions, where evaporation rates are high and fresh waters are scanty to flush out the excess salts from soil, favor the formation of such soils. Gupta and Abrol (1990) have extensively reviewed processes of soil salinization.

a. Natural processes of soil salinization ( i.e ., primary salinization)

• Weathering of parent material : During the process of weathering of rock minerals or sediments with high salt content (physically, chemically, and biologically), salts are released and made soluble. They are transported away from their source of origin through surface or groundwater streams. In arid regions, the concentration of salts gradually increases until they start precipitating in soil due to limited natural precipitation and leaching, high evaporation and transpiration rates. Low-lying areas with high groundwater table and locked topography favor salinization.

• Fossil salts : The fossil salt deposits (e.g., marine and lacustrine deposits) are also responsible for salinization in arid regions. Fossil salts can be dissolved under water storage or water transmission structures causing salinization ( Bresler et al., 1982 ).

• Salinization in coastal lands : The ingression of sea-water along the coast increases salt contents in coastal areas ( Rao et al., 2014 ). The salt-laden winds and rains (sea sprays) along sea coasts carry oceanic salts along with them in quantities sufficient to cause salinization in coastal areas. The sea sprays may contain salt content as high as 14.2 μg m −3 ( Prospero, 1979 ), and may show impact as deep as 80 km inland or even more. The coastal regions are also exposed to the risk of progressive salinization of land due to processes like storms, cyclones, tidal surges, flooding etc.

• Transport of salts in rivers : The salts brought down from the upstream by rivers to the plains and their deposition along with alluvial materials and weathering of rocks may also cause salinization.

b. Anthropogenic reasons of soil salinization (i.e., secondary salinization)

• Land clearing for cultivation : Replacement of perennial vegetation with annual crops, may result into soil salinization due to saline seepage process. Change of land use from natural forest vegetation to annual food crops decreases evapotranspiration and increases leaching. The presence of impermeable/less permeable subsoil layers may intercept the percolating water passing through saline sediments resulting in lateral seepage, causing salinization in low lying areas ( Doering and Sandoval, 1976 ).

• Incorrect irrigation : Indiscriminate use of brackish and saline irrigation water, poor drainage conditions, rising water tables etc., lead to secondary salinization of land and water resources ( Rao et al., 2014 ). Even irrigation with good quality water over a period of time in the absence of proper soil-water-crop management practices may cause salinization. Fall of civilizations like Mesopotamia, Nile Valley, Mohanzoadaro, and Indus Valley are glaring examples of imminent occurrence of salinity following irrigation ( Dagar, 2005 ). Currently worldwide 310 million ha area is irrigated, out of which 20–33% area is estimated to be salt-affected ( Glick et al., 2007 ; Jamil et al., 2011 ; Qadir et al., 2014 ; Shahid et al., 2018 ). Irrigation with sea water causes salinization in coastal areas.

• Over extraction of groundwater : It brings salts to soil surface where they get precipitated when water evaporates ( Rao et al., 2014 ).

• Canal water seepage : It is a serious problem leading to rise in water table and salinity development along the banks of canals. Water-logging and soil salinization in the Indira Gandhi Nahar Priyojna (IGNP) area in India is a glaring example of this process. Around 50% of the command area of IGNP has experienced water-logging ( Tewari et al., 1997 ).

• Over-use of agro-chemicals : Over-use of chemical fertilizers and soil amendments (lime and gypsum) may also lead to soil salinization.

• Use of waste effluents: Use of sewage sludge and/or untreated sewage effluent, dumping of industrial brine onto the soil etc. may also cause soil salinization. Of particular concern is the entry of heavy metals into soils.

At several occasions the socio-economic and political considerations become extremely important in accelerating soil salinization processes. Many times, such factors are beyond the control of individual farmers. Some of such examples, especially in developing countries, may be the ill-conceived or poorly implemented irrigation schemes, intensive vs. extensive irrigation, over-irrigation due to zero water pricing, small and scattered land holdings etc. It is, therefore, the responsibility of respective governments to take appropriate policy decisions and corrective measures in order to keep a check on soil salinization.

Characteristics of Salt-Affected Soils

The salt-affected soils are classified into three groups depending on the nature and concentration of salts present in them:

i. Saline soils (also called “white alkali” or “solonchak” soils): soils containing calcium, magnesium, and sodium as predominant exchangeable cations (Ca and Mg more than Na), and sulfate, chloride, and nitrate the predominant anions; sodium adsorption ratio (SAR) <13; exchangeable sodium percentage (ESP) <15 of total CEC; pH <8.5; EC of saturation extract >4 dS m −1 ; white color due to white crust of salts on the surface; good permeability for water and air; salt problems in general; the salt concentration is enough to adversely affect the growth of most crop plants; mostly found in arid or semi-arid regions where less rainfall and high evaporation rates tend to concentrate the salts in soils; rarely found in humid regions.

ii. Sodic soils (also called “non-saline sodic soils” or “alkali soils,” or “solonetz”): soils high in exchangeable sodium compared to calcium and magnesium; sodium carbonate and sodium bicarbonate are the predominant salts; SAR >13; ESP >15; pH = 8.5–10.0; EC of saturation extract <4 dS m −1 ; black color; poor permeability for water and air; soils formed due to exchange of Ca 2+ and Mg 2+ ions by Na + ions; sodium problems.

iii. Saline-sodic soils : these soils are transitional between saline and sodic soils; SAR >13, ESP >15, pH >8.5; EC of saturation extract >4 dS m −1 ; air and water permeability depends on the sodium content; soils formed due to combined processes of salinization and alkalization; problems with sodium and other salts; leaching converts these soils into sodic soils.

Extent of Soil Salinization in India

Around 60% of the total geographical area of the country is cultivable (arable), of which nearly 80% (141 million ha) is under crops and about 6% (10 million ha) is under rangelands ( Mythili and Goedecke, 2016 ). The remaining arable lands are not cultivated. Nearly 147 million ha of land is subjected to soil degradation, including 94 million ha from water erosion, 23 million ha from salinity/alkalinity/acidification, 14 million ha from water-logging/ flooding, 9 million ha from wind erosion and 7 million ha from a combination of factors ( Bhattacharyya et al., 2015 ; Mythili and Goedecke, 2016 ).

Around 6.727 million ha area in India, which is around 2.1% of geographical area of the country, is salt-affected, of which 2.956 million ha is saline and the rest 3.771 million ha is sodic ( Arora et al., 2016 ; Arora and Sharma, 2017 ). Around 2.347 million ha of the salt-affected soils occur in the Indo-Gangetic plains of the country, of which 0.56 million ha are saline and 1.787 million ha are sodic ( Arora and Sharma, 2017 ). Nearly 75% of salt-affected soils in the country exist in the states of Gujarat (2.23 million ha), Uttar Pradesh (1.37 million ha), Maharashtra (0.61 million ha), West Bengal (0.44 million ha), and Rajasthan (0.38 million ha) ( Mandal et al., 2018 ).

Salt affected soils in India are spread in four major agriculturally important ecological regions in 15 states across the country and Andaman & Nicobar Islands, and they are:

i. Semi-arid Indo-Gangetic alluvial tract of Punjab, Haryana, UP, Delhi, parts of Bihar and West Bengal

ii. Arid and semi-arid tracts of Gujarat, Rajasthan, Madhya Pradesh, and Maharashtra

iii. Peninsular regions of Maharashtra, Karnataka, Tamil Nadu, Andhra Pradesh, and Orissa

iv. Coastal-alluvial region of Andhra Pradesh, Orissa, Tamil Nadu, Kerala, Karnataka, Maharashtra, Gujarat, and Island of Andaman & Nicobar.

The salt-affected soils in India broadly fall in two categories: sodic soils and saline soils. At certain places, with mean annual rainfall around 550 mm, saline-sodic soils are also found in the form of narrow band separating saline and sodic soils ( Arora and Sharma, 2017 ), but because their chemical properties and management are almost the same as the sodic soils, they are grouped with sodic soils category ( Qadir et al., 2007 ). Majority of the sodic soils occur in Indo-Gangetic region of India. They originate primarily due to weathering of rocks and minerals containing high sodium minerals, irrigation with groundwater containing excessive quantities of carbonates and bicarbonates, rise in groundwater table due to introduction of canal irrigation and salt laden run-off from the adjoining areas and un-drained basins. The saline soils are widespread in the canal irrigated arid and semi-arid regions. Table 2 shows the distribution of salt-affected soils in India.

Table 2 . Extent of salt-affected soils in India (‘000 ha).

Mandal et al. (2018) distinguished salt-affected soils into three categories ( Table 3 ). According to these workers sodic, saline, and coastal saline soils are spread over 56, 25, and 19% area in the country ( Table 3 ). Sodic soils are confined in the Indo-Gangetic plains, arid and semi-arid region of western and central India, and Peninsular region in the southern India. Largest area under saline soils (71.2%) occurs in the state of Uttar Pradesh. More than 72% of coastal saline soils occur in the states of Gujarat and West Bengal. Largest area under sodic soils (35.6%) occurs in the state of Gujarat.

Table 3 . State-wise share (%) of salt-affected soils in India.

Introduction of the canal irrigation projects without proper provision of drainage has led to wide spread salinity in the country. Substantial salt-affected area occurs in different canal commands viz., Sharda Sahayak in Uttar Pradesh; Tungabhardra in Karnataka; Indira Gandhi Nahar Pariyojana (IGNP), Chambal and Tawa in Rajasthan and Madhya Pradesh; and Mahi and Ukai command area in Gujarat ( Mandal et al., 2010 ). Continuous seepage from the canals has resulted into rise in water tables and subsequent upward flux of salts to the surface, water-logging, formation of marshy lands, increased soil salinity, and decreased biodiversity. Two glaring examples include: (i) salinization of around 0.37 million ha area in Sharda Sahayak Canal Command region in Utter Pradesh within a span of three decades; (ii) salinization of around 0.18 million ha area in the Indira Gandhi Nahar Priyojana (IGNP) region in Rajasthan within few years of introduction of irrigation project ( Singh, 2009 ).

Use of brackish irrigation waters has caused secondary salinization in about 17% of irrigated lands in the country ( Shahid et al., 2018 ). Good quality irrigation water is scarce in the country. Increasing pressure of producing more food per unit available arable land forces for extensive use of brackish groundwater for irrigation. Ground water surveys indicate that poor quality waters being utilized in different states are 32–84% of the total groundwater development ( Minhas, 1999 ). Many more areas with good quality aquifers are endangered with contamination as a consequence of excessive withdrawals of groundwater.

The salinized areas in India continue to increase each year due to introduction of irrigation in new areas ( Patel et al., 2011 ). The rate of increase is around 10% annually ( Jamil et al., 2011 ). According to Sharma et al. (2014a) , unless preventive/ameliorative attempts are taken, the salt-affected areas are estimated to treble, i.e., increase from 6.74 to 16.2 million ha by 2050.

Delineation and digitization process of salt-affected soils in India is on. Fifteen salt- affected states have been mapped on 1:250,000 scale and digitization on 1:50,000 scale is in progress. The planning and execution of soil reclamation programmes by the policymakers and stakeholders are based on the state-wise data and maps of saline and sodic soils ( Mandal et al., 2010 ). The first approximation of water quality map of India has been published ( Sharma et al., 2014a ), adding great value in executing the plans effectively.

Ecological, Agricultural, and Social Concerns of Soil Salinization

The soil salinization has tremendous environmental, ecological, agricultural, and social impacts in terms of shrinkage of agricultural lands, low agricultural productivity, uncertain and unstable livelihood security, low economic returns, and poor quality of life. Excess salts in soil affect the metabolism of soil flora and fauna, leading ultimately to the destruction of all soil life, transforming fertile and productive lands into barren and desert lands. Soils are rendered useless agriculturally as well as for several other purposes (e.g., construction work). The salt accumulation damages existing infrastructure, farm machinery, waterways, roads etc. History records that soil salinization was partly responsible for the collapse of ancient civilizations like Mesopotamia, Nile Valley, Mohanzoadaro, and Indus Valley ( Dagar, 2005 ).

Salinity affects almost all aspects of plant development including germination, vegetative growth, and reproductive development due to drought and high soil salinity, and harsh environmental conditions ( Machado and Serralheiro, 2017 ). Plants in salt-affected environments experience two types of stress, the osmotic stress and nutrient stress. The osmotic stress is due to low osmotic potential of water in saline soils which adversely affects water absorption by plants. Nutrient stress is due to both toxicity (Na, Cl, B) and deficiency of plant nutrients (N, Ca, K, P, Fe, Zn). It also results in nutritional imbalances. Soil salinity significantly reduces phosphorus uptake by plants because phosphate ions precipitate with Ca ions ( Bano and Fatima, 2009 ). The enhanced Na + absorption in sodic soils reduces K + absorption which adversely affects the enzymatic activities involved in metabolic processes like photosynthesis and protein synthesis ( Hauser and Horie, 2010 ), which is detrimental for plant growth ( Katiyar-Agarwal et al., 2005 ). Reduced leaf area, chlorophyll content and stomatal conductance in salt-affected soils also affect photosynthesis ( Netondo et al., 2004 ).

Apart from high ESP and nutrient deficiencies and toxicities, other constraints for plant growth in sodic soils include poor soil physical conditions, viz. low water and air permeability, high runoff, low water holding capacity, surface crusting, and hard setting. They affect plant root penetration, seedling emergence, and tillage operations ( Murtaza et al., 2006 ).

Although salinization has strong implications on socio-economic aspects, yet very few publications are available in literature ( Shahid et al., 2018 ). Social consequences of soil salinization include decline in agricultural harvest, low income, change of livelihood options and related social constraints. The estimates show that the global annual cost of salt-induced land degradation in irrigated areas could be US$ 27.3 billion in terms of lost crop production ( Qadir et al., 2014 ). Annual global income loss due to salinization of irrigated lands has been estimated around US$ 12 billion ( Ghassemi et al., 1995 ). The inflation-adjusted cost of salt-induced land degradation in 2013 was estimated at US $ 441 per ha, with global economic losses pegged at US $ 27.3 billion per year ( Qadir et al., 2014 ).

The estimates based on 2012–14 moving average data suggest that due to soil salinization India loses annually 16.84 million tons of farm production (cereals, oilseeds, pulses, and cash crops) valued at Rs. 230.20 billion ( Mandal et al., 2018 ). It has strong implications on the national economy. The state of Uttar Pradesh topped the list with 7.69 million tons production loss, followed by Gujarat state with 4.83 million tons production loss. In terms of monetary loss, Gujarat topped the list with Rs. 100.63 billion loss, followed by Uttar Pradesh with Rs. 81.29 billion loss. Gujarat and Uttar Pradesh have the largest salt-affected area (>50% of cultivated area) in the country. These two states alone share around 79% monetary losses in the country. All these states deserve policy attention for management of salt-affected areas to reduce the crop production and monetary loss.

Peoples' living standard, daily life activities and socio-economic conditions are adversely affected. Farmers in response to salinity problem are forced to shift their livelihood strategies ( Ziaul Haider and Zaber Hossain, 2013 ). Farmers in salt-affected areas are generally resource constrained and require financial and technical assistance to sustain their livelihood efforts ( Oo et al., 2013 ).

Such degraded ecosystems, nevertheless, offer immense opportunities to harness the productivity potential through appropriate technological interventions. Even marginal to modest gains in crop yields in such soils would mean dramatic improvements in the lives of thousands of poor farmers in salinity affected regions in a country facing many challenges in agriculture.

Technological Interventions

After decades of experiments globally including ICAR-CSSRI, Karnal and several SAUs in India, understanding the problems of salt-affected soils, poor-quality irrigation waters, water dynamics, causes of salt accumulation and behavior of plants under salt stresses, recommendations have emerged as technologies for reclamation and management of salt-affected soils, viz. gypsum technology for reclamation of sodic soils, developing salt tolerant crop varieties, guidelines for use of poor quality waters, rehabilitation of salty lands using forestry species, etc. ( Mandal et al., 2018 ). There may be two approaches to tackle problem of soil salinity. One, to reclaim salt-affected soils; two, to manage salt-affected soils as they exist, i.e., without reclamation, using alternate suitable agricultural options such as cultivation of salt tolerant crops, saline aquaculture etc. The choice depends on the feasibility of reclamation and the cost effectiveness.

Not all salt-affected soils can be reclaimed practically and economically. While it is feasible to reclaim alkali and sodic soils by specific amendments and manage thereafter, the coastal salt-affected soils and black soils cannot be fully reclaimed. They require continuous soil and water management practices for their productive uses. Indian Council of Agricultural Research (ICAR)-Central Soil Salinity Research Institute (CSSRI) was established in India in 1969 to work exclusively on salt-affected soils. In addition, several State Agricultural Universities, especially those located in salt-affected regions, are also engaged in soil salinity research. Their efforts have resulted in the development of several technological interventions for the reclamation and management of salt-affected soils and use of poor quality water for irrigation in different agro-ecological zones of the country ( Sharma et al., 2011 ). The popularity of gypsum-based sodic soil reclamation, sub-surface drainage of water-logged saline lands, salt tolerant crop varieties and improved agroforestry techniques are a few laudable testimonies to the research credentials of these research Institutes.

Reclamation and Management of Saline Soils

Salt leaching with ponded fresh water, sub-surface drainage, mulching between two irrigations and during fallow period, irrigation management are some of the effective and well-known technological intervention to tackle the problems of water-logging and soil salinity ( Smedema and Ochs, 1998 ; Gupta, 2002 ; Arora and Sharma, 2017 ). The sub-surface drainage technology has been successfully adopted in Haryana, Rajasthan, Gujarat, Punjab, Andhra Pradesh, Maharashtra, Madhya Pradesh, and Karnataka, restoring around 110,000 ha waterlogged saline soils ( Sharma et al., 2014a ).

The adoption of sub-surface drainage technology in saline soils resulted in 3-fold increase in farmers' income. The yields of paddy, wheat and cotton increased by about 45, 111, and 215%, respectively ( Sharma et al., 2014a ). Besides, it significantly increased cropping intensity and socio-economic benefits in terms of on-farm employment generation ( Singh, 2009 ). The sub-surface drainage technology was able to generate around 128 man-days additional employment per ha per annum ( Sharma et al., 2011 ).

The cost of installation of sub-surface drainage system per hectare was estimated Rs. 74,000 for medium to coarse-textured soils with 67 m spacing and Rs. 1,15,000 for fine-textured black soils with 30 m spacing, with a benefit/cost ratio of around 2.71 ( Raju et al., 2016 ). The reclaimed area contributed about 0.56 million tons of foodgrains and an income generation of Rs. 8.60 million annually ( Raju et al., 2016 , 2017 ).

The technology is useful but constrained by bottlenecks like higher initial costs, operational difficulties, lack of community participation and the problems of safe disposal of drainage effluents, for the rapid adoption of this technology ( Singh, 2009 ). Successful implementation of sub-surface drainage projects demands a collective approach and responsibility duly supported by appropriate institutional arrangements ( Ritzema et al., 2008 ). In majority of the salinity affected regions, however, the community participation appears lacking as evidenced by the non-existent or non-functional water-user organizations for irrigation as well as drainage projects. It slows down the up-scaling of reclamation technologies in salt-affected areas.

Reclamation and Management of Sodic Soils

The technology package based on chemical amendments consists of the components such as land leveling, bunding, flushing, drainage for removal of excess water, good quality irrigation water, application of amendments, selection of crops and efficient nutrient management. Different chemical amendments used for the reclamation of sodic soils may be grouped into two categories: soluble calcium sources (e.g., gypsum, calcium chloride, and phospho-gypsum) and acids or acid formers (e.g., elemental sulfur, sulphuric acid, sulfates of iron and aluminum, pyrites and lime sulfur). Farmyard manure and pressmud are also used as amendments for reclaiming sodic soils. Chemical amendments require moisture (rainfall or irrigation) to activate the chemical processes that can reduce sodium levels or leach salts from the root zone. The organic amendments, on the other hand, are capable of alleviating problems associated with excessive salts or sodium without supplemental irrigation.

The amount and type of chemical amendments required for reclamation of sodic soils depend primarily on soil pH, EC, and ESP. Soluble calcium sources are recommended for use in non-calcareous soils while for calcareous soils acids or acid-formers are recommended. Gypsum followed by pyrites has emerged as the most preferred and acceptable chemical amendment for sodic soils in India due to their easy availability and low cost ( Abrol et al., 1988 ; Tyagi and Minhas, 1998 ). Pyrite was much less effective than gypsum ( Tyagi, 1998 ). The pyrites to be effective for reclamation must contain at least 5–6% soluble S ( Sharma and Swarup, 1990 ).

Gypsum requirement for restoring an alkali soil depends on the initial exchangeable sodium percentage (ESP), texture and mineralogy of soil, depth of soil to be reclaimed and tolerance of crops to sodicity. A good correlation exists between soil pH and gypsum requirement ( Abrol et al., 1973 ). Generally, 10–15 Mg ha −1 gypsum is required for the reclamation of alkali soils ( Abrol and Bhumbla, 1971 ).

The addition of organic materials in conjunction with gypsum hastens the reclamation process and also reduces the gypsum requirement ( Chorum and Rengasamy, 1997 ; Vance et al., 1998 ; Arora and Sharma, 2017 ). Addition of organic material increases soil microbial biomass while gypsum lowers soil pH ( Wong et al., 2009 ). Industrial byproducts such as phosphogypsum, pressmud, molasses, acid wash, and effluents from milk plants help in the reclamation of sodic soils by providing Ca directly or indirectly by dissolving soil lime ( Arora and Sharma, 2017 ). However, care should be taken that toxic elements like F, which is present in large quantities in products like phosphogypsum, are not added to soil ( Chhabra et al., 1980 ). The equivalent amounts of other amendments relative to gypsum are given in Table 4 .

Table 4 . Equivalent quantities of some common amendments for sodic soil reclamation.

The gypsum-based alkali land reclamation technology has found large scale on-farm adoption in the country. Nearly 2.07 million ha of barren sodic soils have been brought under cultivation, contributing 16-17 million tons of paddy and wheat per annum to the country's food basket. Farmers are harvesting 5 t ha −1 of rice and 3 t ha −1 of wheat from third year onwards in such reclaimed lands ( Mandal et al., 2018 ). Besides, it also provides an employment opportunity to about 2.8 million man days annually. Financial viability for investment on gypsum technology has been found positive with benefit/cost ratio of 2.47 ( Tripathi, 2011 ). Sharma et al. (2011) calculated the economics for reclamation of sodic soils by considering 10% discount rate. The reclamation cost was estimated to be around Rs. 56,000/ha, with B:C of 1.52, internal rate of return 21.4% and payback period of 3 years.

Reclamation and Management of Coastal Saline Soils

A number of technologies have been standardized and perfected to restore coastal saline soils and sustain crop production in them. Rabi cropping in mono-cropped coastal saline soils, salt tolerant rice cultivars, rainwater harvesting in dugout farm ponds, integrated rice-fish culture and efficient nutrient management have been successfully practiced ( Sharma and Chaudhari, 2012 ). An innovative “ Doruvu ” technology has become popular in coastal regions of the country. The technology involves skimming of shallow depth fresh water floating on the saline water and storing in dug-out conical pits, locally called “ Doruvus .”

Multi-storeyed integrated agroforestry systems involving fish or shrimp culture, poultry, plantation crops, cattle, and diversified arable crops etc. seem to have potential in these areas. Khan et al. (2014) reported an average yield advantage of 20–30% over the existing rice yield of 2.9–3.3 t ha −1 by using biocompost @ 2–6 t ha −1 in sodic soils of Uttar Pradesh.

Initial cost on land excavation for constructing farm ponds, paddy-cum-fish culture and raised-sunken beds in coastal salt-affected areas was around Rs. 145, 136, and 88 thousand, respectively, with benefit/cost ratio of 1.20–1.58 ( Mandal et al., 2018 ). Such techniques in coastal areas of West Bengal increased cropping intensity from 114 to 186% which resulted in increase in farmers' income from Rs. 5,644 ha −1 (wet rice) to Rs. 1,43,982 ha −1 (wet rice-fish-vegetables) ( Mandal et al., 2017 ). Similar encouraging results were obtained through land modification technology (pond based and raised and sunken bed) under sodic soils in Uttar Pradesh ( Verma et al., 2012 ).

Phytoremediation of Salt-Affected Soils

Phytoremediation of salt-affected soils refers to the processes of removing excess salts from soil by growing different type of plants. Growing of salt tolerant trees, shrubs, and grasses is a cost-effective and environmental-friendly way of restoring salt-affected soils ( Mishra et al., 2003 ; Qadir et al., 2007 ). Different species of salt tolerant trees, shrubs, and grasses have been identified and put to use ( Table 5 ). Excellent reviews are available in literature on phytoremediation, e.g., Dagar (2014) for inland salt-affected lands, Dagar et al. (2014a) for coastal regions and Dagar and Minhas (2016) for use of poor-quality waters, etc.

Table 5 . Soil ECe and SAR reduction through phytoremediation and chemical amendments using different plants ( i initial, f final).

Plants remove excess salts from soil through root absorption and accumulate them in their biomass, a process called phyto-accumulation or phyto-extraction . It decreases exchangeable sodium and soluble salt concentrations in soil. They also augment soil organic carbon and nutrient content thereby gradually improving physical (bulk density, porosity, infiltration, water holding capacity etc.), chemical (nutrient concentrations), and biological (microbial population) properties of soils and overall soil productivity ( Bhojvaid and Timmer, 1998 ; Kaur et al., 2000 ; Mishra et al., 2003 ; Nosetto et al., 2007 ; Qadir et al., 2007 ). Tree plantation, besides making degraded lands productive, provides fuel wood, and forage and helps in moderating climate change impacts through carbon sequestration ( Dagar, 2005 ; Sharma et al., 2011 ). It has been estimated that reforestation of 75 million ha degraded lands with suitable trees and grasses/crops has the potential to sequester carbon in above-ground as well as below-ground C biomass to the tune of about 4 Pg of carbon ( Dagar and Swarup, 2003 ).

Reclamation of sodic and saline waterlogged soils through afforestation and agroforestry practices is well established and documented ( Dagar, 2005 ; Dagar et al., 2014b ; Dagar and Minhas, 2016 ). Some of the promising species for sodic soil reclamation include Prosopis juliflora, Acacia nilotica, Casuarina equisetifolia, Tamarix articulate, Eucalyptus tereticornis , and Leptochloa fusca ( Singh et al., 1994 ; Dagar et al., 2016 ), and for waterlogged saline soils include Prosopis juliflora, Tamarix articulata, Casuarina glauca, Acacia farnesiana, Acacia nilotica, Acacia tortilis , and Parkinsonia aculeata ( Dagar and Tomar, 2002 ). Plant species like Eucalyptus tereticornis, Populus deltoids , and Tectona grandis are effective for reclaiming sodic soils ( Singh et al., 1994 ).

Dagar et al. (2001a) used raised-sunken bed technology to successfully establish trees like pomegranate (fruit tree) and Salvadora persica (a non-edible oil yielding tree) on sodic soils. These trees were grown on raised beds to avoid damage due to water stagnation. In highly sodic soils of semiarid regions, having kankar pan in upper 2-m soil layer, Dagar et al. (2001b) used auger hole planting technique for successfully planting the forest tree species like Tamarix articulata, Prosopis juliflora , and Acacia nilotica .

Many grass species suited for sodic soils have been identified but all of them could not find field application due to the reason that they absorb and accumulate sodium and other toxic elements in their foliage and, thus, are unfit as fodder. Efforts are on to identify and popularize those grass species which can retain high proportion of sodium in their root system, rendering the shoots palatable for cattle. However, Biswas and Biswas (2014) have advocated that most of the field crops are less tolerant than grasses to alkali environment. Para grass ( Brachiaria mutica ), rhodes grass ( Chloris gayana ), matricaria ( Matricaria recutila ), Karnal grass ( Leptochloa fusca ) have been found the most promising grass spp. suitable for alkali soils. Aeluropus lagopoides, Chloris barbata, Echinocloa colonum, Dicanthium annulatum, Sporobolus helvolus, Phragmites spp., and Sida spp. have been identified the other promising grasses for rehabilitation of saline soil. Large tracts of salt-affected community and government lands lying barren have been restored and put to best productive use through adoption of agroforestry techniques and agronomic practices.

Promising agro-forestry models, fruit-based agro-forestry models, silvi-pastoral models etc. along with appropriate planting and management techniques have been developed specifically for saline/sodic/saline-sodic etc. conditions ( Singh et al., 1994 ; Dagar et al., 2008 , 2015 ; Sharma et al., 2014b ). Under saline irrigation conditions medicinal and aromatic plants such as isabgol ( Plantago ovata ), aloe ( Aloe barbadensis ), kalmeg ( Andrographis paniculata ), Matricaria chamomilla, Vetiveria zizanioides, Cymbopogon martini , and Cymbopogon flexuosus have been found to produce high biomass ( Tomar et al., 2003a , b ; Dagar et al., 2004 , 2006 ; Tomar and Minhas, 2004 ).

Salt-affected Vertisols (i.e., black cotton soils) are difficult and tedious to restore compared to alluvial sandy loam soils of Indo-Gangetic Plains. The high clay content of these soils makes them vulnerable even at low salt and exchangeable sodium concentrations. Major chunk (about 1.21 million ha) of salt-affected black cotton soils (Vertisols) is found in Gujarat. Such soils also occur in appreciable extent in Karnataka, Maharashtra, and Rajasthan. Commercial cultivation of salt tolerant plants like Salvadora persica (a halophyte, non-edible oil tree), dill ( Anethum graveolens ) a spice crop, industrial species like Euphorbia and Mulethi ( Glycyrrhiza glabra ), castor and sunflower has been found useful in reclaiming these soils and have largely been practiced by the farmers ( Rao et al., 2000 , 2003 ; Sharma and Chaudhari, 2012 ; Arora et al., 2013 ).

Large stretches of canal irrigated lands in many arid and semi-arid regions have become unproductive due to water-logging and the subsequent secondary salinization. Water seepage from canals and faulty on-farm water management practices together create shallow water table conditions. Higher capillary salinization in such areas has caused significant increase in root zone salinity ( Chhabra and Thakur, 1998 ). The conventional approaches to reclaim such lands are expensive, difficult to operate and pose problems in the safe disposal of saline drainage effluents and so have necessitated interest in other viable alternatives such as bio-drainage ( Chhabra and Thakur, 1998 ; Ram et al., 2011 ). Analogous to energy-operated water pumps, bio-drainage is a proven technology to arrest salinity build-up in canal commands with growing of suitable tree species (e.g. eucalyptus, poplar, and bamboo) ( Singh, 2009 ). Efforts are on in exploring combined applications of bio-drainage and suitable land modifications to effectively utilize the water-logged salt-affected soils ( Sharma et al., 2011 ).

Bio-Remediation

The bio-remediation approach, which involves plant-microbial interaction, has received increased attention worldwide for enhancing productivity of salt-affected soils ( Arora et al., 2014 ). The microorganisms have the capability of rapid adjustment toward environmental changes and deterioration, and thus can play an important role in the maintenance and sustainability of any ecosystem. Microorganisms possess some unique properties such as salt stress tolerance, genetic diversity, synthesis of compatible solutes, production of plant growth promoting hormones, bio-control potential, and their interaction with crop plants. If these traits are suitably exploited, microorganisms can play a significant role in alleviating salt effects on crop plants ( Shrivasata and Kumar, 2015 ).

Microorganisms present in the rhizosphere could promote plant growth and yield in salt stress environment in different ways, directly and indirectly ( Dimkpa et al., 2009 ). For example, some plant growth-promoting rhizobacteria may directly stimulate plant growth and development by providing plants with fixed nitrogen, phytohormones, iron (sequestered by bacterial siderophores), and soluble phosphate ( Hayat et al., 2010 ), while others may indirectly benefit plants by protecting them against soil-borne diseases, mostly caused by pathogenic fungi ( Lutgtenberg and Kamilova, 2009 ) by inducing cell wall structural modifications, biochemical and physiological changes leading to synthesis of proteins and chemicals involved in plant defense mechanisms ( Arora and Sharma, 2017 ).

Halophilic bacteria have the potential to remove sodium ions from soil and increase metabolic and enzymatic activities in plants. Arora et al. (2016) used halophilic bacteria for the remediation of saline and sodic soils. In a field experiment, bio-inoculation of wheat seeds with halophilic bacteria increased grain and straw yield of wheat in a sodic soil by 18.1 and 24.2%, respectively. The bacterial inoculation improved soil properties by decreasing soil pH from 9.4 to 8.6, increasing microbial biomass C from 82 to 137 μg/g. Similarly, in a pot experiment irrigated with saline water (5% NaCl), inoculation of halophilic bacterial consortium increased fresh weight, dry weight, shoot length, and root length of maize plants by 194.5, 98.97%, 15.37 and 7.4 cm, respectively, compared to the uninoculated control plants. Arora et al. (2014) could enhance wheat yield by 10–12% in salt-affected soil (EC = 156 dS/m) by using phosphatic solublizing bacteria and Rhizobium strains.

A low-cost microbial bio-formulation “CSR-BIO,” a consortium of Bacillus pumilus, Bacillus thuringenesis , and Trichoderma harzianum , is rapidly becoming popular with the farmers in many states ( Damodaran et al., 2013 ). This bio-formulation acts as a soil conditioner and nutrient mobilizer and has been found to increase the productivity of the high value crops such as banana, vegetables, and gladiolus in sodic and normal soils by 22–43%.

Cultivation of Salt Tolerant Crops and Crop Varieties

Cultivation of salt tolerant crops and crop varieties is another way to address the problem of soil salinization. This technique is viable and cost effective and suits well to the small and marginal farmers who without financial support are unable to bear the high costs of chemical amendment-based reclamation technologies. Salt tolerant varieties of rice, wheat, mustard, and other crops, grasses, shrubs, fruit trees, and medicinal and aromatic plants have been developed/identified for commercial cultivation in salt-affected soils ( Singh, 2009 ; Sharma et al., 2011 ). The relative tolerance of some crops to total salinity (EC) and sodicity (ESP) is shown in Tables 6 , 7 , respectively.

Table 6 . Relative tolerance of some crops to salinity (EC).

Table 7 . Relative tolerance of some crops to soil sodicity (ESP).

Use of salt tolerant varieties of field crops is another practical option to manage salt-affected soils with the poor farmers, especially small and marginal, for whom chemical amendment technologies are not feasible without Government subsidies ( Arora and Sharma, 2017 ). Several varieties of important field crops like rice, wheat and mustard, having potential to yield reasonable economic returns in saline and sodic soils, have been developed ( Singh and Sharma, 2006 ).

Cultivation of salt tolerant multipurpose trees, bushes, and grasses, fruit plants, medicinal and aromatic plants etc. on salt-affected village community lands, road-side lands, lands along the railway tracks, Government lands etc. is another opportunity of managing salt-affected soils ( Singh et al., 1994 ; Minhas et al., 1997 ; Tomar et al., 2003b ).

Tissue culture techniques find usefulness in developing suitable salt-tolerant trees and crops of high economic value.

It may be noted, however, that crop production on salt-affected soils is generally costlier and crop yields are usually low, net returns are low and the risk of crop failures continues even after suitable amendments are provided ( Minhas and Sharma, 2003 ).

Saline Aquaculture

Inland saline aquaculture (land-based aquaculture using saline groundwater) is being commercially practiced in many saline tracts of Australia, Israel, and USA ( Allan et al., 2009 ). This knowledge was used in India also to make the saline water-flooded soils profitable. The experience in many parts of south-western Haryana and Punjab have shown that the degraded soil and water resources could be put to profitable use by shrimp and fish farming ( Purushothaman et al., 2014 ). At Nain Experimental Farm, Panipat, Haryana (India), under conditions of high salinity of pond water (25 dS m −1 ), low water availability and high evaporation losses, fish growth of about 400–600 g in 6-month and 600–800 g in 1-year period was observed ( CSSRI, 2013 ).

In coastal areas of Andhra Pradesh, many farmers have converted their rice fields into brackish water fish farms for reason of high remuneration from aquaculture. They store brackish water, drawn from the sea through creeks and drains, in big tanks for raising high value prawns. Estimates suggest that nearly 0.2 million ha is under saline aquaculture in the coastal districts of Andhra Pradesh. Many small and marginal farmers (>50%), however, found this technology (prawn farming) highly risky with unstable returns, and hence abandoned after few years ( Singh, 2009 ).

Multi-Enterprise Agriculture Models

Integrated multi-enterprise models comprising different components, viz. field and horticultural crops, fishery, cattle, poultry, and beekeeping etc. are being developed and tested to address the specific needs of small and marginal farmers especially in post reclamation phase. The models have been standardized for specific conditions such as saline soils of Haryana, water-logged sodic soils of Uttar Pradesh, highly saline black soils of Gujarat and coastal saline soils of West Bengal ( Singh, 2009 ; Sharma and Chaudhari, 2012 ). The aim is to sustain resource use efficiency, high and regular income and employment generation to the farmers. The models drastically reduce the production costs by synergistic recycling of resources among different components.

A multi-enterprise model developed and evaluated by ICAR-CSSRI Karnal for reclaimed sodic land generates net annual income of Rs. 2.65 lakh ( Chinchmalatpure et al., 2015 ). The model on daily basis generates a gross income of Rs. 400–700 and net income of Rs. 250–500 from about 1.0 ha land area when fisheries, dairy, horticulture, poultry, duckery, and mushroom cultivation are integrated and by-products of these enterprises are recycled within the system. Biogas produced (2 m 3 per day) in the Model adequately meets the energy requirements of farmer's family.

Reclamation of Salt-Affected Soils and Food Security in India

It is estimated that due to soil salinization India loses around Rs. 230.20 billion annually in terms of crop production loss to the tune of 16.84 million tons ( Mandal et al., 2018 ). The Indian Government, therefore, has attached highest priority to the policy planning for the reclamation of degraded lands, including salt-affected soils in the country. The Indian Government is keen to restore 26 million ha of degraded lands by the year 2030 in order to ensure food security in the country. Significant research efforts have been made during the last 4 decades with encouraging results. The response of the farming community in salt-affected regions is overwhelming.

Sharma and Chaudhari (2012) reported reclamation of 1.5 million ha of salt-affected soils in the country, with addition of around 15 million tons of food grains to the national food basket annually. It provided additional income of around Rs. 13.5 billion per annum, and also generated 8.33 million man-days per year in terms of on-farm and off-farm rural employment opportunities. According to a recent publication of Mandal et al. (2018) , around 2.18 million ha salt-affected soils (0.11 million ha saline soils and 2.07 million ha sodic soils) have been reclaimed in India. The reclamation has been achieved through gypsum technology in saline soils and sub-surface drainage technology in sodic soils. It has contributed an estimated 17.16 million tons of food-grains per annum (16.6 million tons from saline soils and 0.56 million tons from sodic soils) to the national food basket, with additional income of as high as Rs. 15.5 billion annually ( Mandal et al., 2018 ).

The technological interventions on other aspects of salt-affected soils such as alternate land-use systems, saline aquaculture, cultivation of salt tolerant crop varieties, agroforestry, phytoremediation, bioremediation etc. have proved their worth by positively influencing food and nutritional security, women empowerment, involvement of landless laborers and minimizing rural migration, besides restoration of the ecological balance by its positive impact on environment ( Sharma and Chaudhari, 2012 ).

Soil salinization is a serious problem challenging food security in India. It is a dynamic process caused by several natural and human-induced processes, and quite often, the socio-economic and political considerations become extremely important in accelerating the processes of soil salinization. Many times, such factors are beyond the control of individual farmers and call for the attention of the policy makers. It becomes the responsibility of respective governments to take appropriate policy decisions and corrective measures in order to keep a check on soil salinization and also to restore the soils already affected by salts.

Several on-farm tested technologies are available for the reclamation and management of salt-affected soils. The efforts put-in by Government agencies and farmers for the reclamation and rehabilitation of salt-affected soils in the country so far have been encouraging. Nevertheless, in order to achieve the target of reclamation of 26 million ha of salt-affected soils, concerted efforts are needed by all the stakeholders. The site-specific restoration programmes be conceived and implemented in mission mode with the genuine participation of the local farmers. The farmers need to be incentivized rather than subsidized to undertake corrective measures. Under the scenario where the cultivable lands are shrinking due to increased urbanization, the restoration and management of salt-affected soils offer a potential hope of land expansion and production enhancement for future food security in the country.

Author Contributions

PK contributed in conception and first draft preparation. PKS reviewed, analyzed, and provided interpretation. All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: degraded lands, salinization, saline soils, sodic soils, reclamation technologies, food security

Citation: Kumar P and Sharma PK (2020) Soil Salinity and Food Security in India. Front. Sustain. Food Syst. 4:533781. doi: 10.3389/fsufs.2020.533781

Received: 10 February 2020; Accepted: 31 August 2020; Published: 06 October 2020.

Reviewed by:

Copyright © 2020 Kumar and Sharma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Pardeep Kumar, drpardeep1968@gmail.com

† Present address: Pradeep K. Sharma VPO Aima, Palampur, India

This article is part of the Research Topic

Sustaining Soil Carbon to Enhance Soil Health, Food, Nutritional Security, and Ecosystem Services

The Food and Nutrition Status in India: A Systematic Review

• First Online: 07 March 2023

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• Aakriti Grover 6 , 7  

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With undernutrition, overnutrition, and micronutrient deficiencies afflicting the country, India experiences a triple burden of malnutrition. Recent decades have seen modest progress when it comes to health in India, but progress has been uneven and inequitable. This study reviews food and nutrition status in India. The diversity in food is enabled by variety in nutrition, which is only possible with serious crop diversification. The nutrient uptake is majorly cereal-centric as food production, availability, and access are impacted by the agricultural policy that has placed a significant thrust on food grain production spurred by the green revolution and supported by the institutions. India is not only affected by malnutrition amongst the poor but also amongst all socio-economic groups. India ranks 101 out of 116 countries based on the Global Hunger Index 2020. The Global Nutrition Report 2018 clearly mentions that India is home to 46.6 million stunted children and 25.5 million wasted children. India ranks 103 out of 119 qualifying countries per the Global Hunger Index 2018. Malnutrition was the predominant risk factor for death in children younger than five years of age in every state of India in 2017 (GBD), accounting for 68.2% (95% UI 65.8–70.7) of the total under-5 deaths and the leading risk factor for health loss for all ages, responsible for 17.3% (16.3–18.2) of the entire disability-adjusted life years (DALYs). In India, nutrition status has deteriorated over decades because of ineffective policy interventions and inadequate food systems, which are neither affordable nor sustainable. There are severe gaps in India’s nutrition statistics, and even the most important nutrition trends are far from explicit; practical action in this field requires regular and reliable large-scale surveys that would make it possible to monitor the nutrition situation at the district levels at intervals.

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Basheer, S., Ashique, V.V., Grover, A. (2023). The Food and Nutrition Status in India: A Systematic Review. In: Grover, A., Singh, A., Singh, R.B. (eds) Sustainable Health Through Food, Nutrition, and Lifestyle. Advances in Geographical and Environmental Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-19-7230-0_9

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