Correction
21 Oct 2022: Jaacks LM, Gupta N, Plage J, Awasthi A, Veluguri D, et al. (2022) Correction: Impact of the COVID-19 Pandemic on Agriculture in India: Cross-Sectional Results from a Nationally Representative Survey. PLOS Sustainability and Transformation 1(10): e0000033. https://doi.org/10.1371/journal.pstr.0000033 View correction
Figures
Abstract
The COVID-19 pandemic has disrupted agriculture in India in many ways, yet no nationally representative survey has been conducted to quantify these impacts. The three objectives of this study were to evaluate how the pandemic has influenced: (1) cropping patterns and input use, (2) farmers’ willingness to adopt sustainable agricultural practices, and (3) farmers’ COVID-19 symptoms. Phone surveys were conducted between December 2020 and January 2021 with farmers who had previously participated in a nationally representative survey. Values are reported as weighted percent (95% confidence interval). A total of 3,637 farmers completed the survey; 59% (56–61%) were small/marginal farmers; 72% (69–74%) were male; and 52% (49–55%) had a below poverty line ration card. A majority of farmers (84% [82–86%]) reported cultivating the same crops in 2019 and 2020. Farmers who reported a change in their cropping patterns were more likely to be cultivating vegetables (p = 0.001) and soybean (p<0.001) and less likely to be cultivating rice (p<0.001). Concerning inputs, 66% (63–68%) of farmers reported no change in fertilizers; 66% (64–69%) reported no change in pesticides; and 59% (56–62%) reported no change in labor. More than half of farmers (62% [59–65%]) were interested in trying sustainable farming, primarily because of government schemes or because their peers were practicing it. About one-fifth (18% [15–21%]) of farmers reported COVID-19 symptoms in the past month (cough, fever, or shortness of breath) and among those with symptoms, 37% (28–47%) reported it affected their ability to work. In conclusion, COVID-19 infections had started to impact farmers’ productivity even during the first wave in India. Most farmers continued to grow the same crops with no change in input use. However, many expressed an interest in learning more about practicing sustainable farming. Findings will inform future directions for resilient agri-food systems.
Author summary
Nearly half of the Indian population is employed in agriculture, yet no nationally representative survey has explored the impact of the COVID-19 pandemic on farmers. We leveraged a pre-existing nationally representative sample of 20 states/union territories to conduct surveys via phone interview between December 2020 and January 2021 with 3,637 farmers. This period coincided with the end of the first wave of COVID-19 (which peaked in mid-September 2020) and the end of the Kharif (monsoon) season–the major agricultural season when rice is primarily cultivated. Our three objectives were to evaluate how the pandemic has influenced: (1) cropping patterns and the use of inputs such as fertilizers, pesticides, and labor; (2) farmers’ willingness to adopt sustainable agricultural practices such as organic farming; and (3) farmers’ COVID-19 symptoms. We found that symptoms associated with COVID-19 had started to impact farmers’ productivity even during the first wave in India. Most farmers continue to grow the same crops with no change in input use. However, many expressed an interest in learning about sustainable farming practices. Among the farmers who did change their cropping pattern, they were more likely to be growing nutrient-dense crops (vegetables) instead of rice. Findings will inform future directions for resilient agri-food systems.
Citation: Jaacks LM, Gupta N, Plage J, Awasthi A, Veluguri D, Rastogi S, et al. (2022) Impact of the COVID-19 pandemic on agriculture in India: Cross-sectional results from a nationally representative survey. PLOS Sustain Transform 1(8): e0000026. https://doi.org/10.1371/journal.pstr.0000026
Editor: Prajal Pradhan, Potsdam Institute for Climate Impact Research (PIK), GERMANY
Received: February 4, 2022; Accepted: July 9, 2022; Published: August 18, 2022
Copyright: © 2022 Jaacks 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: De-identified participant data is available at https://doi.org/10.7910/DVN/YOOU7C.
Funding: Funding to support data collection was provided by the Council on Energy, Environment and Water (AJ), The Royal Society of Edinburgh and the Scottish Government (LMJ), discretionary faculty research funds from the Harvard T.H. Chan School of Public Health (LMJ), and Medical Research Council/UK Research and Innovation (LMJ). ED received salary support from the Royal Society of Edinburgh and the Scottish Government for this work. LMJ received salary support from Medical Research Council/UK Research and Innovation for this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Since its initial outbreak in Wuhan, China, in December 2019, coronavirus disease 2019 (COVID-19) has killed more than 6 million people globally [1]. In addition, more than 100 million people are estimated to have ‘long COVID’ globally, with the highest rates of long COVID reported in Asia [2]. Thus, the COVID-19 pandemic will have long-lasting effects on population health and wellbeing. In addition, supply chain disruptions arising from government responses to control the pandemic, i.e. lockdowns and border closures, have led to a re-emergence of debates on the vulnerabilities of globalized value chains [3]. Finally, the pandemic and pandemic response led to the largest global economic crisis in more than a century with the world economy shrinking by approximately 3% and global poverty increasing for the first time in a generation [4]. Given that agriculture is the largest employer in most developing economies [5] and the important role agriculture plays in food security, an in-depth evaluation of this particular sector is warranted.
India’s agricultural system is largely based on input-intensive monocropping of staple crops. Two-thirds of irrigated land and one-third of unirrigated land is cultivated with paddy and wheat [6]. With regards to inputs, 90% of irrigated land and 63% of unirrigated land is treated with synthetic fertilizer and approximately 40% of agricultural land is treated with synthetic pesticides [6]. While there has been an increase in organic farming and other sustainable approaches such as natural farming in recent years, it still makes up less than 2% of all cultivated land [7,8]. The cost of cultivation has been increasing [9] and yields of rice and wheat have been stagnating [10], resulting in more than half of agricultural households being in debt [11]. Thus, even before the COVID-19 pandemic, there was a crisis among Indian farmers.
In 2020, as a result of public health interventions to prevent the spread of COVID-19, there were major disruptions to India’s agri-supply chains. A phone survey of a convenience sample of Indian farmers across 12 states conducted in May 2020–during the first lockdown–found that farmers struggled to sell their produce because the market price was too low or they could not access the markets due to travel restrictions [12]. Moreover, about half of farmers reported the lockdown had affected their ability to sow for the upcoming season due to labor not being available and not being able to access or afford inputs such as seeds, fertilizer, and pesticides [12]. One might expect that the high cost of these products and disruption to accessing them during the pandemic may have led some farmers to consider agricultural practices that do not rely on external inputs, such as organic farming, natural farming, and other sustainable agricultural practices. At the same time, from the demand-side, the pandemic and increasing health-consciousness among consumers in India has stimulated growth of the organic market [13].
To address the aforementioned disruptions to the agriculture sector, the Finance Minister announced a COVID-19 economic package worth 1.5 trillion Indian Rupees (INR) (~20 billion US Dollars [USD]) aimed at strengthening infrastructure, logistics, and capacity building [14]. A majority of the funds went to setting up an “Agri Infrastructure Fund” to finance projects at the farm gate and aggregation points [14]. Other aspects of the package included the promotion of herb/medicinal plant cultivation and the extension of “Operation Greens” from tomato, onion, and potato to all fruits and vegetables [14]. These new initiatives may also shift agricultural practices, particularly cropping patterns. One previous survey found that more than 90% of farmers who were monocroppers in Kharif 2019 were monocroppers in Kharif 2020–and primarily cultivating rice–suggesting there has not been a major shift in cropping patterns as a result of the pandemic [15], but further research is needed to confirm this observation.
To date, no nationally representative study has been conducted among Indian farmers nor has any study explored whether the pandemic has shifted farmers’ crop choices, input use, and willingness to adopt more sustainable practices. Moreover, early in the pandemic–i.e., in May 2020–individuals living in urban slums were nearly twice as likely to have been infected with COVID-19 (Immunoglobulin G antibody positive in a national seroprevalence study) as compared to individuals in rural areas [16]. However, by mid-September 2020, when India’s first wave of COVID-19 peaked, rural areas had also experienced a rise in cases [17]. Whether or not this affected farmers’ ability to work has not been explored. Given that different crops have different labor requirements [18] and sustainable agricultural practices tend to be more labor-intensive [19], one might expect COVID-19 infection to affect a farmer’s decision to cultivate a certain crop or adopt chemical-free practices.
There are multiple pathways through which agriculture impacts food and nutrition security [20]. Agricultural production is a direct source of food for farmers and a source of income that can be used to purchase food. Agriculture also has indirect effects on nutrition security through influencing expenditures on health care, education, and improved water and sanitation as well as women’s empowerment and caring practices. Farming systems that promote crop diversity, such as agroecology, may have an even greater positive effect on nutrition security [21]. Indeed, during the first COVID-19 lockdown in India, it was observed that farmers who cultivated two or more crops were less likely to experience a decline in dietary diversity than farmers who cultivated one crop (i.e., monocroppers) [15]. Thus, any impact of the COVID-19 pandemic on agriculture may have downstream effects on food and nutrition security.
There were three primary objectives of this study. First, to understand how the COVID-19 pandemic has influenced cropping patterns and the use of inputs by Indian farmers. Second, to evaluate how the COVID-19 pandemic has influenced their willingness to adopt sustainable agricultural practices. Third, to monitor if Indian farmers are experiencing symptoms of COVID-19 that disrupt their work activities. In addition, a secondary objective was to evaluate food insecurity and diet quality in the most vulnerable group of farmers, namely, agricultural laborers. Together, findings from these objectives deepen our understanding of the impact of the COVID-19 pandemic on national food security and future directions for resilient agri-food systems.
Results
Characteristics of study sample
Of the 5,200 participants called, 4,099 (79%) answered the call and 3,637 (89%) of those who answered consented to participate (Fig 1). Of the total consented participants, 3,266 were farmers and the remaining 371 were agricultural laborers. Not having time was the most common reason reported for not participating (40%). Twenty states/union territories (herein ‘states’) were represented in the sample (S1 Table). State-wise sample sizes ranged from 2 (Delhi and Uttarakhand) to 419 (Uttar Pradesh). The sample size was particularly small for Delhi (n = 2), Haryana (n = 16), and Punjab (n = 19), partly because farmer protests were going on at the time of the survey.
The weighted mean farm size was 2.11 ha, ranging from 0.004 to 23.8 ha; 59% (95% confidence interval [CI], 56–61%) of participants were small/marginal farmers. A majority of participants were male and middle-aged; about one-third lived in households with 6 or more people; and 17% (15–19%) were illiterate (Table 1). About one-third reported belonging to Other Backward Caste (OBC) and half reported having a Below Poverty Line (BPL) ration card. Landless and small/marginal farmers had smaller household sizes (p = 0.005) and were more likely to have a BPL ration card (p = 0.001).
Change in cropping patterns and input use during the COVID-19 pandemic
A majority of participants cultivated in both 2019 and 2020 (83% [95% CI, 80–85%], data not shown). Among these participants, 76% (73–79%) reported no change in the area of land cultivated on their farms (Table 2). The remaining 21% (18–24%) reported an increase in cultivated land and 3% (2–4%) a decrease in cultivated land. At the state level, the percent reporting no change in the area of land cultivated on their farms ranged from 41% (28–56%) in Assam to 94% (89–96%) in Gujarat (S2 Table). In Assam and Odisha, a much larger proportion of farmers reported an increase in the amount of land cultivated: 57% (42–71%) and 50% (39–60%), respectively (S2 Table). The most commonly reported reason for a change in the extent of land cultivated was a financial loss during the lockdown, which was reported by 53% (46–60%) of farmers (Fig 2).
With regards to cropping pattern, 84% (95% CI, 82–86%) of farmers reported cultivating the same crops in 2019 and 2020 (Table 2). Among those who reported a change in the type of crop, 41% (34–49%) said it was a temporary change, but 32% (25–39%) said they were considering a permanent change. The reporting pattern was similar across all states, except Assam and Karnataka, where 36% (22–53%) and 48% (41–55%), respectively, reported a change in their cropping pattern (S2 Table). Rice and wheat were the most commonly cultivated crops in both Kharif 2019 and 2020 followed by pulses, vegetables, and mustard (Fig 3). Vegetables were the most commonly cultivated crops in kitchen gardens with other crops (including fruit) rarely cultivated in kitchen gardens.
‘Rice’ includes basmati and other. ‘Pulses’ includes tur, urad, gram, moong, and other. Crops were presented if they were reported by >5% of participants. Rapeseed, other oilseeds, fruit, coconut, jute, and spices were reported by <5% of participants and were therefore not presented.
Farmers who changed their cropping patterns were less likely to be cultivating rice (27% versus 41% among farmers who did not change their cropping patterns, p<0.001) and wheat (27% versus 36% among farmers who did not change their cropping patterns, p = 0.05). Those who changed their cropping patterns were more likely to be cultivating vegetables (26% versus 15% among farmers who did not change their cropping patterns, p = 0.001) and soybean (7% versus 3% among farmers who did not change their cropping patterns, p<0.001).
The most commonly reported reason for continuing to cultivate the same crop was that it was profitable (Fig 4). Not having a specific reason to shift and not having the knowledge to change crops were also commonly reported. Among farmers who changed crops, the most commonly reported reason was weather followed by market price.
Abbreviations: MSP, minimum support price.
Concerning inputs, 66% (95% CI, 63–68%) of farmers reported no change in fertilizers; 66% (64–69%) reported no change in pesticides; and 59% (56–62%) reported no change in labor (Table 2). Medium and large farmers were more likely to report no change in fertilizer use compared to small/marginal farmers (p = 0.01). Participants were more likely to report a decrease in labor availability (24% [22–26%]) than an increase in availability (17% [15–19%]). In terms of state-wise differences, farmers from Andhra Pradesh (25% [16–37%]), Chhattisgarh (31% [19–46%]), Odisha (22% [16–29%]), and West Bengal (39% [33–46%]) were most likely to report an increase in the use of fertilizers (S2 Table). Farmers from Andhra Pradesh (34% [23–46%]), Gujarat (36% [27–45%]), and West Bengal (36% [30–43%]) were most likely to report an increase in the use of pesticides. Farmers were most likely to report a decrease in labor availability in Andhra Pradesh (37% [25–50%]), Assam (35% [21–53%]), Madhya Pradesh (49% [42–57%]), and Odisha (45% [35–56%]). Poor soil quality and too expensive were the top two reasons for reporting a change in fertilizer use (Fig 5). More pests was the number one reason for reporting a change in pesticide use.
Coping strategies during the COVID-19 pandemic and willingness to adopt sustainable agricultural practices
About 1 in 5 farmers (21% [95% CI, 18–23%]) had a problem in accessing bank credit during the Kharif season, with loan sanction delays identified as the main problem by half of participants (Table 3). Across states, farmers in Madhya Pradesh had the greatest difficulty in accessing bank credit: 56% (48–63%) of farmers reported having a problem in this state (S3 Table).
In terms of coping strategies to help mitigate the impact of COVID-19, one-third of participants had a kitchen garden for home consumption–small/marginal farmers were more likely to have kitchen gardens than medium and large farmers (p<0.001)–and 50% reported eating their own production (Table 3). More than 50% of farmers in Assam, Bihar, Odisha, and West Bengal had kitchen gardens (S3 Table). Other commonly reported coping strategies included reducing the price of produce (31% [95% CI, 29–34%] of farmers), finding new markets (21% [19–24%]), and storing more of their produce (17% [15–20%]) (Table 3). Small/marginal and medium farmers were more likely to store their produce than larger farmers (p = 0.03).
About half of farmers (52% [95% CI, 49–55%]) reported avoiding the use of chemicals such as fertilizers or pesticides to some extent and 62% (59–65%) were interested in trying these practices, primarily because of government schemes encouraging such approaches or because their peers were practicing it (Table 3). Small/marginal farmers were more likely to report government schemes and peers, whereas large farmers were more likely to report high input costs (all p<0.001). In four states–Assam (74% [59–85%]), Chhattisgarh (67% [55–78%]), Madhya Pradesh (76% [69–82%]), and Tamil Nadu (84% [75–90%]), the vast majority of farmers reported avoiding the use of chemicals such as fertilizers or pesticides to some extent (S3 Table). The lowest rates of interest in agroecology practices were in Karnataka (21% [15–27%] expressing an interest) and Gujarat (19% [14–26%] expressing an interest). Government schemes were most frequently cited as a reason in Chhattisgarh, Madhya Pradesh, Tamil Nadu, and West Bengal. COVID-19-related reasons were most frequently cited in Karnataka, Madhya Pradesh, Maharashtra, Rajasthan, and Tamil Nadu, and rarely reported in other states.
COVID-19 symptoms and impact on work
With regards to COVID-19 symptoms in the past month, 8% (95% CI, 6–9%) of farmers had a cough, 12% (9–15%) had a fever, 5% (4–7%) had shortness of breath, and 18% (15–21%) had any one of these three symptoms (Table 4). Among those who had COVID-19 symptoms, 22% (14–32%) said it impacted their ability to work for several days in the past month; 10% (6–17%) said it impacted their ability to work for more than half the days in the past month; and 5% (1–18%) said it impacted their ability to work nearly every day in the past month. Landless and small/marginal farmers were most likely to report COVID-19 symptoms had an impact on their work (p = 0.03).
Contrary to our hypothesis, we did not find an association between COVID-19 symptoms and changes in crop cultivation patterns or interest in trying agroecological practices. Among those with COVID-19 symptoms, 13% reported changing the type of crop they are cultivating compared to 16% among those without symptoms (p = 0.20). Among those with COVID-19 symptoms, 68% reported an interest in trying agroecological practices compared to 61% among those without symptoms (p = 0.17). Results were similarly non-significant for COVID-19 symptoms affecting their work: symptoms versus no symptoms, 14% versus 13%, respectively (p = 0.91), for changing the type of crop they are cultivating, and 63% versus 70%, respectively (p = 0.49), for interest in trying agroecological practices.
Food security and diet quality among agricultural laborers during the COVID-19 pandemic
Among agricultural laborers, 43% (95% CI, 35–51%) were not able to find work in the current Kharif season. Among those who were able to find work, it was mostly as agricultural laborers (82% [72–80%]), though 5% (3–8%) had work through the Mahatma Gandhi National Rural Employment Guarantee Act 2005 (MGNREGA) (Table 5). About one-third reported a decrease in the number of days employed (34% [25–44%]) and 17% (11–25%) a decrease in wage rate. In terms of support received in the past 3 months, 75% (67–81%) had received rations. One in five had not received any support during this period.
A total of 44% (95% CI, 7–52%) of agricultural laborers reported having a kitchen garden for home consumption (Table 5). In terms of food insecurity, 43% (36–51%) were worried about food in the past month and 21% (16–28%) ate less than usual. More severe forms of food insecurity–skipping a meal in the past month and going without eating for a whole day in the past month–were less common. Diet quality was very poor: the weighted mean dietary diversity score was 1.28 (out of a maximum of 8) and 94% (91–97%) of participants had low dietary diversity. The most commonly consumed food groups were grains (59% [50–67%] consuming daily), vegetables (24% [19–31%] consuming daily), potatoes (18% [14–23%] consuming daily), dairy (15% [9–25%] consuming daily), and pulses (14% [10–18%] consuming daily). All other food groups were consumed by <10% of the sample daily (fruit, nuts, eggs, fish, poultry, and meat).
Discussion
Despite disruptions to agri-supply chains and labor mobility due to the pandemic [12], and major new policy initiatives to support development of the agriculture sector [14], we found that most farmers in a nationally representative sample did not report a change in either their cropping pattern or input use between 2019 and 2020. Among the 16% of farmers who did report cultivating a different crop in 2020 as compared to 2019, many had transitioned from growing rice to growing higher-value, nutrient-dense crops (vegetables), citing weather and the market price as underlying reasons. It was promising to find that 62% of farmers were interested in trying more sustainable farming practices. Given the recent emphasis on natural farming by the highest levels of government–including the Prime Minister of India [8,22]–this willingness among farmers to try sustainable farming practices is especially encouraging for achieving the Sustainable Development Goal 2 target, “to ensure sustainable food production systems and implement resilient agricultural practices” [23].
Lack of knowledge was the most frequently reported barrier to shifting cropping patterns. Farmers have consistently reported lack of knowledge and information as a key barrier to diversification towards high-value crops [24]. Access to knowledge and information is also an important factor in determining adaptation behaviors of farmers in response to climate-related risks [25]. Non-farm level factors such as access to inputs, credit, local markets, and road networks are also significantly related to crop choice and farm-level diversification [24,26–28]. Thus, external support, particularly in the form of farmer training and extension services, is necessary to enable farmers to make changes to their crop cultivation patterns.
This was among the first studies to evaluate the spread of COVID-19 to rural agricultural communities in India and the impact of infection on farmers’ productivity. About one-fifth (18%) of farmers reported COVID-19 symptoms in the past month (cough, fever, or shortness of breath) and among those with symptoms, 37% reported it affected their ability to work. This is likely to be an underestimate of the impact of the first wave on farmers’ productivity given that the survey asked farmers to recall symptoms in the past month, which would have referred to November-December 2020, after the first wave peaked in mid-September 2020. The second wave, which started in March 2021, was much more severe, and continued into the Kharif season of 2021. Continued monitoring of the impact of the spread of COVID-19 in rural communities is required, particularly considering the average age of farmers in India is 50 years and 18% of farmers are over 61 years old [29]–with age being the biggest single risk factor for COVID-19 morbidity and mortality.
Half of farmers in this national sample reported avoiding the use of chemicals such as fertilizers or pesticides to some extent during the Kharif season following the initial lockdown. This was surprising given that 90% of irrigated land and 63% of unirrigated land is treated with synthetic fertilizer in India and approximately 40% of agricultural land is treated with synthetic pesticides according to a national census of farmers conducted in 2016–2017, before the pandemic [6]. The lockdown affected farmers’ ability to access and afford inputs including fertilizer and pesticides [12], and this may explain why a large proportion of farmers in this sample reported avoiding their use to some extent. Moreover, this may reflect the avoidance of fertilizers and pesticides on plots used for home consumption rather than commercial plots–our survey did not differentiate between the two when asking this question. Given that only 16–17% of farmers reported a decrease in fertilizers and pesticides during the COVID-19 pandemic, further exploration of trends in the use of inputs on agricultural land–both commercial and non-commercial–is warranted.
Another key finding of this survey is the substantial interest in agroecological practices among farmers. More than half (62%) of farmers reported that they were interested in trying more sustainable farming practices such as reducing their use of synthetic fertilizers and pesticides, and the proportion was similar across farm sizes. However, the underlying drivers reported differed across farm sizes with small/marginal farmers more likely to report government schemes and the fact that their peers are practicing it, whereas large farmers were more likely to report high input costs as the reason. These findings can inform programmatic approaches to increasing adoption of these practices across India. Of note, there was variability in the proportion of farmers expressing an interest in agroecological practices across states with Gujarat and Karnataka having the lowest proportions. In contrast, in six states, more than 80% of farmers reported that they were interested in trying these practices, including Assam, Chhattisgarh, Madhya Pradesh, Odisha, Tamil Nadu, and West Bengal. Recently, several state governments have taken up policy initiatives to promote sustainable agriculture in India and the central government is providing fiscal and policy support for these initiatives [8]. For example, Odisha introduced a state organic farming policy in 2018 and has undertaken various initiatives such as an organic millet mission to link farmers to the public distribution system [30].
Prior to the COVID-19 pandemic, uptake of sustainable farming practices in India was low; less than 2% of all cultivated land was under organic farming [7,8]. A recent systematic review identified several factors influencing uptake of these practices by farmers [31]. For example, older farmers who typically have lower education levels than younger farmers are less likely to adopt sustainable farming practices [31]. Considering the average age of Indian farmers is 50.5 years according to the latest Input Survey (2016–17) [6], this may partially explain low uptake of sustainable farming practices in India. In addition, institutional factors, particularly visits from agriculture extension services, participation in training programs, and organizational membership are important determinants of uptake of sustainable farming practices [31]. We recently confirmed this in Andhra Pradesh, where meeting with government or non-governmental organization (NGO) extension agents was significantly positively associated with practicing zero-budget natural farming [32]. Farmers’ perceptions as relate to sustainable farming can also influence adoption. Farmers who perceive that sustainable farming is beneficial for environmental and human health or that it is more profitable because it reduces cultivation costs, are more likely to adopt this alternative approach [31]. Unfortunately, however, access to extension agents in India, particularly for women, sharply declined during the pandemic and farmers increasingly relied on social networks for information [33]. The lack of access to extension agents may hinder adoption of sustainable farming practices even if farmers express an interest in trying them.
This study also uncovered the most common coping strategies to manage their produce implemented by farmers during the first wave: (1) eating their own production (50%), (2) reducing the price of their agricultural products (31%), (3) finding new markets (21%), and (4) storing more (17%). A previous survey conducted in four states (Assam, Andhra Pradesh, Jharkhand, and Karnataka) in May 2020–approximately 8–9 months before our survey–found that 52% coped by finding new markets, 25% by reducing their price, 18% by consuming their own production, and just 5% by storing more [34]. The discrepancy between studies could suggest that in a nationally representative sample, farmers have less access to new markets but more access to storage facilities than that previous sample of World Vegetable Center program participants [34].
Among agricultural laborers, 43% were not able to find work during the Kharif season following the initial lockdown and about one-third reported a decrease in the number of days employed. The loss of wage income as a result of the pandemic was also reported in a previous survey of farmers across 12 states that found from June to July/August 2020, 38% of agricultural households no longer earned an income from wages [35]. Together, these findings are especially worrying because an estimated one-third of agricultural household income comes from wages in India [36].
Related to this, we also evaluated food insecurity and dietary diversity in agricultural laborers. We found a high proportion were worried about food in the past month (43%), and a notable proportion ate less than usual (21%), skipped a meal (15%), and went without eating for a whole day (6%). These proportions are only slightly lower than reported in a survey across 12 states conducted in May 2020 that found 52% of agricultural laborers worried about food in the past month, 18% skipped a meal, and 7% went without eating for a whole day [12]. This suggests that food insecurity remains a critical issue. It is promising that 75% of agricultural laborers reported receiving food rations and 44% had a kitchen garden as these may protect them from more severe food insecurity [15]. This finding is consistent with a previous study of smallholder farmers in two states (Haryana and Odisha), which found that a well-functioning Public Distribution System (PDS) for food rations and homestead gardening protected households from worsening food insecurity during the pandemic [37]. A survey of rural areas across nine states similarly found that receipt of food rations was high during the initial lockdown period: 52% of households had received free food rations multiple times [38]. Interestingly, that survey also found the same percent of respondents did not have a ration for the day of the survey (6%) [38]. Finally, a large-scale survey across 15 states also found that PDS had met the grain needs for the vast majority of households, but distribution of nutrient-dense foods such as pulses lagged behind [39].
Nonetheless, diet quality was poor–the diets of agricultural laborers in our sample largely consisted of grains, only one-fourth consumed vegetables daily, and less than one-fifth consumed high-protein foods such as pulses and eggs daily. Thus, while these agricultural laborers may have staved off hunger to some extent, they did not have nutritional security. The importance of nutritional security has been recognized in food security studies for over two decades. In fact as Hwalla et. al (2016) propose, there can be no food security without nutritional security and vice versa [40]. Our findings are similar to the existing literature which shows that households that are food insecure sacrifice the quality of food and food variety “in favor of food quantity, in order to avoid a state of absolute hunger” [40]. Moreover, a balanced diet plays a key role in building immunity against diseases such as COVID-19 [41]. Much more work is needed to improve diet quality for these vulnerable groups in India.
This study is not without limitations. The overall response rate was high (89%), however, response rates were differential by state with lower response rates in Haryana, Punjab, and NCR Delhi due to widespread farmer protests in these states at that time. Given that Haryana and Punjab are major agricultural states in India–they are often referred to as the “bread basket” of India–the lack of representation from these states is a major limitation of this study. Moreover, the average farm size in this sample was much larger than that reported in the latest Agriculture Census for India, conducted in 2015–2016, of 1.08 ha [29]. This study was also cross-sectional, conducted after the first wave of COVID-19 in 2020, which was less severe than the second wave in 2021. Nonetheless, as it is to the best of our knowledge the only nationally representative survey of farmers to be conducted during the pandemic, the findings are valuable for understanding farmers’ response to prepare for such disruptions in the future. Finally, a phone interview relying on self-report may result in biased responses. For example, farmers may over-report practicing sustainable farming practices because it is perceived of as the socially desirable response.
Indian agriculture and its farmers have proven to be resilient during the COVID-19 pandemic. While the Indian economy declined in the first quarter of 2020 by 15%, agriculture remained the only sector to grow–by 3.4% [42]–largely due to a good harvest with favorable monsoons and the exemption of agricultural activities during the lockdown. However, the sector is not without major challenges. Diet quality remains poor, soils are degraded, groundwater levels continue to drop, and greenhouse gas emissions continue to increase [43].
With these growing concerns, India must look at a paradigm shift in producing and consuming food. This study found that despite the severe agri-supply chain constraints stemming from the pandemic, farmers did not find it feasible or were not motivated to change their cropping patterns or input-intensive practices, though about half of farmers reported already trying to avoid the use of chemicals to some extent. The policy structure in India continues to favor intensification of a limited number of staple crops–especially rice and wheat. An encouraging finding was the substantial interest in sustainable agricultural practices among farmers, which, if scaled, have the potential to improve farmers’ livelihood, reduce environmental externalities, and increase resilience.
Materials and methods
Sampling strategy
The sampling frame used for this survey was a sub-set of a nationally representative survey–the Indian Residential Energy Survey (IRES)–conducted by the Council on Energy, Environment and Water between November 2019 and March 2020 [44]. The original IRES study was conducted to describe the state of energy access and energy-use patterns across Indian households.
IRES surveyed 14,850 households across 152 districts in the 21 most-populous states of India, which account for 97% of the Indian population. The study used stratified multi-stage probability sampling. The primary sampling units (PSU) were villages in rural areas and wards in urban areas, according to the 2011 Census. Within each state, a select number of districts (d) were sampled randomly from d/2 number of strata. Within each of the sampled districts, two basic strata were formed: (i) rural strata comprised of all rural areas of the district and (ii) urban strata comprised of all urban areas of the district. In each district, a total of 12 PSUs were sampled from the urban and rural sampling frames, proportional to the urban and rural population in the district. From each PSU, eight households were randomly surveyed. An equal number of households were sampled from each of the sampled districts.
The IRES survey collected details on the primary source of income for the household. Those reporting agriculture and agricultural labor were contacted for this follow-up survey. There are primarily two cropping seasons in India: Kharif, which runs from May to mid-October, and Rabi, which runs from mid-October to mid-April. Our survey focused on the Kharif season. Participants who matched the IRES database and cultivated land or worked as agricultural laborers in the 2020–2021 Kharif season were included. Those who owned land, but leased it out to someone else during the 2020–2021 Kharif season were excluded.
Data collection
Surveys were conducted via phone interview between 1 December 2020 and 10 January 2021 using SurveyToGo (Dooblo Ltd, Kefar Sava, Israel). The same survey agency that conducted the original IRES survey was contracted to collect the data (Market Xcel Data Matrix Pvt Ltd, New Delhi, India). The survey took, on average, about 20 minutes to complete.
The survey is provided in the Supporting Information (S1 Text). Briefly, the survey had four sections. The first section included questions on landholding amount, amount of land cultivated in the current and last Kharif season, reason for change in amount of land cultivated (if applicable), what crops were cultivated in the current and last Kharif season, reason for change in type of crop cultivated and whether the participant thought it was a permanent change (if applicable), reason for sticking with the same type of crop (if applicable), whether there was a change in fertilizer or pesticide use between the current and last Kharif season, reason for change in fertilizer or pesticide use (if applicable), whether there was a change in labor availability between the current and last Kharif season, whether the participant had a kitchen garden for home consumption, what is grown in the kitchen garden (if applicable), and problems accessing bank credit. The second section included questions on coping strategies, agroecological practices, interest in trying agroecological practices, and reason for interest (if applicable). The third section included questions for agricultural laborers on receipt of support, finding work, changes in number of days of work and wage rate between the current and last Kharif season, food insecurity, and dietary intake. The fourth section included questions on COVID-19 symptoms and whether the symptoms had affected the participant’s ability to work.
Questions on agricultural practices were adapted from Government of India surveys [45,46]. Land values were reported in local units and converted into hectares (S4 Table). Four farm size categories were defined according to land ownership as landless (0 ha), small/marginal farms (0.01–2.00 ha), medium farms (2.01–4.00 ha), and large farms (>4.00 ha) [29]. The questions on practice and interest in agroecological practices was framed as: ‘Do you follow any practices in agriculture where you avoid using chemicals such as fertilizers or pesticides, like organic farming?’
Food security was assessed using three questions from the Food and Agriculture Organization’s (FAO) Food Insecurity Experience Scale (FIES) [47,48]: in the past month, was there a time when you or others in your household (1) worried you would run out of food, (2) skipped a meal, or (3) went without eating for a whole day. Only three of the eight FIES questions were asked based on previous experiences administering these questions to farmers in India [12] that suggested they are very sensitive questions and cause participant discomfort. Questions on food consumption were adapted from the FAO’s Minimum Dietary Diversity for Women (MDD) [49]. Eight of the ten MDD food groups were included: (1) starchy staples (rice, wheat, and potatoes), (2) pulses, (3) nuts, (4) vegetables, (5) fruits, (6) dairy, (7) eggs, and (8) fleshy foods (meat, poultry, and fish). Those who consumed a food group every day in the past week were assigned a value of “1” and those who did not were assigned a value of “0.” Values were then summed across the eight food groups such that the dietary diversity score ranged from 0 to 8 with 8 representing maximum dietary diversity. Low dietary diversity was defined as a dietary diversity score less than 4.
Household demographic data were from the baseline IRES survey and included rural versus urban residence; age and gender of the participant; educational attainment of the primary income earner of the household; caste; household size; and whether or not they had a BPL or Antyodaya ration card.
Ethics
This study was reviewed and approved by the Institutional Review Board of the Centre for Media Studies (Protocol #: IRB00006230). Verbal informed consent was obtained from all participants.
Statistical analysis
All analyses were conducted using Stata Statistical Software, Release 16.1 (StataCorp LLC, College Station, Texas, USA). Less than 5% of data were missing for all variables (S5 Table). State-wise analyses excluded states with sample sizes <100, including Haryana, Himachal Pradesh, Jharkhand, Kerala, Delhi, Punjab, and Uttarakhand (S1 Table). Descriptive statistics were used to summarize demographic characteristics, agricultural practices, food insecurity, dietary diversity, and COVID-19 symptoms, overall and by farm size and state. Values were reported as a weighted percent (95% CI). The weighted percents were calculated as weighted means of indicator variables (e.g., proportions) using Stata’s estimation commands for survey data (e.g., svy). The 95% CIs were logit-transformed CIs derived from the standard errors of those means. Details of the IRES sampling weight derivation are described elsewhere [44]. Briefly, a sampling weight was derived for each participating household. The sampling weight equals the number of households in the population that the household represents, estimated as the reciprocal of the probability of selecting that household for the IRES sample. The IRES sampling weights were then adjusted for non-response to the COVID-19 survey using inverse propensity scores derived from a binary logistic regression model based on background characteristics of the participants [50]. We tested for differences in characteristics according to farm size using Pearson’s chi-squared tests, which are corrected for the survey design [51,52]. A two-sided p<0.05 was considered statistically significant.
Supporting information
S2 Table. State-wise agricultural practices during the Kharif season in 2020 and 2019 among land-owning farmers in India.
https://doi.org/10.1371/journal.pstr.0000026.s002
(DOCX)
S3 Table. State-wise coping strategies during the COVID-19 pandemic and interest in agroecology among land-owning farmers in India.
https://doi.org/10.1371/journal.pstr.0000026.s003
(DOCX)
S4 Table. Land conversion factors from hextobinary.com (accessed 17 February and 11 May 2021).
https://doi.org/10.1371/journal.pstr.0000026.s004
(DOCX)
Acknowledgments
We would like to sincerely thank the many farmers and agricultural laborers who responded to our survey. We would also like to express our thanks to the enumerators, without whom this study would not have been possible.
References
- 1.
Our World in Data. Daily new confirmed COVID-19 deaths per million people Oxford: University of Oxford; 2022 [cited 2022 May 17]. Available from: https://ourworldindata.org/explorers/coronavirus-data-explorer?facet=none&Metric=Confirmed+deaths&Interval=7-day+rolling+average&Relative+to+Population=true&Color+by+test+positivity=false&country=~OWID_WRL.
- 2. Chen C, Haupert SR, Zimmermann L, Shi X, Fritsche LG, Mukherjee B. Global Prevalence of Post COVID-19 Condition or Long COVID: A Meta-Analysis and Systematic Review. J Infect Dis. 2022. Epub 2022/04/17. pmid:35429399; PubMed Central PMCID: PMC9047189.
- 3. Miroudot S. Reshaping the policy debate on the implications of COVID-19 for global supply chains. Journal of International Business Policy. 2020;3(4):430–42.
- 4.
World Bank. World Development Report 2022: Finance for an Equitable Recovery. Washington DC: The World Bank; 2022.
- 5.
World Bank. Employment in agriculture (% of total employment) (modeled ILO estimate) Washington, DC: World Bank; 2019 [cited 2021 June 16]. Available from: https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS.
- 6.
Agriculture Census Division. All India Report on Input Survey 2016–17. New Delhi: Ministry of Agriculture & Farmers Welfare, 2021.
- 7.
Gupta N, Pradhan S, Jain A, Patel N. Sustainable Agriculture in India 2021: What We Know and How to Scale Up. New Delhi: Council on Energy, Environment and Water, 2021.
- 8.
NITI Aayog. Natural farming New Delhi: NITI Aayog,; 2021 [cited 2022 January 20]. Available from: https://naturalfarming.niti.gov.in/.
- 9. Srivastava SK, Chand R, Singh J. Changing Crop Production Cost in India: Input Prices, Substitution and Technological Effects. Agricultural Economics Research Review. 2017;30(Conference):265259.
- 10. Madhukar A, Kumar V, Dashora K. Spatial and Temporal Trends in the Yields of Three Major Crops: Wheat, Rice and Maize in India. International Journal of Plant Production. 2020;14(2):187–207.
- 11.
Ministry of Statistics & Programme Implementation. India—Situation Assessment Survey of Agricultural Households, January—December 2013, NSS 70th Round New Delhi: Ministry of Statistics & Programme Implementation,; 2019 [cited 2021 February 8]. Available from: http://microdata.gov.in/nada43/index.php/catalog/133.
- 12. Jaacks LM, Veluguri D, Serupally R, Roy A, Prabhakaran P, Ramanjaneyulu GV. Impact of the COVID-19 pandemic on agricultural production, livelihoods, and food security in India: baseline results of a phone survey. Food Secur. 2021:1–17. Epub 2021/05/19. pmid:34002117; PubMed Central PMCID: PMC8116443.
- 13.
USDA. India—Organic Industry Market Report—2021. New Delhi,: United States Department of Agriculture, Foreign Agricultural Service, 2021 Contract No.: IN2021-0095.
- 14.
Ministry of Finance. Finance Minister announces measures to strengthen Agriculture Infrastructure Logistics, Capacity Building, Governance and Administrative Reforms for Agriculture, Fisheries and Food Processing Sectors New Delhi: Press Information Bureau; 2020 [cited 2022 January 20]. Available from: https://pib.gov.in/PressReleasePage.aspx?PRID=1624153.
- 15. Connors K, Jaacks LM, Prabhakaran P, Veluguri D, Ramanjaneyulu GV, Roy A. Impact of Crop Diversity on Dietary Diversity Among Farmers in India During the COVID-19 Pandemic. Frontiers in Sustainable Food Systems. 2021;5(192).
- 16. Murhekar MV, Bhatnagar T, Selvaraju S, Rade K, Saravanakumar V, Vivian Thangaraj JW, et al. Prevalence of SARS-CoV-2 infection in India: Findings from the national serosurvey, May-June 2020. Indian J Med Res. 2020;152(1 & 2):48–60. Epub 2020/09/22. pmid:32952144; PubMed Central PMCID: PMC7853249.
- 17.
Mohanan M, Malani A, Krishnan K, Acharya A. Prevalence of COVID-19 in rural versus urban areas in a low-income country: findings from a State-Wide study in Karnataka, India. University of Chicago, Becker Friedman Institute for Economics Working Paper. 2021;(2021–92).
- 18.
Federation of Indian Chambers of Commerce & Industry (FICCI). Labour in Indian Agriculture: A Growing Challenge. New Delhi: FICCI, 2015.
- 19. Adhikari P, Araya H, Aruna G, Balamatti A, Banerjee S, Baskaran P, et al. System of crop intensification for more productive, resource-conserving, climate-resilient, and sustainable agriculture: experience with diverse crops in varying agroecologies. International Journal of Agricultural Sustainability. 2018;16(1):1–28.
- 20. Gillespie S, Poole N, van den Bold M, Bhavani RV, Dangour AD, Shetty P. Leveraging agriculture for nutrition in South Asia: What do we know, and what have we learned? Food Policy. 2019;82:3–12. https://doi.org/10.1016/j.foodpol.2018.10.012.
- 21. Sibhatu KT, Qaim M. Meta-analysis of the association between production diversity, diets, and nutrition in smallholder farm households. Food Policy. 2018;77:1–18.
- 22.
Prime Minister Narendra Modi, editor Prime Minister’s Address (Virtual). National Conclave on Natural Farming; 2021 December 16; Anand, Gujarat, India.
- 23.
United Nations. Goal 2: Zero Hunger. Goal 2 Targets. New York: United Nations,; 2022 [cited 2022 January 23]. Available from: https://www.un.org/sustainabledevelopment/hunger/.
- 24.
Haque TB M; Sinha G; Kalra P; Thomas S;. Constraints and Potentials of Diversified Agricultural Development in Eastern India. New Delhi: Council for Social Development, 2010.
- 25.
Bahinipati CS, Patnaik U. What Motivates Farm Level Adaptation in India? A Systematic Review. In: Haque E, editor. Climate change and community resilience Insights from South Asia: Springer; 2021.
- 26. Kumar A, Kumar P, Sharma AN. Crop diversification in Eastern India: Status and determinants. Indian Journal of Agricultural Economics. 2012;67(902-2016-66732).
- 27. Birthal PS, Hazrana J, Negi DS. Diversification in Indian agriculture towards high value crops: Multilevel determinants and policy implications. Land Use Policy. 2020;91:104427.
- 28. Nagarajan L, Smale M, Glewwe P. Determinants of millet diversity at the household-farm and village-community levels in the drylands of India: the role of local seed systems. Agricultural Economics. 2007;36(2):157–67.
- 29.
Department of Agriculture C, and Farmers Welfare;. All India Report on Agriculture Census 2015–16. New Delhi: Ministry of Agriculture and Farmers Welfare, Government of India, 2020.
- 30. Kumar V. How Indian states are promoting organic, natural farming New Delhi: Down To Earth; 2020 [cited 2022 January 23]. Available from: https://www.downtoearth.org.in/blog/agriculture/how-indian-states-are-promoting-organic-natural-farming-73306.
- 31. Priya Singh SP. Factors Influencing the Adoption of Sustainable Agricultural Practices: A Systematic Literature Review and Lesson Learned for India. Forum for Social Economics. 2022:1–17.
- 32. Jaacks LM, Serupally R, Dabholkar S, Venkateshmurthy NS, Mohan S, Roy A, et al. Impact of large-scale, government legislated and funded organic farming training on pesticide use in Andhra Pradesh, India: a cross-sectional study. The Lancet Planetary Health. 2022;6(4):e310–e9. pmid:35397219
- 33. Alvi M, Barooah P, Gupta S, Saini S. Women’s access to agriculture extension amidst COVID-19: Insights from Gujarat, India and Dang, Nepal. Agricultural Systems. 2021;188:103035.
- 34. Harris J, Depenbusch L, Pal AA, Nair RM, Ramasamy S. Food system disruption: initial livelihood and dietary effects of COVID-19 on vegetable producers in India. Food Security. 2020. pmid:32837650
- 35. Pandya NV, Divya Roy, Aditi Prabhakaran, Poornima Jaacks, Lindsay M. Economic Impact of the 2020 COVID-19 Lockdown on Indian Farmers. EPW. 2021;56(50):31–4.
- 36.
NABARD. NABARD All India Rural Financial Inclusion Survey 2016–17. Mumbai: National Bank for Agriculture & Rural Development (NABARD), 2018.
- 37. Ceballos F, Kannan S, Kramer B. Impacts of a national lockdown on smallholder farmers’ income and food security: Empirical evidence from two states in India. World Development. 2020;136:105069.
- 38.
Rapid Community Response to COVID-19 (RCRC). Resilient Communities. RCRC Centre for Monitoring Rural India during COVID-19 Times. RCRC Hosehold Survey. May 2020. New Delhi: RCRC, 2020.
- 39.
Dalberg. Efficacy of government entitlements for low income families during Covid 19. Mumbai: Dalberg, 2020.
- 40. Hwalla N, El Labban S, Bahn RA. Nutrition security is an integral component of food security. Frontiers in Life Science. 2016;9(3):167–72.
- 41. Calder PC. Nutrition, immunity and COVID-19. BMJ Nutrition, Prevention & Health. 2020:bmjnph-2020-000085. pmid:33230497
- 42.
Ministry of Finance. Indian Agriculture contributes to green shoots of the Indian Economy with a Growth Rate of 3.4 Per Cent Despite COVID-19 Pandemic New Delhi: Press Information Bureau; 2021 [cited 2022 January 24]. Available from: https://pib.gov.in/PressReleasePage.aspx?PRID=1693205.
- 43. Veluguri DR GV; Jaacks LM. Statewise Report Cards on Ecological Sustainability of Agriculture in India. Economic & Political Weekly. 2019;54(26–27):1–9.
- 44.
Agrawal SM, Sunil Jain, Abhishek Ganesan, Karthik Urpelainen, Johannes India Residential Energy Survey (IRES) 2020. Design and data quality. New Delhi Council on Energy, Environment and Water (CEEW), 2020.
- 45.
Ministry of Agriculture GoI. Agriculture Census 2015–16: Manual of Schedules and Instructions for Data Collection. New Delhi, India: Government of India, 2015.
- 46.
Ministry of Statistics & Programme Implementation. National Sample Survey (NSS), 70th round. New Delhi: Government of India; 2013.
- 47.
Ballard TJ, Kepple AW, Cafiero C. The food insecurity experience scale: development of a global standard for monitoring hunger worldwide. Rome: Food and Agriculture Organization 2013.
- 48. Cafiero C, Viviani S, Nord M. Food security measurement in a global context: The food insecurity experience scale. Measurement. 2018;116:146–52.
- 49.
FAO. Minimum dietary diversity for women: a guide for measurement. Rome: FAO, 2016.
- 50.
Potter F, Grau E, Williams S, Diaz-Tena N, Carlson BL, editors. An application of propensity modeling: Comparing unweighted and weighted logistic regression models for nonresponse adjustments. Proceedings of the Survey Research Methods Section American Statistical Association; 2006.
- 51. Rao JN, Scott AJ. The analysis of categorical data from complex sample surveys: chi-squared tests for goodness of fit and independence in two-way tables. Journal of the American Statistical Association. 1981;76(374):221–30.
- 52. Rao JN, Scott AJ. On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Ann Statist. 1984;12:46–60.