Unveiling the Food and Income Insecurity among Farm Households of Lucknow, Uttar Pradesh

S C Ravi, Maneesh Mishra, Rohit Jaiswal, Arnab Roy, Shantanu Kumar Dubey, T Damodaran
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Abstract

The study was conducted during 2022-23 to assess the level of food insecurity and income status among farm households. Data from 474 farmers through personal interview method were collected. Agriculture was the primary occupation for most households followed by off-farm activities. Average per capita annual income (Rs. 1,00,073) was lower than the national average. The per capita annual income was Rs. 73,303, Rs. 93,256 and Rs. 1,44,456 for marginal, small, and medium farmers, respectively. About 47 per cent of the expenditure was made on consumption. A comparison of calorie intake to recommended calorie intake indicated that food insecurity was prevailing among 26 percent of the farmers. The major contribution to calorie intake was from cereals, the consumption of vegetables and fruits was low. A decision tree model using machine learning algorithms was used to identify the factors influencing food security. Per capita income, family size, consumption expenditure, social participation, and land holdings had significant importance in classifying the households as food secure and insecure. Diversifying farm activities and creating additional opportunities in rural areas, teaching households about balanced diets, promoting home gardening, and institutional policies to improve food security may be the strategic points.
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揭示了北方邦勒克瑙农户的粮食和收入不安全
该研究于2022年至2013年进行,旨在评估农户的粮食不安全水平和收入状况。采用个人访谈法对474名农民进行数据收集。农业是大多数家庭的主要职业,其次是非农活动。人均年收入(100,073卢比)低于全国平均水平。边际农民、小农和中等农民的人均年收入分别为73,303卢比、93,256卢比和144,456卢比。大约47%的开支用于消费。卡路里摄入量与推荐卡路里摄入量的比较表明,26%的农民普遍存在粮食不安全问题。卡路里摄入量的主要来源是谷物,蔬菜和水果的摄入量很低。采用机器学习算法的决策树模型识别影响粮食安全的因素。人均收入、家庭规模、消费支出、社会参与和土地持有在将家庭划分为粮食安全家庭和粮食不安全家庭方面具有重要意义。使农业活动多样化并在农村地区创造更多机会,向家庭传授均衡饮食,促进家庭园艺,以及制定改善粮食安全的体制政策,这些可能是战略要点。
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