Doubling farmer's income: The case of India

Singh, Rohit

doi:10.1002/wfp2.12002

Cited by 3 publications

(3 citation statements)

References 2 publications

(1 reference statement)

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“…Additionally, poor irrigation facilities have led to steep decline in farmer's ability to carry out farming throughout the year (Singh, 2019). Farmers have a major reliance on rainfall for crop production as irrigation facilities have shown a little improvement since the reforms.…”

Section: Literature Reviewmentioning

confidence: 99%

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Farmer's income and agrarian distress: The case of India

Singh

2020

World Food Policy

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The paper analyses the effects of five distinct factors, which are responsible for high incidents of suicides among farmers in India. The study analyses the effect of ratio of net irrigated area to net sown area, average yield per hectare and expenditure by the households, and credit advanced to the farmers and proportion of food grain crops and non‐food grain crops on farmer's suicides. The study uses a panel data over 17 years (from 2001–2002 till 2017–2018) for all 28 states. The study finds that an increase in ratio of net irrigated area to net sown area, average yield and credit advanced to the farmers reduces the number of farmer suicides, whereas farmer's household expenditure and proportion of food to non‐food crops have no significant effect on suicides. Furthermore, the paper suggests that there are increased incidences of suicides by the farmers every year and the government need to amend its existing agricultural policies and work for the economic and social well‐being of the farmers, thus preventing suicides at a larger scale. The study also draws a comparison with Chinese policy at local level which may be implicated in India.

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Section: Literature Reviewmentioning

confidence: 99%

“…The records did not include agricultural laborers as they are not categorized as self‐employed and work under those who own land. Inequality is one of the major causes of farmer's suicides in rural areas (Singh, 2018, 2019). Inequality which leads to extreme poverty is the major cause of suicides among farmers.…”

Section: Literature Reviewmentioning

confidence: 99%

Farmer's income and agrarian distress: The case of India

Singh

2020

World Food Policy

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“…This sector is undergoing rapid growth due to urbanization, population growth, and, most importantly, the rise in income in developing countries. Further, the Indian policymakers also suggested self-sustainable models empowered with the more significant employment of technologies and market linkage to double farmers' income by 2022 [4].…”

Section: Introductionmentioning

confidence: 99%

Computer Vision-Based Approach for Automatic Detection of Dairy Cow Breed

et al. 2022

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Purpose: Identification of individual cow breeds may offer various farming opportunities for disease detection, disease prevention and treatment, fertility and feeding, and welfare monitoring. However, due to the large population of cows with hundreds of breeds and almost identical visible appearance, their exact identification and detection become a tedious task. Therefore, the automatic detection of cow breeds would benefit the dairy industry. This study presents a computer-vision-based approach for identifying the breed of individual cattle. Methods: In this study, eight breeds of cows are considered to verify the classification process: Afrikaner, Brown Swiss, Gyr, Holstein Friesian, Limousin, Marchigiana, White Park, and Simmental cattle. A custom dataset is developed using web-mining techniques, comprising 1835 images grouped into 238, 223, 220, 212, 253, 185, 257, and 247 images for individual breeds. YOLOv4, a deep learning approach, is employed for breed classification and localization. The performance of the YOLOv4 algorithm is evaluated by training the model on different sets of training parameters. Results: Comprehensive analysis of the experimental results reveal that the proposed approach achieves an accuracy of 81.07%, with maximum kappa of 0.78 obtained at an image size of 608 × 608 and an intersection over union (IoU) threshold of 0.75 on the test dataset. Conclusions: The model performed better with YOLOv4 relative to other compared models. This places the proposed model among the top-ranked cow breed detection models. For future recommendations, it would be beneficial to incorporate simple tracking techniques between video frames to check the efficiency of this work.

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Dynamic Relationship Between Expenditure on Finance Education, Income Gap Between Urban and Rural Residents and Agricultural Economy Level

Lin

Gao

2022

Advances in Artificial Systems for Medicine and Education V

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Doubling farmer's income: The case of India

Cited by 3 publications

References 2 publications

Farmer's income and agrarian distress: The case of India

Farmer's income and agrarian distress: The case of India

Computer Vision-Based Approach for Automatic Detection of Dairy Cow Breed

Dynamic Relationship Between Expenditure on Finance Education, Income Gap Between Urban and Rural Residents and Agricultural Economy Level

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