Current Science

S. K. Srivastava ¹, Ramesh Chand ², Jaspal Singh ¹, Amrit Pal Kaur ¹, Rajni Jain ¹, I. Kingsly ¹, S. S. Raju ³

Affiliations
1 ICAR-National Institute of Agricultural Economics and Policy Research, DPS Marg, Pusa, New Delhi 110 012, IN
2 NITI Aayog, Government of India, New Delhi 110 001, IN
3 ICAR-Central Marine Fisheries Research Institute, Visakhapatnam 530 003, IN

Abstract

The study identifies factors behind the groundwater depletion in Punjab (India) and examines the economics of groundwater irrigation across farm-size categories, varied groundwater levels and energy policy scenario. The farm-level evidences point out that farmers with smaller land holdings incur 2-3 times groundwater cost than those with larger land holdings. Also, small farmers are affected more adversely due to falling groundwater level. Further, financial expenses in extracting groundwater are borne equally by the society and the farmers. The withdrawal of energy subsidy is expected to reduce net returns, but at a varying rate across different crops. However, crop cultivation would still be profitable and desubsidization will result in 29-82% savings in existing groundwater use in different crops.

Keywords

Crop Profitability, Energy Subsidy, Farm Economics, Groundwater Depletion.

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Prem Chand ¹, Jitender Mohan Singh ², Jatinder Sachdeva ², Jasdev Singh ², Priyanka Agarwal ¹, Rajni Jain ¹, Sulakshana Rao ³, Baljinder Kaur ²

Affiliations
1 ICAR-National Institute of Agricultural Economics and Policy Research, DPS Marg, Pusa, New Delhi 110 012, India, IN
2 Department of Economics and Rural Sociology, Punjab Agricultural University, Ludhiana 141 027, India, IN
3 CHRIST University, Bannerghatta Main Road, Hulimavu, Bengaluru 560 076, India, IN

Abstract

Increasing global water shortage emphasizes the need for demand-side water management policies, especially in the agriculture sector, being the largest consumer of freshwater. Such policies are relevant in India, where groundwater depletion may have severe implications at various socio-economic levels. In this study, using mathe­matical modelling, we assess the feasibility of two alternative irrigation water pricing policies – (i) uniform water pricing policy and (ii) differentiated water pricing policy, wherein farmers growing less water-requiring crops (<4488 m3/ha) get an incentive for saving water, while those growing water-intensive crops pay for it. Using a case study of Punjab, the breadbasket and one of the fastest groundwater-depleting states in India, alternative cropping patterns are also suggested. The findings reveal that the current rate of groundwater withdrawal could not sustain agricultural intensification in the state. Although optimization of resource allocation has the potential to save water by 8%, this alone is unlikely to break the rice–wheat mono-cropping pattern in Punjab. The analysis of two different volumetric irrigation water pricing policies shows that differentiated water pricing would be more effective in halting groundwater depletion in the state. However, adequate investment in irrigation water supply infrastructure, mainly for installing water meters, is required to implement the policy

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Preety Dagar ¹, Alka Arora ¹, Mrinmoy Ray ¹, Sudhir Kumar ², Himanshushekhar Chourasia ³, Mohit Kumar ¹, Sudeep Marwaha ¹, Rajni Jain ¹, Viswanathan Chinnusamy ²

Affiliations
1 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, IN
2 ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN
3 ICAR-Central Institute for Research on Cotton, Mumbai 400 019, IN

Abstract

In this study, a pipeline has been proposed where colour image and depth information of wheat plants are captured using an red green blue-depth (RGB-D) camera; later these two are combined to create a three-dimensional point cloud of the plant. The point clouds were processed to calculate the plant height. The results were then statistically analysed with the help of machine learning algorithms, viz. linear regression, support vector machine and artificial neural network (ANN). The comparison of the results shows that ANN performed better than the other two models with mean squared error 189.94, root mean squared error 13.70, mean absolute error 11.40 and mean absolute percentage error 18.73. The proposed study shows a high-precision and low-cost technology that can be widely used for non-destructive measurement of phenotyping parameters for wheat and other crops.

Keywords

3D reconstruction, image processing, Open3D, plant phenotyping, RGB-D imaging.

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