Kharif crops selection for sustainable farming practices in the rajasthan-india using multiple attribute-based decision-making

• Main Authors: Tirth, Vineet, Singh, Ram Karan, Islam, Saiful, Badruddin, Irfan Anjum, Abdullah, Rini Asnida, Algahtani, Ali, Mahmoud, Essam R. I., Arabi, Amir, Shukla, Neeraj Kumar, Gupta, Parul
• Format: Article
• Language: English
• Published: MDPI 2020
• Subjects: TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/93458/1/SaifulIslam2020_KharifCropsSelectionforSustainableFarming.pdf; http://eprints.utm.my/id/eprint/93458/; http://dx.doi.org/10.3390/agronomy10040536

Sustainability of agricultural practices depends on economic, environmental, and social conditions. The Rajasthan state of India has arid climatic conditions where kharif crops are commonly grown. In this work, the four major criteria are considered such as the farm area, crop yield per unit area, the cost prices, and the market sales price. Merged analytic hierarchy process (AHP) and entropy techniques have been employed to give reasonable weight coefficients for the objective and subjective weights to each criterion. Multiple attribute-based decision-making models (MADM) have been developed using three proven techniques, namely the Exprom2, the technique for order of preference by similarity to ideal solution (TOPSIS), and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The crop Pennisetum glaucum emerged as the most productive kharif crop in the arid climatic conditions of Rajasthan, India under the given criteria. The sensitivity analysis of the three methods identifies the most significant criteria and validates that Pennisetum glaucum is the first ranked crop despite the interchange of the weights. The methodology used in this study may be applied across the globe to select appropriate crops for maximizing the profit, optimizing the natural resources, and promoting sustainable agricultural practices. This study may be used to enhance the agricultural gross domestic product (GDP) to make the agriculturalists self-sufficient and to help the state policymakers in making effective regional policies.