Assessment of Economic Sustainability of Cropping Systems in the Salt–Affected Coastal Zone of West Bengal, India

Krishnendu Ray, Suman Mondal, Md. Jahangir Kabir, Sukamal Sarkar, Kalyan Roy, Koushik Brahmachari, Argha Ghosh, Manoj K. Nanda, Sanchayeeta Misra, Supriya Ghorui, Rupak Goswami and Mohammed Mainuddin ()
Additional contact information
Krishnendu Ray: Sasya Shyamala Krishi Vigyan Kendra, Ramakrishna Mission Vivekananda Educational & Research Institute, Arapanch, Sonarpur 700150, India
Suman Mondal: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Md. Jahangir Kabir: Business School, University of New England, Armidale, NSW 2351, Australia
Sukamal Sarkar: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Kalyan Roy: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Koushik Brahmachari: Department of Agronomy, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur 741252, India
Argha Ghosh: Department of Agricultural Meteorology, Odisha University of Agriculture and Technology (OUAT), Bhubaneswar 751003, India
Manoj K. Nanda: Department of Agricultural Meteorology, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur 741252, India
Sanchayeeta Misra: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Supriya Ghorui: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Rupak Goswami: School of Agriculture and Rural Development, Ramakrishna Mission Vivekananda Educational & Research Institute, Narendrapur Campus, Kolkata 700103, India
Mohammed Mainuddin: Water Security Program, CSIRO Environment, Black Mountain Science and Innovation Park, Canberra, ACT 2601, Australia

Sustainability, 2023, vol. 15, issue 11, 1-25

Abstract: Identifying productive, profitable, and less risky cropping systems is pivotal for ensuring sustainable farm–based livelihoods in the context of climatic uncertainties and market volatility, particularly in many developing nations. Conventional field crop research often identifies the best or optimal solutions based on treatment replicates at a specific point in time without considering the influence of market volatility and climatic uncertainties. To address this gap, we conducted an assessment of productivity profitability and climate– and market–uncertainty-driven risk for eleven different rice-based cropping systems (eight existing and three potential systems) in the coastal region of Gosaba Block, West Bengal, India. Farmers’ observations of the best, typical, and worst seasonal yields and price data for the selected cropping systems over the last five to seven years were collected from fifty farm households. Irrespective of the scenarios, the rice–lathyrus systems, followed by rice–onion and rice–lentil systems, recorded the lowest rice equivalent yields and system yields. However, the highest rice equivalent yields and system yields were recorded for rice–chilli systems, followed by rice–tomato and rice–potato–green-gram systems. Per hectare, total paid–out cost (TPC) of rice–tomato systems was higher, followed by rice–chilli, rice–potato–green–gram, and rice–potato systems. However, irrespective of seasonal conditions (best, normal, and worst), rice–chilli systems gave a higher net return followed by rice–tomato and rice–potato–green–gram systems. The rice–fallow system recorded the lowest value for both parameters. Under the worst seasonal conditions, the rice–onion system gave a negative net return. Under all the scenarios, the rice–chilli system gave the highest benefit over cost, followed by the rice–tomato, rice–potato–green-gram, and rice–potato systems. The cumulative probability distribution (CDF) of per ha net income of the rice–tomato system showed first–degree stochastic dominance over other systems, implying that the system is economically the most profitable and less risky. Additionally, the CDF of net income per ha of the rice–chilli system showed second–degree stochastic dominance over the rest of the systems, indicating that the system is economically more profitable and less risky than other rice/non–rice cropping systems except for the rice–tomato system. Furthermore, the risk analysis results suggest that the likelihood of obtaining negative net income was nil for the selected cropping systems, except the rice–onion system had a slight chance (<1%) of providing a negative net return. Considering the productivity and economic viability (e.g., profitability and risk) of different rice–based systems, it is recommended to promote the adoption of the rice–vegetable systems, especially rice–tomato and rice–chilli from among the existing systems and rice–potato–green-gram systems from among the potential systems, for achieving sustainable intensification in these coastal saline tracts of the region.

Keywords: sustainable intensification; rice–based cropping systems; risk analysis; stochastic dominance; economic sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/11/8691/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/11/8691/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:11:p:8691-:d:1157412

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().