Abstract
Augmenting greenhouse gas (GHG) emissions into paddy production efficiency measurements suggests possible GHG reduction through optimal utilization of input resources. For this, the study aims to identify the resource use efficiency of the paddy farmers and the level of overused inputs. Based on the findings, the study adopted three new technologies and identified their impact on crop productivity and economic return with the help of a technology verification trial. The study collected primary data from 153 farmers through a face-to-face questionnaire for resource use efficiency estimation. A slack-based Data Envelopment Analysis (SBM-DEA) model was used to measure the efficiency score (with and without considering GHG emissions as undesirable output) and the level of overused inputs. The resulting mean efficiency score (considering the undesirable outputs) of 0.63 indicates that smallholder paddy growers were eco-inefficient with space to improve input use like the seed, diesel, electricity, and nitrogen fertilizer (N-fertilizer). To optimize input use, minimize GHG emission, and improve paddy yield, three technologies (high-yielding seed variety, systemic rice intensification (SRI), and SPAD-based N management) were adopted and tested through a technology verification trial. Results indicate that adopting three technologies produced 6.12 tons ha−1 of paddy compared to 4.22 tons ha−1 paddy through farmers’ conventional practices. Hence, developing participatory research among agricultural experts and farmers can bring sustainable agricultural development.
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Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Notes
The resource use efficiency defined as the ratio of dry matter generated to nutrients consumed is the inverse of nutrient concentration in plant tissue (Chapin, 1980). Fundamentally, resource use efficiency refers to increasing agricultural outputs while utilising less nutrients, water, land, energy, capital, and labor.
A group of people, departments, or divisions within an organization that collaboratively decides how to allocate resources and produce something is known as a decision-making unit (DMU). The fundamental analytical units in DEA are known as DMUs, and they are made up of decision-makers, decision inputs, and decision outputs.
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Dey, S., Abbhishek, K. & Swain, D.K. Resource Use Efficiency Estimation and Technology Verification Trial for Sustainable Improvement in Paddy Production: An Action-Based Research. Int. J. Plant Prod. 17, 337–352 (2023). https://doi.org/10.1007/s42106-023-00243-6
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DOI: https://doi.org/10.1007/s42106-023-00243-6