A metafrontier approach and fractional regression model to analyze the environmental efficiency of alternative tillage practices for wheat in Bangladesh

• Published in: Environmental science and pollution research international Vol. 29; no. 27; pp. 41231 - 41246
• Main Authors: Aravindakshan, Sreejith, AlQahtany, Ali, Arshad, Muhammad, Manjunatha, A. V., Krupnik, Timothy J.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2022; Springer Nature B.V
• Subjects: Agricultural development; Agricultural practices; Agricultural production; Agriculture; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Bangladesh; Conservation tillage; Crop production; Cultivation; Earth and Environmental Science; Economic analysis; Economic factors; Ecotoxicology; Efficiency; Emissions; Emissions control; Energy consumption; Environment; Environmental Chemistry; Environmental Health; Environmental science; Farm buildings; Farmers; Farms; Fertilizers; Fertilizers - analysis; Grain cultivation; Greenhouse gases; Greenhouse Gases - analysis; Methane - analysis; Nitrous Oxide - analysis; Nutrients; Regression models; Research Article; Seeders; Social factors; Socioeconomic factors; Socioeconomics; Soil; Soil conservation; Tillage; Triticum; Waste Water Technology; Water Management; Water Pollution Control; Wheat; Bangladesh; Directional distance function; Greenhouse gas emission; Climate smart agriculture, Sustainable intensification, Conservation tillage; Fractional regression model
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-021-18296-3

Among alternative tillage practices, conservation tillage (CT) is a prominent greenhouse gas (GHG) mitigation strategy advocated in wheat cultivation, largely because of its low energy consumption and minimum soil disturbance during cultural operations. This paper examines the agricultural production and GHG emission trade-off of CT vis-à-vis traditional tillage (TT) on wheat farms of Bangladesh. Using a directional distance function approach, the maximum reduction in GHG emissions was searched for within all available tillage technology options, while increasing wheat production as much as possible. The underlying institutional, technical, and other socio-economic factors determining the efficient use of CT were analyzed using a fractional regression model. The average meta-efficiency score for permanent bed planting (PBP) and strip tillage (ST) was  0.89, while that achieved using power tiller operated seeders (PTOS) is 0.87. This indicates that with the given input sets, there is potential to reduce GHG emissions by about 11% for ST and PTOS; that potential is 13% for farmers using PTOS. The largest share of TT farmers cultivate wheat at lower meta-efficiency levels (0.65–0.70) compared to that observed with farmers practicing CT (0.75–0.80). Fractional regression model estimates indicate that an optimal, timely dose of fertilizers with a balanced dose of nutrients is required to reduce GHG emissions. To develop climate smart sustainable intensification strategies in wheat cultivation, it is important to educate farmers on efficient input management and CT together. Agricultural development programs should focus on addressing heterogeneities in nutrient management in addition to tillage options within CT.