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

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Abstract

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.

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Acknowledgements

This study was conducted as part of the Cereal Systems Initiative for South Asia in Bangladesh (CSISA-BD) project, funded by the United States Agency for International Development (USAID) in Bangladesh, and the USAID-Washington and Bill and Melinda Gates Foundation (BMGF) funded CSISA Phase II and III projects. The data collection of this study was partly supported by the Erasmus Mundus programme of the European Commission (EC). The first author received non-financial research support from the Farming Systems Ecology (FSE) group at the Wageningen University and Research (WUR), Netherlands. The third author received financial and administrative support from Leibniz Center for Agricultural Landscape Research (ZALF), Müncheberg, Germany, during the preparation of the manuscript. The third author also acknowledges financial support from Alexander von Humboldt Foundation under the award No. (Ref 3.5-DEU-1212362-FLF-P). The views presented in this paper do not necessarily represent those of USAID or BMGF and shall not be used for advertising purposes.

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Authors and Affiliations

  1. Farming Systems Ecology (FSE), Wageningen University and Research Centre, Wageningen, The Netherlands

    Sreejith Aravindakshan

  2. Arunachal University of Studies (AUS), Knowledge City, Namsai, Arunachal Pradesh, 792103, India

    Sreejith Aravindakshan

  3. Department of Urban & Regional Planning, College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam, 31441, Saudi Arabia

    Ali AlQahtany

  4. Department of Economics, School of Social Sciences and Humanities (S3H), National University of Sciences and Technology (NUST), 44000, Islamabad, Pakistan

    Muhammad Arshad

  5. Institute of Socio-Economics, Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany

    Muhammad Arshad

  6. Programme Monitoring and Statistics Department, Government of Karnataka, Karnataka Evaluation Authority, Planning, Bengaluru, India, 560 001

    A. V. Manjunatha

  7. International Maize and Wheat Improvement Center (CIMMYT), House-10/B, Road-53, Gulshan-2, Dhaka, 1212, Bangladesh

    Timothy J. Krupnik

Authors
  1. Sreejith Aravindakshan
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  2. Ali AlQahtany
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  4. A. V. Manjunatha
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  5. Timothy J. Krupnik
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Contributions

Sreejith Aravindakshan, Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – Original draft, Writing — review and editing, and Data visualization.

Ali AlQahtany, Methodology, Software, Validation, Writing — review and editing, and Data visualization.

Muhammad Arshad, Conceptualization, Investigation, Project administration, and Writing — review and editing.

Manjunatha A.V., Methodology, Writing — review and editing, and Data visualization.

Timothy J. Krupnik, Secured funding, Management, Conceptualization, Methodology, Writing – review and editing.

Corresponding author

Correspondence to Sreejith Aravindakshan.

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Aravindakshan, S., AlQahtany, A., Arshad, M. et al. A metafrontier approach and fractional regression model to analyze the environmental efficiency of alternative tillage practices for wheat in Bangladesh. Environ Sci Pollut Res 29, 41231–41246 (2022). https://doi.org/10.1007/s11356-021-18296-3

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