Impact of Zero Tillage Maize Production on Yield, Income, and Resource Utilization in Peninsular India: An Action-Based Quasi-Experimental Research Provisionally Accepted
- 1Dr. Reddy's Foundation, India
- 2Indian Institute of Technology Kharagpur, India
The present study aims to identify the crucial determinants of the widespread adoption of zerotillage (ZT) technology in maize production. The study also measures the impact of ZT adoption on maize yield, income generation, and the expenses associated with different agricultural operations.The study used multi-stage stratified random sampling and conducted a face-to-face questionnaire survey to collect primary data from 1189 maize farmers. Initially, the study employed probit regression analysis to identify the ZT adoption determinants. Subsequently, using the Propensity Score Matching (PSM) approach, the study measures the impact of ZT adoption over conventional tillage in terms of yield, income, and cost management. Finally, the Endogenous Switch Regression (ESR) method was implemented to mitigate unobserved heterogeneity and sample selection bias. Additionally, ESR assessed the robustness of PSM results.The probit model identifies that variables like education, institutional credit adoption, crop insurance, visit of extension agent, landholding size, and prior experience of new technology adoption positively influence ZT adoption. The PSM and ESR approach results suggest that ZT adoption positively impacts farmers' yield and net income while reducing the cultivation cost and labor use. Results show that ZT adoption decreases the cost of land preparation, weed, pest management, and harvesting, thereby decreasing the cultivation cost by INR8376 acre -1 . Moreover, adopting ZT improves maize yield by 2.53quintal acre -1 and minimizes 9.56 persondays acre -1 .The study findings may support policymakers in designing suitable agricultural policies to improve technology adoption and motivate farmers for sustainable production.
Keywords: Conservation tillage, impact assessment, economic analysis, Propensity score matching (PSM) approach, Endogenous Switch Regression, Peninsular India
Received: 28 Dec 2023;
Accepted: 02 May 2024.
Copyright: © 2024 Dey, Abbhishek, Saraswathibatla, Singh, Sreedhar, Bommaraboyina, Raj, Kaliki, Choubey, Rongali and Upamaka. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Kumar Abbhishek, Dr. Reddy's Foundation, Hyderabad, India