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Library Synergies and Determinants of Sustainable Intensification Practices in Pakistani Agriculture

Synergies and Determinants of Sustainable Intensification Practices in Pakistani Agriculture

Synergies and Determinants of Sustainable Intensification Practices in Pakistani Agriculture
Volume 9 Issue 4

Resource information

Date of publication
April 2020
Resource Language
ISBN / Resource ID
10.3390/land9040110
License of the resource

Sustainable intensification practices (SIPs) involve a process to produce high yields for existing land without affecting the environment. The significance and relevance of SIPs in a Pakistani context demands an investigation. Hence, this study takes the initiative to investigate the determinants regarding the adoption of these practices. Based on the evidence, we selected five SIPs, namely, improved seeds, organic manure, crop rotation, intercropping, and low tillage. Furthermore, this study analyzes the adoption of SIPs with randomly collected data from 612 farmers through multistage sampling. A multivariate probit model (MVP) is employed to analyze the mutually dependent adoption decisions and identify the factors associated with them. The results revealed that education, the area under cultivation, access to information, extension access, social participation, rainfall variability, and temperature increase significantly predict the adoption of SIPs. The adoption of organic manure and crop rotation was highest between all the ecological zones, whereas low tillage was the least adopted practice. Adoption intensity in mixed cropping zones was slightly higher than the other ecological zones. Moreover, the findings also reveal the important synergies amid natural resource management and input-based SIPs. Hence, the study highlights the perseverance and importance of social groups and recommends the government to formulate comprehensive policies to facilitate institutional access and elevate the adoption level amongst the farming community.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Jabbar, Awais
Wu, Qun
Peng, Jianchao
Zhang, Jian
Imran, Asma
Yao, Luo

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Data Provider
Geographical focus