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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18667
Title: Uncertainty-based fuzzified environmental-socio-economic risk assessment of precision agricultural practices
Authors: Srinivas, Rallapalli
Keywords: Civil engineering
Precision agriculture (PA)
Fertilizer runoff
Crop diseases
Fuzzy fault tree analysis (FFTA)
Issue Date: Nov-2024
Publisher: Springer
Abstract: Precision agriculture (PA) is a management system that helps farmers address issues like fertilizer runoff, crop diseases, and declining yields by employing contemporary advanced technology. However, various environmental, socio-economic, and technological challenges hinder its widespread adoption. This study aims to bridge the gap between theoretical understanding of the PA techniques and their practical implementation. The present study proposes a fuzzy fault tree analysis (FFTA) based approach. The approach incorporates farmers’ willingness to adopt PA technology, presenting two novel aspects: (i) expert elicitation and fuzzy logic in fault tree analysis to estimate PA implementation failure probability, and (ii) assessment of farmer behavioral responses with uncertainties to identify critical adoption challenges. Results highlight the relative importance of challenges faced by different farmer categories. Key challenges include the high cost of technology (0.7604) and fertilizer dependence among innovators (0.7541), small landholdings among early adopters (0.7583), and resistance to new technology among late adopters (0.7637). Birnbaum’s measure effectively captured these challenges’ contributions to PA adoption failure. The proposed approach provides an ordered rank list of challenges, guiding stakeholders, researchers, and agricultural bodies to systematically address and mitigate these obstacles, enhancing PA implementation.
URI: https://link.springer.com/article/10.1007/s00477-024-02864-3
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18667
Appears in Collections:Department of Civil Engineering

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