Farmer-Centered Digital Advisory Models for Sustainable Crop Decisions

Aarav Mehta

Farmer-Centered Digital Advisory Models for Sustainable Crop Decisions

Author(s)	Aarav Mehta
Country	United States
Abstract	Digital agricultural advisory systems are increasingly used to deliver weather information, crop-management recommendations, pest warnings, market intelligence, and resource-use guidance to farmers. Their technical capacity has expanded rapidly, yet the practical value of these systems depends on more than the volume or speed of information delivered. Farmers make crop decisions within highly localized agronomic, economic, climatic, cultural, and household contexts. Digital platforms that treat farmers as passive recipients of standardized recommendations may therefore produce high information availability without equivalent improvements in decision confidence, trust, resource efficiency, or sustainable practice adoption. This study develops and evaluates a farmer-centered digital advisory model in which farmer preferences, local conditions, experiential knowledge, accessibility requirements, feedback, and extension support are incorporated directly into the advisory cycle. The research is structured as a simulation-based methodological study because no original field dataset was supplied. A scenario framework representing 300 hypothetical smallholder and medium-scale farmer profiles was constructed to compare a conventional one-directional digital advisory model with a farmer-centered model. Five dimensions were evaluated: decision confidence, resource-use efficiency, sustainable-practice intention, advisory trust, and advisory usability. Simulated performance scores indicate that the farmer-centered model produced higher values across all dimensions. The largest modeled improvements were observed for advisory trust and usability, suggesting that personalization alone is insufficient unless digital recommendations are understandable, explainable, locally relevant, and supported by mechanisms through which farmers can question or modify advice. The study proposes six operational principles for sustainable digital advisory: contextual personalization, multimodal accessibility, farmer–advisor interaction, transparent recommendations, adaptive feedback, and sustainability-oriented decision support. Rather than positioning digital technology as a substitute for farmers' knowledge or agricultural extension, the proposed model treats digital systems as decision partners embedded within local agricultural knowledge networks. The results are illustrative rather than empirical and should be validated through longitudinal field trials. Nevertheless, the framework provides a reproducible foundation for evaluating digital agricultural advisory platforms on farmer-centered and sustainability outcomes rather than technology adoption alone.
Keywords	digital agriculture; farmer-centered advisory; sustainable agriculture; crop decision support; agricultural extension; smallholder farmers; digital advisory services; climate-smart agriculture; decision support systems
Field	Engineering
Published In	Volume 2, Issue 3, May-June 2021
Published On	2021-05-29

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American Journal of Advanced Multidisciplinary Innovation and Research

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Farmer-Centered Digital Advisory Models for Sustainable Crop Decisions

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