Integrating Ecological and Economic Indicators into Decision Support Systems for Sustainable Pest Management
DOI:
https://doi.org/10.61978/sativa.v2i1.1432Keywords:
Decision Support Systems, Sustainability Metrics, Pest Management, Proxy Indicators, Ecological Resilience, Digital AgricultureAbstract
Digital Decision Support Systems (DSS) are increasingly leveraged in agricultural pest and disease management to enhance decision-making and reduce environmental impacts. This study aims to evaluate how DSS contributes to sustainability by identifying measurable proxy indicators across ecological, economic, and behavioral dimensions. A conceptual framework was applied using secondary data from agricultural reports, scientific literature, and DSS evaluations. Sustainability was operationalized through indicators such as pesticide use frequency, Environmental Impact Quotient (EIQ), yield improvements, input cost reductions, and user adoption rates. Results reveal that DSS implementation can significantly reduce pesticide dependency, increase natural enemy populations, and enhance ecological resilience. Economically, DSS promotes input efficiency, higher productivity, and improved profitability. Behaviorally, adoption rates and user engagement correlate positively with sustainability outcomes. The study identifies barriers such as inconsistent data and limited user accessibility, while proposing design principles like real-time feedback, dynamic proxy integration, and user-centric visualization tools. In conclusion, embedding sustainability metrics into DSS enhances their potential to support environmentally sound and economically viable farming. This research offers a structured evaluation framework that informs DSS development, policymaking, and farmer adoption strategies, thereby contributing to the advancement of sustainable agriculture.
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