Enhancing the livelihoods of small-scale paddy farmers in sri lanka through computational approaches for inclusive and equitable agriculture
Sri Lanka Institute of Information Technology, Department of Computer Science and Software Engineering, Malabe, Western Province, Sri Lanka.
Research Article
World Journal of Advanced Research and Reviews, 2023, 20(01), 882-893
Publication history:
Received on 02 September 2023; revised on 14 October 2023; accepted on 16 October 2023
Abstract:
Paddy cultivation, also known as rice cultivation, contributes significantly to Sri Lanka's food security and economic prosperity. Nevertheless, a number of challenges exist in the practice, such as insufficient furrow irrigation techniques, inefficient fertilizer subsidy distribution, a lack of yield prediction models, and limited access to research findings. In order to address these concerns, this research proposes an integrated system with four components. An application for furrow irrigation planning is included in the first component, utilizing support vector machine algorithms and random forest algorithms to optimize irrigation paths. Second, a priority-based fertilizer subsidy system is introduced, employing Gradient Boosting to allocate subsidies efficiently based on farmers' needs. The third component focuses on improving the dissemination of research findings by employing text summaries in order to make the findings more accessible to small-scale farmers. In the fourth component, a yield prediction model is implemented using a Random Forest algorithm that takes into account climatic and soil variables in order to forecast expected yields. The integrated system aims to enhance the efficiency, productivity, and profitability of paddy farming in Sri Lanka, providing practical solutions to challenges faced by farmers. By adopting these innovations, farmers can make informed decisions and optimize their agricultural practices, leading to sustainable rice production and economic growth.
Keywords:
Paddy cultivation; Small-scale farmers; Fertilizer subsidy distribution; Random Forest algorithms; Gradient Boosting; Sustainable rice production
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0