Abstract
Forecasting susceptibility to fruit rot disease in areca nut through the analysis of weather data using machine learning techniques. The research uses data from the OpenWeatherMap API, with a specific focus on important factors like precipitation, highest temperature, and moisture levels. Research uses machine learning models to predict disease scores and categorize disease severity levels. The information is divided into separate training and testing sets, then utilized to teach the models how to predict disease outcomes using weather data
Abstract from the paper’s OpenAlex record; open copy licensed public-domain. Read at the source ↗
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Claims 0
Judged insufficient_evidence: unclear endpoint — claims were not extracted. This is a scope decision by the model, not a statement about the paper’s findings.