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In present - day agriculture, weather based forewarning systems have become a vital tool in combating pests and diseases. These systems forecast the occurrence and severity of important insect pests and diseases using the meteorological data provided. The data regarding important meteorological variables like temperature, rainfall, humidity, wind speed, and wind patterns are integrated in these systems. As forewarning systems use highly developed artificial intelligence technology, historical data analysis and pest-weather correlations to provide precise and timely insights to the farmer community, which enable them to take appropriate control measures when required and help in reducing crop losses and optimising the pesticide usage. These will help to schedule pesticide applications as needed, ultimately reducing the quantity of pesticides sprayed and their detrimental impact on the environment and other beneficial organisms and increasing the overall agricultural output, which is very important in sustainable agriculture. To unlock the full potential of these systems, issues regarding data availability, localizing the systems to particular regions, and the effects of climate change should be addressed.
Dasari et al. (Sat,) studied this question.