Predicting rice diseases across diverse agro-meteorological conditions using an artificial intelligence approach.

ABSTRACT: With the aid of a plant disease forecasting model, the emergence of plant diseases in a given region can be predicted ahead of time. This makes it easier to take proactive steps to reduce losses before they occur. The proposed model attempts to find an association between agrometeorological parameters and the occurrence of the four types of rice diseases. Rice is the staple food of people in Maharashtra. The four major diseases that occur on rice crops are focused on this paper (namely Rice Blast, False Smut, Bacterial Blight and Brown Spot) as these diseases spread rapidly and lead to economic loss. This research paper demonstrates the usage of artificial neural network (ANN) to detect, classify and predict the occurrence of rice diseases based on diverse agro-meteorological conditions. T

SUBMITTER: Patil RR 

PROVIDER: S-EPMC8444092 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature