Rice Blast (<i>Magnaporthe oryzae</i>) Occurrence Prediction and the Key Factor Sensitivity Analysis by Machine Learning

Rice Blast (<i>Magnaporthe oryzae</i>) Occurrence Prediction and the Key Factor Sensitivity Analysis by Machine Learning

This study aimed to establish a machine learning (ML)-based rice blast predicting model to decrease the appreciable losses based on short-term environment data. The average, highest and lowest air temperature, average relative humidity, soil temperature and solar energy were selected for model devel...

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Bibliographic Details
Main Authors: Li-Wei Liu, Sheng-Hsin Hsieh, Su-Ju Lin, Yu-Min Wang, Wen-Shin Lin
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Agronomy
Subjects:
rice disease
precision agriculture
artificial neural networks (ANN)
soil temperature
confusion matrix
F-measure
Online Access:https://www.mdpi.com/2073-4395/11/4/771

Internet

https://www.mdpi.com/2073-4395/11/4/771

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