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Inicio  /  Applied Sciences  /  Vol: 9 Par: 22 (2019)  /  Artículo
ARTÍCULO
TITULO

Predicting Rice Pest Population Occurrence with Satellite-Derived Crop Phenology, Ground Meteorological Observation, and Machine Learning: A Case Study for the Central Plain of Thailand

Sukij Skawsang    
Masahiko Nagai    
Nitin K. Tripathi and Peeyush Soni    

Resumen

Integration of ground-based weather variables, satellite-derived host-plant phenology and ANN modelling were applied for rice pest warning and prediction to support an integrated pest management (IPM) programme in the central plain of Thailand.

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