Securing China’s rice harvest: unveiling dominant factors in production using multi-source data and hybrid machine learning models

Securing China’s rice harvest: unveiling dominant factors in production using multi-source data and hybrid machine learning models

Abstract Ensuring the security of China’s rice harvest is imperative for sustainable food production. The existing study addresses a critical need by employing a comprehensive approach that integrates multi-source data, including climate, remote sensing, soil properties and agricultural statistics f...

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Hlavní autoři: Ali Mokhtar, Hongming He, Mohsen Nabil, Saber Kouadri, Ali Salem, Ahmed Elbeltagi
Médium: Článek
Jazyk:English
Vydáno: Nature Portfolio 2024-06-01
Edice:Scientific Reports
Témata:
Climate change
Vegetation indices
Food security
Hybrid machine learning models
Rice production
On-line přístup:https://doi.org/10.1038/s41598-024-64269-0

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