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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Bibliografische gegevens
Hoofdauteurs:	Ali Mokhtar, Hongming He, Mohsen Nabil, Saber Kouadri, Ali Salem, Ahmed Elbeltagi
Formaat:	Artikel
Taal:	English
Gepubliceerd in:	Nature Portfolio 2024-06-01
Reeks:	Scientific Reports
Onderwerpen:	Climate change Vegetation indices Food security Hybrid machine learning models Rice production
Online toegang:	https://doi.org/10.1038/s41598-024-64269-0

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