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...
Автори: | Ali Mokhtar, Hongming He, Mohsen Nabil, Saber Kouadri, Ali Salem, Ahmed Elbeltagi |
---|---|
Формат: | Стаття |
Мова: | English |
Опубліковано: |
Nature Portfolio
2024-06-01
|
Серія: | Scientific Reports |
Предмети: | |
Онлайн доступ: | https://doi.org/10.1038/s41598-024-64269-0 |
Схожі ресурси
Схожі ресурси
-
Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images
за авторством: Haixiao Ge, та інші
Опубліковано: (2021-11-01) -
Estimation and Forecasting of Rice Yield Using Phenology-Based Algorithm and Linear Regression Model on Sentinel-II Satellite Data
за авторством: Abid Nazir, та інші
Опубліковано: (2021-10-01) -
Estimating Relative Chlorophyll Content in Rice Leaves Using Unmanned Aerial Vehicle Multi-Spectral Images and Spectral–Textural Analysis
за авторством: Yuwei Wang, та інші
Опубліковано: (2023-06-01) -
Assessing The Field Hyperspectral Remote Sensing Data To Diagnose Crop Variables In Tropical Irrigated Wetland Rice
за авторством: Muhammad Evri, та інші
Опубліковано: (2009-11-01) -
Assessing vegetation indices and productivity across nitrogen gradients: a comparative study under transplanted and direct-seeded rice
за авторством: Manojit Chowdhury, та інші
Опубліковано: (2024-03-01)