Predicting rice phenology across China by integrating crop phenology model and machine learning-Reference-Cited by-同舟云学术

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Predicting rice phenology across China by integrating crop phenology model and machine learning

Published:2024-11 Issue: Volume:951 Page:175585
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Zhang Jinhan,Lin Xiaomao,Jiang Chongya,Hu Xuntao,Liu Bing,Liu Leilei,Xiao Liujun,Zhu Yan,Cao Weixing,Tang Liang

Funder

National Key Research and Development Program of China

Jiangsu Provincial Agricultural Science and Technology Independent Innovation Fund

Nanjing Agricultural University

Jiangsu Collaborative Innovation Center for Modern Crop Production

Higher Education Discipline Innovation Project

Publisher

Elsevier BV

Reference80 articles.

1. A review of interpretable ML in healthcare: taxonomy, applications, challenges, and future directions;Abdullah;Symmetry,2021

2. Uncertainty in simulating wheat yields under climate change;Asseng;Nat. Clim. Chang.,2013

3. Upland rice simulation and its use in multicriteria optimization. International Benchmark Sites Network for Agrotechnology Transfer;Alocija,1988

4. Rising temperatures reduce global wheat production;Asseng;Nat. Clim. Chang.,2015

5. Evaluation of wheat yield in North China plain under extreme climate by coupling crop model with machine learning;Bai;Comput. Electron. Agric.,2024

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