Author:
Li He,Mao Yilin,Shi Hongtao,Fan Kai,Sun Litao,Zaman Shah,Shen Jiazhi,Li Xiaojiang,Bi Caihong,Shen Yaozong,Xu Yang,Chen Hao,Ding Zhaotang,Wang Yu
Funder
Shandong Academy of Agricultural Sciences
Reference46 articles.
1. Environmental factors variably impact tea secondary metabolites in the context of climate change;Ahmed;Front. Plant Sci.,2019
2. Estimation of soybean grain yield from multispectral high-resolution UAV data with machine learning models in West Africa;Alabi;Remote Sens. Appl.,2022
3. Study on deep learning model for online estimation of chlorophyll content based on near ground multispectral feature bands;Cao;IEEE Access.,2022
4. Prediction of drought-induced components and evaluation of drought damage of tea plants based on hyperspectral imaging;Chen;Front. Plant. Sci.,2021
5. Comparative prediction accuracy of hyperspectral bands for different soybean crop variables: from leaf area to seed composition;Chiozza;Field Crops Res.,2021
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献