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Use of a leaf chlorophyll content index to improve the prediction of above-ground biomass and productivity

文献类型: 外文期刊

作者: Liu, Chuang 2 ; Liu, Yi 1 ; Lu, Yanhong 3 ; Liao, Yulin 3 ; Nie, Jun 3 ; Yuan, Xiaoliang 1 ; Chen, Fang 1 ;

作者机构: 1.Chinese Acad Sci, Key Lab Aquat Bot & Watershed Ecol, Wuhan Bot Garden, Wuhan, Hubei, Peoples R China

2.Univ Chinese Acad Sci, Beijing, Peoples R China

3.Hunan Acad Agr Sci, Soil & Fertilizer Inst, Changsha, Hunan, Peoples R China

4.China Program Int Plant Nutr Inst, Wuhan, Hubei, Peoples R China

关键词: Rice; Leaf chlorophyll content index; Rice biomass simulation

期刊名称:PEERJ ( 影响因子:2.984; 五年影响因子:3.369 )

ISSN: 2167-8359

年卷期: 2019 年 6 卷

页码:

收录情况: SCI

摘要: Improving the accuracy of predicting plant productivity is a key element in planning nutrient management strategies to ensure a balance between nutrient supply and demand under climate change. A calculation based on intercepted photosynthetically active radiation is an effective and relatively reliable way to determine the climate impact on a crop above-ground biomass (AGB). This research shows that using variations in a chlorophyll content index (CCI) in a mathematical function could effectively obtain good statistical diagnostic results between simulated and observed crop biomass. In this study, the leaf CCI, which is used as a biochemical photosynthetic component and calibration parameter, increased simulation accuracy across the growing stages during 2016-2017. This calculation improves the accuracy of prediction and modelling of crops under specific agroecosystems, and it may also improve projections of AGB for a variety of other crops.

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