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

第一作者： Liu, Yi

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

作者机构：

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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