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

利用叶片叶绿素含量指数提高地上生物量和生产力的预测精度

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Abstract

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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