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

机译:利用叶绿素含量指数改善对地上生物量和生产力的预测

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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.
机译:提高植物生产力的预测准确性是规划养分管理策略以确保气候变化下养分供求之间平衡的关键要素。基于截获的光合有效辐射的计算是确定气候对作物地上生物量(AGB)的影响的有效且相对可靠的方法。这项研究表明,在数学函数中使用叶绿素含量指数(CCI)的变化可以有效地获得模拟和观察到的作物生物量之间的良好统计诊断结果。在这项研究中,用作生化光合成分和校准参数的叶片CCI在2016–2017年的整个生长阶段提高了模拟准确性。这种计算可以提高特定农业生态系统下农作物预测和建模的准确性,也可以改善其他多种农作物的AGB预测。

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