4.6 Article

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

Journal

PEERJ
Volume 6, Issue -, Pages -

Publisher

PEERJ INC
DOI: 10.7717/peerj.6240

Keywords

Rice; Leaf chlorophyll content index; Rice biomass simulation

Funding

  1. Special Fund for Agro-scientific Research in the Public Interest of China [20150312203]
  2. International Plant Nutrition Institute (IPNI) [IPNI-HB-45]

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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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