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  • Title:  Use of a leaf chlorophyll content index to improve the prediction of above-ground biomass and productivity
  • Authors: 
  • Corresponding Author:  Liu, Chuang; Liu, Yi; Lu, Yanhong*; Liao, Yulin; Nie, Jun; Yuan, Xiaoliang; Chen, Fang*.
  • Pubyear:  2019
  • Title of Journal:  Peerj
  • Paper Code: 
  • Volume:  6
  • Number: 
  • Page: 
  • Others: 
  • Classification: 
  • Source: 

    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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