WINTER-WHEAT
; GRAIN-YIELD
; FOLIAR CHLOROPHYLL
; BIOTIC DRIVERS
; AREA INDEX
; MODEL
; RICE
; PHOTOSYNTHESIS
; CALIBRATION
; VALIDATION
WOS学科分类:
Multidisciplinary Sciences
WOS研究方向:
Science & Technology - Other Topics
英文摘要:
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.
1.Chinese Acad Sci, Key Lab Aquat Bot & Watershed Ecol, Wuhan Bot Garden, Wuhan, Hubei, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Hunan Acad Agr Sci, Soil & Fertilizer Inst, Changsha, Hunan, Peoples R China 4.China Program Int Plant Nutr Inst, Wuhan, Hubei, Peoples R China
Recommended Citation:
Liu, Chuang,Liu, Yi,Lu, Yanhong,et al. Use of a leaf chlorophyll content index to improve the prediction of above-ground biomass and productivity[J]. PEERJ,2019-01-01,6