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

被引:82
作者
Liu, Chuang [1 ,2 ]
Liu, Yi [1 ]
Lu, Yanhong [3 ]
Liao, Yulin [3 ]
Nie, Jun [3 ]
Yuan, Xiaoliang [1 ,2 ]
Chen, Fang [1 ,4 ]
机构
[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
关键词
Rice; Leaf chlorophyll content index; Rice biomass simulation; WINTER-WHEAT; GRAIN-YIELD; FOLIAR CHLOROPHYLL; BIOTIC DRIVERS; AREA INDEX; MODEL; RICE; PHOTOSYNTHESIS; CALIBRATION; VALIDATION;
D O I
10.7717/peerj.6240
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
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.
引用
收藏
页数:15
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