Estimation of Rice Aboveground Biomass by UAV Imagery with Photosynthetic Accumulation Models

作     者：Kaili Yang Jiacai Mo Shanjun Luo Yi Peng Shenghui Fang Xianting Wu Renshan Zhu Yuanjin Li Ningge Yuan Cong Zhou Yan Gong Kaili Yang;Jiacai Mo;Shanjun Luo;Yi Peng;Shenghui Fang;Xianting Wu;Renshan Zhu;Yuanjin Li;Ningge Yuan;Cong Zhou;Yan Gong

作者机构：School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina Lab for Remote Sensing of Crop PhenotypingWuhan UniversityWuhanChina College of Life SciencesWuhan UniversityWuhanChina 

出 版 物：《Plant Phenomics》 (植物表型组学（英文）)

年 卷 期：2023年第5卷第3期

页      面：418-434页

核心收录：

学科分类：09[农学] 0901[农学-作物学] 

基　　金：funded by LIESMARS Special Research Funding,ESA-MOST Dragon 5 cooperation(grant number UAV4VAL\ID58817) the Natural Science Foundation of China(grant number 41771381) Key R&D Projects in Hubei Province(grant number 2020BBB058) the National Key R&D Program of China(grant number 2016YFD0101105) 

主　　题：Biomass cultivar season 

摘      要：The effective and accurate aboveground biomass(AGB)estimation facilitates evaluating crop growth and site-specific crop *** that rice accumulates AGB mainly through green leaf photosynthesis,we proposed the photosynthetic accumulation model(PAM)and its simplified version and compared them for estimating *** methods estimate the AGB of various rice cultivars throughout the growing season by integrating vegetation index(Ⅵ)and canopy height based on images acquired by unmanned aerial vehicles(UAV).The results indicated that the correlation of Ⅵ and AGB was weak for the whole growing season of rice and the accuracy of the height model was also limited for the whole growing *** comparison with the NDVI-based rice AGB estimation model in 2019 data(R^(2)=0.03,RMSE=603.33 g/m^(2))and canopy height(R^(2)=0.79,RMSE=283.33 g/m^(2)),the PAM calculated by NDVI and canopy height could provide a better estimate of AGB of rice(R^(2)=0.95,RMSE=136.81 g/m^(2)).Then,based on the time-series analysis of the accumulative model,a simplified photosynthetic accumulation model(SPAM)was proposed that only needs limited observations to achieve R^(2) above *** PAM and SPAM models built by using 2 years of samples successfully predicted the third year of samples and also demonstrated the robustness and generalization ability of the *** conclusion,these methods can be easily and efficiently applied to the UAV estimation of rice AGB over the entire growing season,which has great potential to serve for large-scale field management and also for breeding.