Quantification of Photosynthetic Pigments in Neopyropia yezoensis Using Hyperspectral Imagery

作     者：Shuai Che Guoying Du Xuefeng Zhong Zhaolan Mo Zhendong Wang Yunxiang Mao Shuai Che;Guoying Du;Xuefeng Zhong;Zhaolan Mo;Zhendong Wang;Yunxiang Mao

作者机构：Key Laboratory of Marine Genetics and Breeding(Ministry of Education)College of Marine Life SciencesOcean University of ChinaQingdao266003China Key Laboratory of Utilization and Conservation of Tropical Marine Bioresource(Ministry of Education)College of Fisheries and Life ScienceHainan Tropical Ocean UniversitySanya572002China Yazhou Bay Innovation InstituteHainan Tropical Ocean UniversitySanya572025China Laboratory for Marine Biology and BiotechnologyPilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao266073China 

出 版 物：《Plant Phenomics》 (植物表型组学（英文）)

年 卷 期：2023年第5卷第1期

页      面：60-72页

核心收录：

学科分类：0710[理学-生物学] 09[农学] 0903[农学-农业资源与环境] 0901[农学-作物学] 090302[农学-植物营养学] 

基　　金：supported by the National Natural Science Foundation of China(grant no.32060829) the National Key R&D Program of China(2020YFD0901101) the 2020 Research Program of Sanya Yazhou Bay Science and Tech nology City(no.SKJC­2020­02­009) the Innovation Platform for Academicians of Hainan Province and Special Project of Central Government Guiding Local Science and Technology Development(grant no.ZY2020HN02) the Major Science and Technology Program of Yazhou Bay Innovation Institute of Hainan Tropical Ocean University(2022CXYZD001) 

主　　题：prediction breeding visible 

摘      要：Phycobilisomes and chlorophyll-a(Chla)play important roles in the photosynthetic physiology of red macroalgae and serve as the primary light-harvesting antennae and reaction center for photosystem Ⅱ.Neopyropia is an economically important red macroalga widely cultivated in East Asian *** contents and ratios of 3 main phycobiliproteins and Chla are visible traits to evaluate its commercial *** traditional analytical methods used for measuring these components have several ***,a high-throughput,nondestructive,optical method based on hyperspectral imaging technology was developed for phenotyping the pigments phycoerythrin(PE),phycocyanin(PC),allophycocyanin(APC),and Chla in Neopyropia thalli in this *** average spectra from the region of interest were collected at wavelengths ranging from 400 to 1000 nm using a hyperspectral *** different preprocessing methods,2 machine learning methods,partial least squares regression(PLSR)and support vector machine regression(SVR),were performed to establish the best prediction models for PE,PC,APC,and Chla *** prediction results showed that the PLSR model performed the best for PE(R_(Test^(2))=0.96,MAPE=8.31%,RPD=5.21)and the SVR model performed the best for PC(R_(Test^(2))=0.94,MAPE=7.18%,RPD=4.16)and APC(R_(Test^(2))=0.84,MAPE=18.25%,RPD=2.53).Two models(PLSR and SVR)performed almost the same for Chla(PLSR:R_(Test^(2))=0.92,MAPE=12.77%,RPD=3.61;SVR:R_(Test^(2))=0.93,MAPE=13.51%,RPD=3.60).Further validation of the optimal models was performed using field-collected samples,and the result demonstrated satisfactory robustness and *** distribution of PE,PC,APC,and Chla contents within a thallus was visualized according to the optimal prediction *** results showed that hyperspectral imaging technology was effective for fast,accurate,and noninvasive phenotyping of the PE,PC,APC,and Chla contents of Neopyropia in *** could benefit the efficiency of macro