Predictions of wheat phenotypic variability by integrating high-throughput phenotyping observations into a crop growth model
Dong Cai Shouyang Liu Pierre Martre Chen Zhu Xu Wang Loic Manceau Stéphane Jezequel Mathieu Marguerie Benoit de Solan Frédéric Baret Samuel Buis
Predictions of wheat phenotypic variability by integrating high-throughput phenotyping observations into a crop growth model
Predictions of wheat phenotypic variability by integrating high-throughput phenotyping observations into a crop growth model
摘要
关键词
Bayesian inference/Crop growth model/Data assimilation/Genetic variability/Genotypic parameter/High-throughput phenotyping/Lookup table/WheatKey words
Bayesian inference/Crop growth model/Data assimilation/Genetic variability/Genotypic parameter/High-throughput phenotyping/Lookup table/Wheat引用本文复制引用
Dong Cai,Shouyang Liu,Pierre Martre,Chen Zhu,Xu Wang,Loic Manceau,Stéphane Jezequel,Mathieu Marguerie,Benoit de Solan,Frédéric Baret,Samuel Buis..Predictions of wheat phenotypic variability by integrating high-throughput phenotyping observations into a crop growth model[J].植物表型组学（英文）,2026,8(1):58-72,15.基金项目
This work was supported in China by the National Key Research and Development Program of China(No.2022YFE0116200,No.2021YFD2000105),the Young Scientists Fund of the National Natural Science Foundation of China(No.42201437),and the Biological Breeding-National Science and Technology Major Project(No.2022ZD0401801)and in France by the"Infrastructure Biologie Santé"Phenome funded by the National Research Agency(ANR-11INBS0012).LM,SB,and PM also acknowledge support from the ANR project FFAST(grant n° C10772)and the European Union's Horizon Europe research and innovation programme under grant agreement N° 101094587,and LM and PM from the Horizon 2020 Framework Pro-gramme of the European Union under grant agreement No.817970.SJ and MM acknowledge funding by the Région Sud-Provence-Alpes-Côte-d'Azur,France. （No.2022YFE0116200,No.2021YFD2000105）
