A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria  

作　　者：Noah Fahlgren Maximilian Feldman Malia A. Gehan Melinda S. Wilson Christine Shyu Douglas W. Bryant Steven T. Hill Colton J. McEntee ankalpi N. Warnasooriya Indrajit Kumar Tracy Ficor Stephanie Turnipseed Kerrigan B. Gilbert Thomas P. Brutnell James C. Carrington Todd C. Mockler Ivan Baxter 

机构地区：[1]Donald Danforth Plant Science Center, St. Louis, MO 63132, USA [2]USDA-ARS, Donald Danforth Plant Science Center, St. Louis, MO 63132, USA [3]These authors contributed equally to this article.

出　　处：《Molecular Plant》2015年第10期1520-1535,共16页分子植物（英文版）

摘　　要：Phenotyping has become the rate-limiting step in using large-scale genomic data to understand and improve agricultural crops. Here, the Bellwether Phenotyping Platform for controlled-environment plant growth and automated multimodal phenotyping is described. The system has capacity for 1140 plants, which pass daily through stations to record fluorescence, near-infrared, and visible images. Plant Computer Vision （PlantCV） was developed as open-source, hardware platform-independent software for quantitative image analysis. In a 4-week experiment, wild Setaria viridis and domesticated Setaria italica had fundamentally different temporal responses to water availability. While both lines produced similar levels of biomass under limited water conditions, Setaria viridis maintained the same water-use efficiency under water replete conditions, while Setaria italica shifted to less efficient growth. Overall, the Bellwether Phenotyping Platform and PlantCV software detected significant effects of genotype and environment on height, biomass, water-use efficiency, color, plant architecture, and tissue water status traits. All -79 000 images acquired during the course of the experiment are publicly available.Phenotyping has become the rate-limiting step in using large-scale genomic data to understand and improve agricultural crops. Here, the Bellwether Phenotyping Platform for controlled-environment plant growth and automated multimodal phenotyping is described. The system has capacity for 1140 plants, which pass daily through stations to record fluorescence, near-infrared, and visible images. Plant Computer Vision （PlantCV） was developed as open-source, hardware platform-independent software for quantitative image analysis. In a 4-week experiment, wild Setaria viridis and domesticated Setaria italica had fundamentally different temporal responses to water availability. While both lines produced similar levels of biomass under limited water conditions, Setaria viridis maintained the same water-use efficiency under water replete conditions, while Setaria italica shifted to less efficient growth. Overall, the Bellwether Phenotyping Platform and PlantCV software detected significant effects of genotype and environment on height, biomass, water-use efficiency, color, plant architecture, and tissue water status traits. All -79 000 images acquired during the course of the experiment are publicly available.

关 键 词：abiotic/environmental stress water relations BIOINFORMATICS development PHENOTYPING 

分 类 号：S688.4[农业科学—观赏园艺] TV21[农业科学—园艺学]