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基于田间的高通量表型分析平台的开发与评估

Development and evaluation of a field-based high-throughput phenotyping platform.

作者信息

Andrade-Sanchez Pedro, Gore Michael A, Heun John T, Thorp Kelly R, Carmo-Silva A Elizabete, French Andrew N, Salvucci Michael E, White Jeffrey W

机构信息

Department of Agricultural and Biosystems Engineering, University of Arizona, Maricopa Agricultural Center, 37860 W. Smith-Enke Road, Maricopa, AZ 85138, USA.

US Department of Agriculture, Agricultural Research Service, Arid-Land Agricultural Research Center, 21881 North Cardon Lane, Maricopa, AZ 85138, USA.

出版信息

Funct Plant Biol. 2013 Feb;41(1):68-79. doi: 10.1071/FP13126.

Abstract

Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In this light, we developed a novel system for phenotyping dynamic traits in the field. System performance was evaluated on 25 Pima cotton (Gossypium barbadense L.) cultivars grown in 2011 at Maricopa, Arizona. Field-grown plants were irrigated under well watered and water-limited conditions, with measurements taken at different times on 3 days in July and August. The system carried four sets of sensors to measure canopy height, reflectance and temperature simultaneously on four adjacent rows, enabling the collection of phenotypic data at a rate of 0.84ha h-1. Measurements of canopy height, normalised difference vegetation index and temperature all showed large differences among cultivars and expected interactions of cultivars with water regime and time of day. Broad-sense heritabilities (H2)were highest for canopy height (H2=0.86-0.96), followed by the more environmentally sensitive normalised difference vegetation index (H2=0.28-0.90) and temperature (H2=0.01-0.90) traits. We also found a strong agreement (r2=0.35-0.82) between values obtained by the system, and values from aerial imagery and manual phenotyping approaches. Taken together, these results confirmed the ability of the phenotyping system to measure multiple traits rapidly and accurately.

摘要

随时间变化的生理和发育性状在相关生长条件下难以进行表型分析。鉴于此,我们开发了一种用于在田间对动态性状进行表型分析的新型系统。在2011年于亚利桑那州马里科帕种植的25个皮马棉(Gossypium barbadense L.)品种上对该系统性能进行了评估。田间种植的植株在充分灌溉和水分受限条件下进行灌溉,于7月和8月的3天中不同时间进行测量。该系统携带四组传感器,可在相邻的四行上同时测量冠层高度、反射率和温度,能够以0.84公顷/小时的速率收集表型数据。冠层高度、归一化植被指数和温度的测量结果均显示出品种间存在较大差异,以及品种与水分状况和一天中不同时间之间存在预期的相互作用。广义遗传力(H2)在冠层高度方面最高(H2 = 0.86 - 0.96),其次是对环境更敏感的归一化植被指数(H2 = 0.28 - 0.90)和温度(H2 = 0.01 - 0.90)性状。我们还发现该系统获得的值与航空图像和人工表型分析方法获得的值之间存在很强的一致性(r2 = 0.35 - 0.82)。综上所述,这些结果证实了该表型分析系统能够快速、准确地测量多个性状。

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