|ANDRADE-SANCHEZ, PEDRO - University Of Arizona|
|GORE, MICHAEL - Cornell University - New York|
|HEUN, JOHN - University Of Arizona|
|CARMO-SILVA, ELIZABETE - Rothamsted Research|
Submitted to: Functional Plant Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/18/2013
Publication Date: 9/5/2013
Citation: Andrade-Sanchez, P., Gore, M., Heun, J., Thorp, K.R., Carmo-Silva, E., French, A.N., Salvucci, M.E., White, J.W. 2013. Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology. DOI:10.1071/FP13126.
Interpretive Summary: Plant breeders and geneticists increasingly seek to study the genetic control of crop yield and associated traits by examining hundreds or thousands of genetically different lines grown in individual field plots. However, the limited availability of tools to rapidly and reliably measure plant traits under relevant growing conditions has greatly impeded progress. We developed and evaluated a tractor-based system capable of efficiently and accurately measuring traits related to heat and drought stress tolerance of field-grown cotton plants throughout the growing season. Four sets of sensors were mounted on a high-clearance tractor, so they system could monitor multiple plots as it is driven through a research field. The system has the potential to vastly increase the quantity and quality of field trait data obtained from plants, facilitating the development of high yielding crops that better tolerate stresses such as drought and heat.
Technical Abstract: Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In response to this challenge, we developed a novel system for phenotyping dynamic traits in the field. System performance was evaluated on a field experiment of 25 Pima cotton cultivars (Gossypium barbadense L.) grown under well-watered and water-limited conditions, with measurements taken at different times on three days. The 40 system carried four sets of sensors to simultaneously measure canopy height, reflectance, and temperature on four adjacent rows, allowing for phenotypic data to be collected with ~77% field efficiency at a rate of 0.84 ha h-1. Measurements of canopy height, normalized difference vegetation index (NDVI) and temperature all showed large differences among cultivars, as well as expected interactions of cultivars with water regime and time of the day. Heritabilities were 45 highest for canopy height (0.81–0.93), followed by the more environmentally sensitive NDVI (0.17–0.81) and canopy temperature (0.01–0.82) 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 effectively measure multiple traits rapidly and accurately.