Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling

被引:27
|
作者
Gosseau, Florie [1 ]
Blanchet, Nicolas [1 ]
Vares, Didier [1 ]
Burger, Philippe [2 ]
Campergue, Didier [3 ]
Colombet, Celine [3 ]
Gody, Louise [1 ]
Lievin, Jean-Francois [3 ]
Mangin, Brigitte [1 ]
Tison, Gilles [3 ]
Vincourt, Patrick [1 ]
Casadebaig, Pierre [2 ]
Langlade, Nicolas [1 ]
机构
[1] Univ Toulouse, CNRS, INRA, LIPM, Castanet Tolosan, France
[2] Univ Toulouse, INRA, AGIR, Castanet Tolosan, France
[3] INRA, UE Auzeville, Castanet Tolosan, France
来源
关键词
plant phenotyping; robotics; water stress; genomics; crop modeling; SOIL-WATER DEFICIT; DROUGHT TOLERANCE; DIFFERENTIAL EXPRESSION; PHYSIOLOGICAL TRAITS; STRESS TOLERANCE; PLANT-RESPONSES; ABIOTIC STRESS; SUNFLOWER; ARABIDOPSIS; ENVIRONMENT;
D O I
10.3389/fpls.2018.01908
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a modeling study using measured parameters as inputs for a crop simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used a crop simulation model to predict the impact on crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological model parameters to define ideotypes adapted to different environmental conditions.
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收藏
页数:19
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