Efficiency of different traits for phenotyping soybean drought tolerance in an automated platform when estimated under different basis.

PEIRONE, L.; PEREYRA IRUJO, G.A; AGUIRREZÁBAL L.A.N

Troia

Conferencia; Second International Legume Society Conference; 2016

International Legume Society

Efficiency of different traits for phenotyping soybean drought tolerance in an automated platform when estimated under different basis.PEIRONE, Laura ; PEREYRA IRUJO, Gustavo y AGUIRREZÁBAL, Luis.A.N.*Laboratorio de Fisiología Vegetal, Unidad Integrada Balcarce (INTA-FCA, UNMdP), Argentina, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). * laguirre@mdp.edu.arThe efficiency of different traits for phenotyping drought tolerance by using an automated platform has been assessed taking into account only one basis, i.e.heritability. The aim of this work was to compare the efficiency of different traits for phenotyping when estimated under different basis. Seven soybean genotypes were studied under well-watered and water deficit treatment (WD). WD started at 33 days after emergence (DAE), and finished at 57 DAE. 34 traits were measured before and after the onset of the WD measured in the Glyph platform, a low-cost automatic automated platform developed for soybean which allows the evaluation of genotypes under precisely controlled water deficit condition. The efficiency of these traits for phenotyping were estimated for the basis time from emergence to phenotyping ii) coefficient of genetic determination (CGD), sample size, measurement time and measurement cost. Traits with a high efficiency on time from emergence (Transpiration efficiency estimated at 13, 20, 27, 33 and 38 DAE, Leaf Area Ratio and Shoot Dry Weight at 38 DAE) were also efficient when estimated on basis cost, measurement time, and sample size. They showed intermediate values of CGD. The framework applied in this work for a joint analysis of efficiency of several traits under different basis could be helpful for selecting those more efficient for phenotyping given the bottleneck of each specific case (e.g. capacity of the phenotyping platform, available sensors, budget).