Use of multivariate approaches as a robust selection tool for physiological and molecular traits linked to drought resistance in an oat breeding programme

Abstract

Drought is the main abiotic stress on cereal yield. To date cereal breeding has mainly based on empirical selection for yield per se. However this is far from being optimal, since yield is characterized by a low heritability and a high genotype × environment interaction. There is now strong argument that and indirect approach based on an understanding of the crop at physiological and molecular level, may help target key traits to ease breeding programs. Different studies have revealed several physiological and molecular processes involved in drought resistance, however this information has hardly been used in breeding. The main reason is that there is not enough information about the best physiological or molecular parameters indicative of drought resistance and the best moment for each parameter during drought to discriminate between resistant and susceptible individuals of a breeding population. In this work we first sought for new sources of resistance to drought in an oat germplasm collection consisting on 141 accessions of A. sativa and A. byzantina together with 32 oat cultivars (A. sativa). A visual scale of symptoms able to discriminate among genotypes was set up in seedlings, under controlled conditions and along a treatment of progressive drought during 18 days. According to this evaluation, 1 genotype highly resistant, 3 resistant, and 7 moderately resistant together with three susceptible controls were selected for measuring several physiological and molecular traits associated with resistance at 6 different time points during the drought time course. These traits were the area under the drought progression curve (AUDPC), relative water content (RWC), cell membrane stability (CMS), lipid peroxidation, lipoxygenase activity, antioxidant capacity, infrared leaf temperature, SPAD chlorophyll meter values and curves of stomatal conductance. Following this assessment a multivariate analysis was carried out according to the different parameters assessed with a total of 29 variables. When analysed using multivariate Discriminant Function Analysis (DFA) it was possible to distinguish between the highly resistant, the resistant and the susceptible genotypes. In addition, DFA indicated that Infrared temperature at 12 and 15 days after withholding water, AUDPC, and RWC at day 15 were the most robust parameters to be taken into account in breeding programs for drought resistance in oat.