Defining efficient phenotypic and genetic selection criteria to improve bread wheat yield under drought conditions

Sahar Bennani

National Institute of Agricultural Research

Nsarellah Nasserlhaq, Wuletaw Tadesse, Ahmed Birouk

In the context of climate change, drought is one of the most important and complex abiotic stresses affecting crop production worldwide. The adoption of an appropriate technological package, principally drought tolerant varieties, may overcome these challenges to meet global food security needs for the rapidly growing human population, particularly in developing countries. Therefore, this research was carried out to identify efficient phenotypic and genetic selection criteria to identify drought tolerant wheat varieties. In this perspective, 200 diverse elite bread wheat lines from ICARDA and CIMMYT were evaluated under four Moroccan environments during the 2015 and 2016 seasons for yield and 15 agro-physiological traits. The same set of genotypes was genotyped using 15k SNPs. Significant environment and genotype environment interaction effects were observed for yield. Average yield reached 3.18t/ha and ranged from 2.45 to 4.27t/ha. The secondary traits were mostly dominated by the environment effect (p<0.001). Based on correlation and regression analysis between grain yield and phenotypic data, the biomass, grain number per m<sup>2</sup> and to a lesser extent fertile spikes number and thousand kernel weights (depending of drought scenarios) can be more reliable traits than yield for the identification of drought tolerant genotypes. Moreover, the ground cover and canopy temperature depression can be used as supplementary criteria for more accurate selection. Slow selection on the basis of phenotypic traits may be accelerated and improved by using molecular markers. The genetic analysis highlighted significant SNPs and identified new QTLs linked to yield and the most efficient phenotypic traits under drought conditions. These findings could be useful for breeding drought-resistant wheat cultivars using marker-assisted selection to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield.