Trapping the genetic variation for yield and yield related attributes in bread wheat under water deficit stress

The yield and production of several crops, including wheat ( Triticum aestivum L.), which is the most significant crop in the world, have been significantly affected by drought occurrences in various parts of the world. By Using the randomized complete block design, which is based on three replications, a set of 100 wheat accessions were examined under normal and drought stress condition. The analysis of variance revealed that the genotypes significantly varied in all of the qualities in both condition under normal and drought stress, which demonstrating the wide range of genotypes that can be used in breeding strategies for improvement. The study revealed significant differences among genotypes under both normal and drought conditions, highlighting the varying responses to stress. According to the results of the correlation study, in normal conditions, the grain yield per plant exhibits a significant and favorable link with every trait that was studied. Under drought conditions, grain yield per plant has a negative association with plant height, which has an impact on grain production and results in a significant decrease in the wheat crop’s output. The genotypes G27, G28, G71, G72, and G89 performed best under drought conditions and were termed drought resistant genotypes, according to the mean variability, whereas the genotypes G50, G53, G54, G80, and G88 performed poorly and were considered as drought sensitive. Highest broad-sense heritability (84–96%) and genetic advance exceeded 20% that emphasized the role of genetic factors in influencing studied traits which exhibited significant potential for improvement through selective breeding, particularly in drought-stress. Results obtained from principal component analysis, only 4 PCs showed the significant variability due to having eigenvalues > 1. These 4 PCs cumulatively accounted for 66.1% and 63.8% of the total variability under normal and drought conditions. Eigenvalues, proportions, and cumulative values of principal components were analyzed, indicating that the first few principal components captured the majority of the variance in the dataset. Loading factor analysis further revealed the correlation between original variables and principal components, aiding in understanding the contribution of each trait to overall variance. The identification of drought-tolerant genotypes and the delineation of trait relationships provide crucial information for future breeding endeavors, aiming at enhancing wh