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Background Pre-harvest sprouting (PHS) refers to a phenomenon, in which the physiologically mature seeds are germinated on the spike before or during the harvesting practice owing to high humidity or prolonged period of rainfall. Pre-harvest sprouting (PHS) remarkably decreases seed quality and yield in wheat; hence it is imperative to uncover genomic regions responsible for PHS tolerance to be used in wheat breeding. A genome-wide association study (GWAS) was carried out using 298 bread wheat landraces and varieties from Iran to dissect the genomic regions of PHS tolerance in a well-irrigated environment. Three different approaches (RRBLUP, GBLUP and BRR) were followed to estimate prediction accuracies in wheat genomic selection. Results Genomes B, A, and D harbored the largest number of significant marker pairs (MPs) in both landraces (427,017, 328,006, 92,702 MPs) and varieties (370,359, 266,708, 63,924 MPs), respectively. However, the LD levels were found the opposite, i.e., genomes D, A, and B have the highest LD, respectively. Association mapping by using GLM and MLM models resulted in 572 and 598 marker-trait associations (MTAs) for imputed SNPs (− log10 P > 3), respectively. Gene ontology exhibited that the pleitropic MPs located on 1A control seed color, α-Amy activity, and PHS. RRBLUP model indicated genetic effects better than GBLUP and BRR, offering a favorable tool for wheat genomic selection. Conclusions Gene ontology exhibited that the pleitropic MPs located on 1A can control seed color, α-Amy activity, and PHS. The verified markers in the current work can provide an opportunity to clone the underlying QTLs/genes, fine mapping, and genome-assisted selection.Our observations uncovered key MTAs related to seed color, α-Amy activity, and PHS that can be exploited in the genome-mediated development of novel varieties in wheat.

Moisture stress greatly limits the productivity of wheat in many wheat-growing regions of the world. Knowledge of the degree of genetic diversity among parental materials for key selection traits will facilitate the development of high yielding, stress tolerant wheat cultivars. The objectives of this study were to: (i) use amplified fragment length polymorphisms (AFLPs) to assess genetic diversity among bread wheat lines and cultivars with different responses to drought stress in two distinct environments and, (ii) compare genetic diversity estimated by AFLPs with diversity evaluated on agronomic performance under drought stress. Twenty-eight genotypes, 14 from Iran and 14 developed or obtained by CIMMYT, were evaluated in the study. Phenotypic data on the 14 Iranian lines were obtained in Iran, and data on the 14 CIMMYT lines were collected in Mexico. Ten AFLP primer pairs detected 335 polymorphic bands among the 28 cultivars. At the 5th fusion level of the resulting dendrogram, 6 genotype clusters were identified. Thirteen of the 14 CIMMYT genotypes grouped into one cluster while 4 of the remaining groups were comprised only of Iranian genotypes. When the agronomic performance of the Iranian materials was compared with the AFLP diversity analysis, 5 of the 6 drought susceptible genotypes clustered together in the agronomic dendrogram, and were located in the same cluster in the AFLP dendrogram. However, the drought tolerant Iranian materials did not show the same degree of relationship. The CIMMYT materials did not demonstrate a significant association between agronomic performance and genetic diversity determined using AFLPs. Clearly these data show that there are genotypes with similar agronomic performance and different genetic constitutions in this study that can be combined in a breeding program to potentially improve tolerance to drought stress.

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Improving drought endurance in wheat needs high-throughput screening of yield components including seed volume, area, and weight, all of which are very effortful, time-consuming, and visually mostly infeasible. Imaging-based screening presents an opportunity for more exact/rapid analysis of seed morphometric traits. Therefore, this study was aimed at evaluating the phenotypic diversity of wheat seeds under rain-fed and well-watered conditions by using image analysis. From our observations, the criteria Feret (largest axis length) and MaxR (radius of the enclosing circle centered at the middle of mass) exhibited that grain length is less affected by drought. In the rain-fed environment, seed weight had the highest correlation with seed volume (r = 0.76**) and area (r = 0.76**). The correlation of 1000-grain weight with aspect ratio (r = –0.22**) and Rroundness (r = –0.21**) was negative and also non-significant (P > 0.05). The PCA and cluster analysis highlights the MinR (radius of the inscribed circle centered at the middle of mass), Area, Circ (Circularity), ArEquivD (area equivalent diameter), thickness, and seed volume characteristics can be used as useful parameters to identify genotypes suitable for planting in a rain-fed environment. The relative importance of traits for 1000-grain weight in the neural network displayed that the greatest impact in the rain-fed environment was related to seed volume, area, and MBCRadius (radius of the minimal bounding circle). Overall, our findings permitted the formation of a morphometric seed database for the conservation and characterisation of wheat germplasm.

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