Abstract

Wheat (Triticum aestivum L.) is a key food crop, accounting for approximately 765 million tons produced worldwide. The present study evaluated 16 wheat genotypes using 19 morphological and phenological traits, 16 molecular markers (Inter Simple Sequence Repeats and Start Codon Targeted; ISSR and SCoT) and rbcL and matK plastid gene barcoding. The 16 wheat genotypes showed significant genetic variation using the markers assayed. Cell plot of phenological parameters revealed significant differences among the 16-day-old seedlings of wheat genotypes at Z1.1 growth stage. Collectively, W2 genotype had the lowest shoot length (SL), length of first internodes (LFI) and leaf area (LA) values, while W8 genotype had the highest diameter of first internode (DFI) and LA values. Furthermore, W7 genotype had the maximum plant biomass (PB) and leaf width (LW) values. Geometric models grouped wheat kernels into "rounded" and "nearly elongated". Estimates of heritability (H2) for these morphological characters ranged from 4.93 to 100%. The highest H2 values were recorded for root number (RN) (100%) followed by SL (88.72%), LFI (88.30%), LA (87.76%) and Feret diameter (86.68%), while the lowest H2 value was recorded for DFI (4.93%). Furthermore, highly significant genotypic and phenotypic correlations were also observed among those traits. Reproducible fingerprinting profiles and high levels of polymorphism (PPB%) of SCoT (95.46%) and ISSR (82.41%) were recorded, indicating that they are effective tools for detecting genetic variation levels among wheat genotypes. The informativeness of markers were measured through estimation of polymorphic information content (PIC), resolving power (RP) and marker index (MI). The RP and PPB% of SCoT were significantly higher compared to those of ISSR. Comparatively, the two molecular markers were effective for studying genetic diversity among wheat genotypes, but SCoT markers were more informative. Moreover, based on the two chloroplast DNA regions (rbcL and matK), MatK was found to be more reliable for differentiating among T. aestivum genotypes. Taken together, using all the studied attributes, a clear taxonomic relationship can be used to identify T. aestivum species and improve their pragmatic production and development.

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