Utilizing genetic diversity to select tomato lines tolerant of tomato yellow leaf curl virus based on genotypic coefficient of variation, heritability, genotypic correlation, and multivariate analyses

Abstract

Tomato yellow leaf curl virus (TYLCV) is one of the most destructive pathogens for tomato crops. The development of TYLCV-tolerant tomato lines (TLs) requires a thorough understanding of their genetic variability and relationships among lines and in traits of interest. Twelve F9 TLs were evaluated for phenotypic TYLCV tolerance, vegetative growth, yield, and fruit quality during the 2018 and 2019 fall seasons to identify elite breeding lines. TLs were selected by a bulk selection method from segregating generations of the commercial F1 hybrids TH99802 (TLs 1–6) and TH99806 (TLs 7–12). TLs exhibited either mild or no symptoms. The TYLCV titer varied between 0.8 × 105 and 3.9 × 105 in symptomless TLs plants compared to 56.7 × 105 in severely symptomatic plants of susceptible ‘Castlerock.’ Across both seasons, TL-3, TL-5, and TL-8 exhibited the highest total and marketable plant yields, TYLCV tolerance, and acceptable fruit quality. Most traits had high estimates of genetic variance, genotypic coefficient of variance, and broad sense heritability. Our results indicated that there was sufficient genetic variability for selection of the best lines. Principal component analysis and hierarchical cluster analysis indicated that the TLs were highly diverse of the evaluated traits and could be divided into three clusters. Cluster 1, which included TL-1, TL-3, and TL-8, performed better for TYLCV tolerance and economically important traits. Clusters 1 and 2 showed the greatest degree of dissimilarity. Therefore, crossing parents from Cluster 1 with 2 is predicated to maximum recombination for improve genotypes.

Influence of seagrass traits on the diversity of endophytic fungi

“…Leaf area was calculated using the leaf weighting method: leaf area = x/y, where x is the weight (g) of the whole leaf and y is the weight of 1 cm 2 area of the leaf (Mahmoud and Osman 2023). The dry matter content was calculated as dry mass divided by the sample's fresh mass (mg g -1 ) (Jovanovic et al 2023).…”