Estimating genetic variability among diverse lentil collections through novel multivariate techniques

Area of Science:

• Agricultural Science
• Plant Breeding
• Food Security

Background:

• Lentil is a vital global food legume, with Pakistan ranking 18th in production.
• Lentils offer rich nutritional value, addressing food security and malnutrition, especially in South Asia.
• Evaluating diverse lentil genotypes is essential for crop improvement.

Purpose of the Study:

• To assess yield, yield-contributing traits, and cooking time (CT) in 220 lentil genotypes.
• To identify superior genotypes for enhanced lentil cultivation and breeding programs.
• To understand trait associations and heritability for future crop improvement.

Main Methods:

• Field evaluation of 220 lentil genotypes from Pakistan, Syria, and the USA.
• Statistical analyses including Pearson correlation, Principal Component Analysis (PCA), Structural Equational Model (SEM), and hierarchical cluster analysis.
• Heritability estimation for key agronomic traits.

Main Results:

• Genotype 6122 (Pakistan) showed excellent performance in seed yield per plant (SY), biological yield per plant (BY), and cooking time (CT).
• Genotypes 6074 and 5745 (Pakistan) exhibited the minimum CT of 10 minutes.
• Significant associations were found between SY, BY, pod size (PS), and number of seeds per pod (NSP).
• Ten genotypes were identified as promising for future breeding, with high heritability observed for HSW, SY, BY, and NSP.

Conclusions:

• Specific lentil genotypes demonstrate superior yield and cooking characteristics, vital for developing improved cultivars.
• Selected genotypes offer potential for enhanced fodder production and faster cooking, saving energy and resources.
• The identified high-heritability traits provide a strong basis for marker-assisted selection in future lentil breeding programs.