Estimation of heritability and genetic variability in selected F1 bitter gourd population for yield and its contributing traits

Abstract

Bitter gourd is one of the potential vegetables that has been clinically proven with several uses due to its medicinal advantages. However, it is less popular than other vegetable crops. Hence, this study was conducted to obtain detailed information on important agronomic traits and determine the pattern of inheritance of morphological traits in bitter gourd. Four F1 populations, P105 × P11, P11 × P92, P92 × P13 and P13 × P92 have been successfully generated from the hybridisation of four genotypes parental lines (P11, P13, P92 and P105). The result of analysis of variance showed that the parents and the F1 populations were significantly different (p < 0.01) in terms of vine length at 90 days after sowing, days of the first harvest after flowering, fruit number, fruit weight, fruit length, fruit girth, flesh thickness and total yield per plant. It also exhibited significantly different (p < 0.05) on days of to first male and female flower appearances. F1 progeny P11 × P92 recorded the highest total yield per plant (5376 g), followed by the parent P92 (4885 g). Positive and significant correlations were observed between total yield per plant and its contributing traits such as fruit weight (r = 0.81), fruit length (r = 0.73), flesh thickness (r = 0.65), fruit girth (r = 0.63), vine length at 90 days after sowing (r = 0.33) and fruit number (r = 0.27). This indicates a higher magnitude of variability for selection with a larger scope of a breeding program in future. The heritability (h 2 ) values ranged from 68.16% for the days of the first harvest after flowering to 99.81% for fruit weight. The highest value of genetic advance (GA) was recorded by the total yield per plant (3220.53%) while the lowest value was displayed by days of the first harvest after flowering (1.35%), respectively. High heritability and GA values indicated that some characteristics could be inherited by the next generation.