Genetic Divergence Study in Bitter gourd (Momordica charantia L.)

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Bitter gourd (Momordica charantia L.) is considered as a valuable vegetable crop for its nutritional and medicinal properties, but it is neglected in terms of genetic and molecular breeding. Even though bitter gourd has a relatively broad phenotypic species variation due to diverse morphological traits, the studies on multi variate analysis is limited (Singh et al., 2013). Genetic divergence has been considered as an important factor in discriminating the genetically diverse parents for efficient and successful hybridization programme in order to get potential transgressive segregants and also provide new recombination of genes in the gene pool.

D2 statistics (Mahalanobis, 1936) is highly acceptable as it provides a measure of magnitude for divergence between two genotypes under comparison. Grouping of genotypes based on D2 analysis will be useful in choosing suitable parental lines for hybridization. Therefore, the present study was conducted to identify suitable parents out of 40 bitter gourd genotypes to initiate a breeding programme by identifying the clusters that are diverse and contain genotypes with good performance.

The present investigation was carried out at the Department of Vegetable Science, College of Horticulture, Yelachenahalli, Mysuru district, Karnataka during 2017-18. The experimental materials comprised of 40 indigenous genotypes of bitter gourd including some of the commercially released varieties from different institutes of India as listed in Table 1. The experiment was laid out in a randomized complete block design (RCBD) with two replications. The spacing used in this experiment was 120×90 cm. The recommended NPK fertilizer doses and cultural practices along with plant protection measures were followed to raise a commercial crop (Choudhary et al., 2003). Five randomly chosen plants in each replication of each entry were labelled and used for recording the observations. The mean of five plants was taken for analysis. Observations were recorded for 16 parameters like Vine length (m), Number of branches per vine, Duration of crop (days), Node at which first female flower appears, Days to first female flower opening, Days to 50 per cent flowering, Days to first fruit picking, Fruit length (cm), Fruit diameter (cm), Average fruit weight (g), Number of fruits per vine, Fruit yield per vine (kg), Fruit yield per hectare (t), Number of seeds per fruit, Flesh thickness (mm) and Ascorbic acid (mg/100g). The data were subjected to multivariate analysis of genetic divergence using Mahalanobis D2 statistic. Grouping of entries was done by Tocher’s method (Rao, 1952).

Table 1
List of genotypes and their sources of collection

The results from the analysis of variance for 16 characters indicated significantly high differences among 40 genotypes of bitter gourd under study. These 40 genotypes were grouped into six clusters. The distribution of genotypes into 6 clusters were presented in Table 2. Cluster I is the largest cluster having 32 genotypes followed by cluster II with four genotypes (GYB-3-1-2, Bit-3-1-2-1, Bit-3-1-1-1and ArkaHarit).

Cluster III (Yellapur Local-2), cluster IV (IC-68238), cluster V (Bit-18-1-1) and cluster VI (Jhalawar Local- 2) had one genotype each. The genotypes collected from different geographical regions were present in same clusters indicating that there was no association between geographical distribution and genetic diversity as reported earlier by Bhagwat et al. (2013) in bitter gourd.

The intra and inter-cluster D2 and D values among 6 clusters are furnished in the Table 3. and illustrated in Figure 1. Intra-cluster average D2 values ranged from 0 to 104.02. Among the clusters, cluster II had the maximum intra-cluster distance (104.02) followed by cluster I (96.08). The clusters like III, IV, V and cluster VI had no inter cluster distance (zero) as they were represented by single genotypes. The maximum inter cluster D2 value was found between cluster II and VI (1620.05) followed by cluster IV and VI (1262.95), cluster II and V (1098.44), cluster II and cluster III

Table 2
Cluster composition based on D2 statistics in bitter gourd

Table 3
Intra-cluster (diagonal) and inter-cluster D2 and D values in bitter gourd genotypes

Figures in parenthesis denotes corresponding D values

Highest inter cluster distance was found in cluster II and VI, suggesting that hybridisation between the genotypes from these clusters may lead to high heterotic effects and better segregants (Rabbani et al., 2012). Similarly, lowest inter cluster distance was observed in cluster III and V indicating that, genotypes exhibited higher genetic similarity (Tyagi et al., 2017).

The Per cent contribution of sixteen characters towards total divergence in bitter gourd genotypes is shown in Table 4. Among all the characters, ascorbic acid contributed the maximum (37.31%) to the diversity by taking first rank in 291 times out of 780 combinations, followed by fruit length (15.64% with 122 times ranked first), fruit diameter (14.36% with 112 times ranked first), flesh thickness (11.92% with 93 times ranked first), number of seeds per fruit

Fig1
Intra-cluster and inter-cluster distance of bitter gourd genotypes (Trocher’s method)

Mahalanobis Euclidean Distance (Not to the scale)

(9.49% with 74 times ranked first), days to first female flower opening (6.92% with 54 times ranked first), average fruit weight (1.28% with 10 times ranked first). While, there was little and negligible

Table 4
Per cent contribution of sixteen characters towards total divergence in bitter gourd genotypes

contribution from number of branches per vine (0.90%), number of fruits per vine (0.77%), fruit yield per vine (0.77%), vine length (0.51%) and node at which first female flower appears (0.13%). Similar results were reported by Sidhu and Pathak, 2016 in bitter gourd. However, the duration of crop, days to 50 per cent flowering, days to first fruit picking and fruit yield per hectare had no contribution towards genetic divergence. Similar findings were also observed by Sundaram (2008) and Bhagwat et al. (2013). Apart from the divergence, the performance of genotypes and the character with maximum contribution towards divergence should also be given due consideration which appear as desirable for improvement of bitter gourd (Deepa and Mariyappan, 2013).

Cluster means of forty genotypes showed that mean values of cluster varied for all the sixteen characters studied. Cluster II, V an VI performed better for the biometric parameters studied. Among the clusters, cluster VI was generally poor and cluster I as well as cluster III were intermediate in number of fruits per vine and fruit yield (Table 5.). Cluster II with four genotypes showed early flowering, flowering at lower node and early fruit picking. Cluster II had smaller fruits but the number of fruits per vine was highest. Cluster VI with one genotype had longer fruits (30 cm), lower fruit diameter with high average fruit weight and higher ascorbic acid content (112.43). Higher number of branches, longer duration of crop and higher fruit yield was noticed in cluster V with one genotype (Bit-18-1-1). Highest vine length was observed in the cluster III (3.67 m). Cluster I with maximum number of genotypes showed intermediate performance for almost all the characters observed. The best cluster with yield and yield components studied was cluster V followed by cluster III and cluster I. By using these elite germplasms, there is a scope for varietal improvement in bitter gourd.

Inter-crossing of genotypes based on the mean performance for their characters would be effective for further crop improvement. To develop early varieties with small fruits and higher number of fruits per vine, cluster II would be effective as it showed early flowering. Selection from cluster I would be useful in breeding moderately early flowering, intermediate yield with longer crop duration. Cluster VI can be used in breeding for longer fruits with greater average fruit

Table 5
The cluster mean of sixteen characters for six clusters in bitter gourd genotypes

weight and higher ascorbic acid content, as the demand is increasing in our country. To breed varieties with higher yield and late flowering, selection from cluster V would be useful.

Genetic divergence has been considered as an important factor in discriminating the genetically diverse parents for efficient and successful hybridization programme in order to get potential transgressive segregants and also provide new recombination of genes in the gene pool.Maximum inter cluster distance observed between cluster II and cluster IV followed by cluster IV and cluster V and cluster II and V. This indicates, the genotypes belonging tocluster II (GYB-3-1-2, Bit-3-1-2-1, Bit- 3-1-1-1, ArkaHarit), cluster IV (IC-68238) and cluster V (Bit-18-1-1) are more diverse and hence, hybridization between genotypes of respective cluster may improve the yield and quality of bitter gourd.