Genetic Diversity Analysis by D2 Clustering for Mineral Nutrient Composition of Watermelon Genotypes (Citrullus sp.)

Watermelon [Citrullus lanatus var. lanatus (Thunb.) Matsum. and Nakai] is a major cucurbitaceous vegetable rich in many health benefitting compounds including citrulline, lycopene, arginine and glutathione (Ren et al., 2012). Globally it is being grown over in about 100 countries which accounts for 7 per cent of the total area under vegetable crops. Watermelon is also excellent source of beta-carotene and vitamin C, while the seeds are high in vitamin E and antioxidants, minerals like zinc and selenium. Its fruits are more diverse in size, shape, rind thickness, rind colour, rind pattern, flesh colour, sugar content, carotenoid, flavonoid, mineral and nutrient composition. The genus Citrullus is comprised of four species (C. lanatus, C. ecirrhosus, C. colocynthis and C. rehmii) (Levi et al., 2001). Citrullus colocynthis (L.) a wild perennial species growing extensively in Northern Africa and South Western Asia. Citrullus colocynthis is considered as the putative ancestral or progenitor species of watermelon, which is commonly grown in north western parts of India (Jarret et al.,1997).

Presently, there is a worldwide interest in improving the nutrition content of fruits and vegetables. Although watermelon fruits have been improved for yield, sugar content, disease and pest resistance, efforts to improve the mineral nutrition content is limited, which requires identification of elite parents from diverse groups.  Multivariate analysis techniques such as D2 statistics and principal component analysis allow selection of elite genotypes from a group of diverse germplasm (Nalla et al., 2014). The present study, genetic diversity of different watermelon genotypes were studied in terms of some mineral nutrient contents. Elite genotypes identified here may be used for improving the nutrition content of watermelon varieties.

Experimental details
 
The study was conducted at the Research Farm of the Division of Vegetable Science, ICAR-Indian Agricultural Research Institute, New Delhi, in the 2017 spring summer and kharif seasons using eighty watermelon genotypes. The genotypes are procured from the United States Department of Agriculture and maintained in the division of vegetable science. The list of genotypes used in this study is mentioned in Table 1. The experimental site is located at an elevation of 228.61 metres above mean sea level (28^o08’N, 77^o12’E). The nursery was grown in polythene bags in poly house and 30 days old seedlings were transplanted. The plants were transplanted on raised beds of 2.5 m apart with 0.75 m spacing between the plants. The crop was grown following recommended agronomic practices along with adopting necessary plant protections measures.
 
Estimations of mineral nutrient contents
 
Fruit of each genotype in replicated trial were harvested at fresh marketable stage. For estimating mineral elements, 100 g of finely chopped fruit was oven dried at 60-65oC followed by grinding in a pestle-mortar and sieving using a 1 mm sieve. The dried sieved fruit powder was stored in an airtight aluminum container. Mineral nutrients were determined by digesting oven dried samples (1 g) overnight in a diacid solution of perchloric acid and nitric acid in a 1: 1 ratio and then heating to 200oC for 2-3 hours until the solution became colourless (Singh et al., 1999). The solution was filtered through Whatman No. 42 filter paper and the final volume was made up to 100 ml using double distilled water. On an Atomic Absorption Spectrophotometer (AAS-4141), the filtrate was used to determine the concentrations of Zn, Mn, Cu and Fe at wavelengths of 213.9 nm, 279.8 nm, 324.8 nm and 248.3 nm, respectively. The concentrations of K and Na were determined at 766.5 and 622 nm wavelengths respectively using a Flame photometer (ELICO CL-361). Ca and Mg contents were determined by EDTA titration method (Tandon, 1998).
 
Statistical analysis
 
The statistical analyses like ANOVA, principal component analysis (PCA) were carried out by using INDOSTAT software package Version 8.1, developed in the year 2010. Genetic diversity in the collection was assessed by determining Mahalanobis (1936) D2 statistics. The sample similarities were calculated on the basis of pair-wise Euclidean distance (Rao, 1952).

Analysis of variance indicated substantial amount of genetic diversity for the mineral nutrients (n=8) in the genetic materials used for this study. The range of variation was very high for many mineral contents such as Zn (0.03 to 18.11 mg/100 g), K (369.93 to 8326.2 mg/100 g) and Na (38.00 to 728.17 mg/100 g) reflecting high selection prospects for these traits to improve the performance through breeding programme (Data not presented). For an initial of successful breeding programme, it is desirable to select genetically divergent suitable parents based on information about the genetic variability and genetic diversity present in the available germplasm. D2 statistics showed that potassium content contributed highest (25%) to divergence followed by magnesium content (22.7%) and manganese content (11%) (Table 2). Eighty watermelon genotypes were classified into 8 distinct clusters using D2 statistics based on mineral nutrient contents. Among 8 clusters (Table 3 and Fig 1), cluster I comprised of maximum number of genotypes (68) and except few (13) all of them belong to lanatus group. Cluster II consist of 6 genotypes and except one (DWM 39) all of them belong to lanatus group. All other 6 clusters consisted of 1 genotype in each. Among 8 clusters (Table 4), cluster II showed highest intra cluster distance (342.14) followed by cluster I (279.07), whereas minimum intra cluster distance recorded in cluster III, cluster IV, cluster V, cluster VI, cluster VII and cluster VIII (0.00). Based on inter-cluster distance the maximum diversity was observed between clusters VI and VIII (3234.85), followed by clusters II and VIII (1347.37) and clusters III and VIII (983.62), suggesting wide divergence between these clusters. The genotypes of cluster III (Table 5) recorded maximum sodium (728.17 mg/100 g) and potassium (8326.20 mg/100 g), while cluster VII recorded minimum sodium (108.10 mg/100 g) and potassium (1159.80 mg/100 g). Cluster VI recorded maximum zinc (18.11 mg/100 g), while cluster IV recorded minimum zinc (0.04 mg/100 g); cluster VIII recorded maximum manganese (0.15 mg/100 g) and copper (0.07 mg/100 g), while cluster III recorded minimum manganese (0.01 mg/100 g) and copper (0.01 mg/100 g); the higher iron was found in cluster IV (2.34 mg/100 g), while it was lower in cluster I (0.88 mg/100g). Cluster VII recorded the maximum magnesium content (4.47 mg/100 g), while cluster III recorded minimum magnesium content (1.23 mg/100 g). The higher and lower calcium content were found in cluster V (19.92 mg/100 g) and cluster I (10.19 mg/100 g), respectively. Genotypes within the same clusters were more similar than those between clusters. Although grouping of watermelon genotypes on the basis of yield traits have been reported by Choudhary et al., 2012, Gbotto et al., 2016 and Singh et al., 2017, no studies considered grouping based on mineral nutrient contents. However, genetic diversity of muskmelon germplasm for nutrient composition has been reported by Bhimappa et al., 2018. In this study, we found that no clusters were superior in terms of all the traits, which indicates wide divergence of the traits among the studied genotype.  Similar findings were reported by Bhimappa et al., 2018.



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Principal component analysis revealed that the first two principal components (PCs) together controlled 52.92 % of total variability (Table 6 and Fig 2). PC1 and PC2 individually explained about 31.32% and 21.60% of the total variance, respectively. This result is similar to the findings of Bhimappa et al. (2018), in which first two PCs explained cumulative 48 percent of total variations for mineral nutrient contents in muskmelon. PC1 showed positive factor loading for manganese (0.55), copper (0.54), magnesium (0.36), iron (0.34), calcium (0.29) and zinc (0.21). PC2 showed highest positive factor loading for potassium (0.70) and sodium (0.69).  Therefore, manganese, copper, magnesium and iron contents contributed largely to the variation present in the studied genotypes. On the basis of nutritional attributes, 6 genotypes viz; DWM 164, DWM 129, DWM 165, DWM 115, DWM 12 and DWM 45 were identified as superior. Based on higher genetic distance among clusters and higher mean value of genotypes for nutritional traits, DWM 164, DWM 129, DWM 165, DWM 115, DWM 142, DWM 117, DWM 45, DWM 196 and DWM 12 may be utilized in hybridization programme for developing nutrient rich watermelon varieties/ hybrids.

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The results of this study showed the presence of significant variations in mineral nutrient composition of watermelon genotypes. Variations were relatively large for Zn, K and Na contents indicating the concentrations of these minerals may be further improved. D2 analysis placed the eighty genotypes in eight distinct clusters indicating divergence among the studied genotypes. Among minerals K, Mg and Mn contents contributed largely towards diversity. Principal component analysis showed more than 50% of cumulative variance was controlled by PC1 and PC2. The selected genotypes in this study may be used to develop nutrient rich watermelon varieties including hybrids.

The authors are grateful to ICAR-Indian Agricultural Research Institute, New Delhi, India, for providing research financial support and laboratory facilities during this study.