Association studies on Yield and Yield Components in Snap Melon (Cucumis Melo. Var. Momordica)

 Snap melon (Cucumis melo var. momordica) is one of the important groups of Cucurbitaceous crop worldwide and play an important role in internationaltrade. India being one of the secondary centre of origin of Cucumis melo var. momordica which comprises nearly 40 species. This is a potent crop, the fruits are rich in vitamin C, calcium and iron (Dhillon et al., 2014). It also possesses numerous nutraceutical and pharmaceutical properties. It is cultivated in various parts of the world including India and Pakistan. It is very popular in arid and semiarid regions. In North India snap melon is commonly called as ‘Phoot’ which means “To split”. The large scale cultivation of ‘phoot’ is confined to the states of Uttar Pradesh, Rajasthan, Haryana, Punjab and Bihar in India. In Kerala it is called as Kanivellari (fruit cucumber) or Pottuvellari (split/ crack cucumber) and cultivated in Thrissur, Ernakulam and Malappuram districts of the state. In Tamil Nadu, it is grown in Ramanathapuram, Madurai, Virudhunagar, Tirunelveli, Villupuram, Karur and Pudukkottai districts. The snap melon has many medicinal properties like antidiabetic, antioxidant activities antihyperlipidemic activities (Yadav et al., 2022; Srivastava et al., 2020). There are several local varieties of melon grown in different regions of India. A wide range of variability is met from Gujarat in the west to West Bengal in the east. Correlation analysis is important to determine the association between the yield and yield components. The obscure nature of yield is largely inclined by a number of component traits. Hence, information on the strength and direction of association of these component characters with yield and also interassociation among themselves will be very useful in formulating an effective and viable selection parameter for improvement of yield (Kumar et al., 2023).An estimate of genotypic and phenotypic correlation coefficients gives a measure of genotypic association since it is an inherited relationship between the traits. The greater the magnitude of correlation coefficient, the stronger the association. After studying the correlation, selection pressure may be more easily exerted on any of the easily observable characters showing a close association with yield. Hence, the present investigation was planned to unravel the 
correlation of yield and yield attributing traits in snap melon.

The experiment was carried out at Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore.  The experimental materials for the study consisted of six parents namely P1 (Amaravathi), P2 (Kothayapatti local), P3 (Thambipatti), P4 (Kariapatti), P5(Gujarat local) and P6 (Thirumangalam long) and thirty hybrids were produced through full diallel mating design. The experiment was laid out in a Randomized Block Design.Each plot consisted of ten plants in a row at 60 x 60 cm inter and intra row spacing. All the recommended package of practices was adopted for raising a healthy crop. Five randomly selected plants, excluding the border ones, from each plot of all the two replications were tagged and used for recording the observations and average values were computed. The association between yield and components traits and among themselves was computed based on per se performance of the genotypes. Phenotypic correlation was worked out by the formulae recommended by AlJibouri et al. (1958). Phenotypic correlation coefficient was computed using the following formularph 1.2=Where, ×100 rph 1.2 = phenotypic correlation coefficient  between the traits 1 and 2  Co Vph 1.2 = phenotypic covariance between characters 1 and 2 
σ2ph 1 = phenotypic variance for the character 1 
σ2ph 2 = phenotypic variance for the character 2

Association of characters. The correlation coefficient between fruit yield and its components traits and inter correlation among the 
different yield attributes are presented in (Tables 1 to 3) 

 The present study revealed that the traits fruit girth, fruit weight, number of primary branches, flesh thickness, number of female flowers per plant, fruit length, fruit girth, fruit weight,  days to first harvest, number of fruits per plant, vine length, TSS, protein, carbohydrate, calcium, iron showed high positive significant correlation with fruit yield per plant. Hence during selection more weightage should be given for these traits for obtaining high fruit yield.