Research Article

Genetic Variability, Correlation and Path Analysis Study on Snap Melon (Cucumis melo L. var. momordica) Farmer’s Varieties

Pasha S. G, S. Marker and Sarath Chandra G

  • Page No:  636 - 644
  • Published online: 22 Jan 2020
  • DOI : HTTPS://DOI.ORG/10.23910/IJBSM/2019.10.6.2029

  • Abstract

The present investigation was carried out to assess the genetic variability, correlation and path analysis for yield and its component traits in 15 Snap melon farmer’s varieties of Eastern Uttar Pradesh for 17 quantitative characters during Kharif- 2018. Analysis of variance showed significance differences for all the quantitative traits at 1% and 5% level of significance. Indicating considerable amount of genetic variation in different farmer’s varieties of Eastern Uttar Pradesh. The low difference between GCV and PCV depicted that a little or no influence of environment on the expression of the various quantitative traits. High heritability coupled with high genetic advance was depicted by for fruit weight at average followed by number of seeds fruit-1 and 100 seed weight, indicating a predominance of additive gene effects and the possibilities of effective selection based on these traits for snap melon improvement. Therefore, these traits may be used as selection indices for genetic improvement of Snap melon farmer’s varieties. Node at first female flower appearance followed by number of fruits plant-1, fruit length, fruit diameter, fruit flesh thickness and fruit weigh at average show positive significant correlation and direct effect on yield plant-1 further proves their genetic worth for selection breeding through pure line/ pedigree method.

Keywords :   Variability parameters, correlation coefficient, path analysis, snap melon

  • Introduction

    Snap melon (Cucumis melo L. var. momordica) belongs to family Cucurbitaceae with chromosome number (2n=2x=24) is a tropical old-world cucurbit species (Somkuwar et al., 1997). India being one of the secondary centers of origin of Cucumis melo, is rich in its feral and cultivated forms which comprise nearly 40 species (Whitaker and Davis, 2008) and  Africa was suggested to be the region of domestication of melon based on the availability of many specimens of wild Cucumis (Koli and Murthy, 2013). A modest gene bank of snap melon has been established in the Department of Vegetable Crops, Punjab Agricultural University, Ludhiana, India (Dhillon et al., 2009). A wide range of variability is met from Gujarat in the west to West Bengal in the east (Seshadri and More, 2002). It is very popular in arid and semi arid regions (Hazra et al., 2011). It is also cultivated in other countries of Southeast Asia, for instance Myanmar (Yi et al., 2009) and Vietnam.

    Indian snap melon accessions have been reported to be a good source for disease and insect pest resistance, and many of them are used as reference accessions world widely (Cohen et al., 2003) and are good sources of nutrients, vitamin C, sugars, minerals and dietary fibers. A 100g edible fruit of snap melon contains 15.6g carbohydrates, 18.6 mg vitamin-C, 0.3 g protein, 95.7% moisture (Peter and Hazra, 2012) and provides 74.0 kcal energy (Goyal and Sharma, 2009). However, the fruits can be stored for 2-3 weeks (Kumar et al., 2013).

    It is cultivated as a mixed crop along with maize, sorghum and pearl millet in rainy season or as a sole crop in summer season (Seshadri and More, 2009). The mature fruits of snap melon are peeled off; sun dried and preserved which is locally known as khelra (Pareek and Samadia, 2002). Snap melon are commonly called ‘Phut,’ which means ‘to split.’ Fruit cracking is either longitudinal or starting in the middle of fruit, though in some instances only skin peeling (longitudinal or random) occurs (Dhillon et al., 2007).

    The understanding of genetic variability present in a given crop species for the traits under improvement is imperative for the success of any plant breeding program. Heritability is in conjunction with high Genetic advance as percent of mean would be more useful in predicting the resultant effect in the selection of the best genotypes for yield and its attributing traits (Pandey et al., 2009). Coefficient of correlations is the measure of level of the relationship between two or more traits related to yield. Path coefficient was estimated to find out the association and quantify the direct and indirect influence of one character upon another. Yield in snap melon is the product of several interrelated traits, so a successful breeding programme depends largely upon the information on the genetic variability and correlation of desired quantitative traits with yield. Therefore, an assessment was made about the performance of various economic traits and the extent of variability, heritability, expected genetic advance and interrelationship of yield components in snap melon was measured.

  • Materials and Methods

    Fifteen farmer’s varieties of Snap melon were obtained from local farmers of Eastern Uttar Pradesh and are grown in a Randomized Block Design with three replications during Kharif- 2018 at Field Experimentation Centre of the Department of Genetics and Plant Breeding, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (Allahabad), U.P. Standard cultural practices were followed and recommended dose of fertilizers were given to raise a good crop.

    The observations were recorded on five random plants for each treatment in each replication for node at first female flower appearance, node at first male flower appearance, days to first female flower opening, days to first male flower opening, vine length, number of nodes per vine, days to first harvest (DAS), number of fruits per plant, fruit length (cm), fruit diameter (cm), seed cavity length (cm), seed cavity breadth (cm), number of seeds per fruit, fruit flesh thickness (cm), 100 seed weight (g), average fruit weight (kg) and yield per plant. The data collected were subjected to Analysis of Variance as suggested by Panse and Sukhatme (1967). Genotypic Coefficient of Variation and Phenotypic Coefficient of Variation was calculated by using the procedure suggested by Burton (1952). Heritability in broad sense was computed by using the formula given by Burton and Devane (1953). The genetic advance for selection intensity at 5% was calculated by the formula given by Johnson et al. (1955). Correlation coefficients were determined as suggested by Al-Jibouri et al.(1958). The Path Coefficient analysis was done according to Dewey and Lu (1959).

  • Results and Discussion

    The mean sum of squares due to the treatments showed significant differences among all the genotypes at 5% level of significance and 1% level of significance for all the characters. Indicating that these varieties were genetically variant from each other and similar findings were reported by Pandey et al, (2009) in snap melon.

    The magnitude of GCV and PCV in (Table 1) were found high (>20) for yield plant-1, fruit weight at average, 100 seed weight, fruit flesh thickness, number of seeds per fruit-1, fruit length and node at first female flower appearance. The higher phenotypic coefficient of variation (PCV) than those of genotypic coefficient of variation (GCV) indicated the predominant role of environment on the expression of these traits and low GCV and PCV were recorded for days to first female flowering opening. A little possibility of improvement of these characters through selection could be used during crop improvement program. Therefore, response to direct selection may be effective in improving these traits. Similar findings were reported by Tomar et al. (2008), Samadia et al.(2009) in snap melon.

    Heritability in broad sense was found to be high (>60%) for all the characters except for node at first male flower appearance followed by number of nodes per vine and number of fruits per plant. Characters showing high heritability indicate that they are less influenced by environment and there could be of greater correspondence between phenotypic and breeding values and there is a scope for improvement in these characters through direct selection.

    High heritability (>60%) coupled with high genetic advance as percent mean (>30%) was recorded for fruit weight at average (99.85% and 143.79%) followed by number of seeds fruit-1 (99.11% and 16.09%), 100 seed weight (90.33% and 42.94%), fruit length (86.84% and 58.57%), yield plant-1 (85.71% and 150.43%), seed cavity length (81.69% and 31.58%), fruit diameter (78.85% and 37.36%), fruit flesh thickness (78.58% and 49.95%) and node at first female flower appearance (69.45% and 44.57%). Therefore indicating a predominance of additive gene effects and the possibilities of effective selection can be conducted based on these traits for crop improvement program. Similar findings were reported in Snap melon by Joseph (2012), Muddarsu and Venkat (2013), in cucumber by Ene et al., (2016), in Melon by Malik (2012), in Muskmelon by Tomar et al. (2008) and in Watermelon by Choudhary et al., (2012)Thus these characters offer the best possibility of improvement through selection procedures.

    For achieving rational improvement in yield and its related parameters, knowledge on mechanism of correlation, cause and effect relationship provides a basis for formulating suitable selection methods for the yield.

    In this present investigation in (Table 2) node at first female flower appearance (rg= 0.565**, rp= 0.417**), days to first female flower opening (rg=0.177*, rp= 0.125*), vine length (rg=0.335*, rp= 0.310*), number of fruits plant-1 (rg=0.892**, rp=0.626**), fruit length (rg=0.561**, rp= 0.537**), fruit diameter (rg=0.783**, rp=0.656**), seed cavity breadth (rg=0.480**, rp= 0.438**), fruit flesh thickness (rg=0.675**, rp= 0.589**) and fruit weight at average (rg=0.944**, rp=0.876**) had shown significant positive correlation with yield per plant at both phenotypic and genotypic levels representing that any improvement in these traits will increase the yield in snap melon. These observations are in conformity with the findings of Reddy et al., (2007) and Pandey et al., (2009) in snap melon.

    Whereas, days to first harvest (DAS) (rg=-0.397**, rp= -0.359*) showed significant negative correlation with yield per plant at both phenotypic and genotypic levels representing that any improvement in these traits would reduce the yield in snap melon. The expression of yield depends upon a number of yield contributing traits. It is not always independent in their action but may be inter-linked. The selection practiced for one character may simultaneously bring change in the other related character. Thus the information of the magnitude and direction of association between the component characters is essential for the improvement in the desirable direction.

    The estimates of correlation coefficient mostly indicated inter-relationship of different characters; however it did not furnish the information on cause and effect. Under such situation path analysis would help the breeder to identify the index of selection. Path coefficient analysis was conducted in order to study the direct and indirect effect of individual components characters on dependent variable .i.e., yield in snap melon. Study of path coefficient enables the breeder to concentrate on the variables which show high direct effect on yield. The genotypic and phenotypic correlation coefficients of yield with other traits were further partitioned into direct and indirect effects and results are presented in (Table 3).

    Path analysis reveals the direct and indirect effects of characters on yield (Table 3). From the study, it is revealed that the characters i.e., node at first female flower appearance (G=0.192, P=0.123), number of fruits plant-1 (G=0.173, P=0.380), fruit length (G=0.276, P=0.068), fruit diameter (G=0.028, P=0.056), fruit flesh thickness (G=0.282, P=0.063) and fruit weight at average (G=0.903, P=0.678) showed positive direct effect on grain yield at the both phenotypic (P) and genotypic (G) levels indicating the effectiveness of direct selection, Therefore these traits can be selected for crop improvement program. These observations were similarly reported in Snap melon by Pandey et al., (2009), Joseph (2012), Muddarsu and Venkat (2013)  and Reddy et al. (2007), in Muskmelon by Nagri et al,. (2009), Choudhary et al,. (2004), Pandey et al. (2003), and Tomar et al. (2008), in Sweet melon by Ibrahim and Ramadan (2013) and in Watermelon by Choudhary et al. (2012).

    The components of residual effect of path analysis in yield and its components traits is 0.0252 at genotypic level and 0.0378 at phenotypic level. The lower residual effect indicated that the characters chosen for path analysis were adequate, appropriate and further indicated that characters included in this study were effective for improving the yield.

  • Conclusion

    Characters like node at first female flower appearance followed by number of fruits plant-1, fruit length, fruit diameter, fruit flesh thickness and fruit weight at average showed positive significant correlation and direct effect on yield plant-1 further proves their genetic worth for selection breeding through pure line/ pedigree method.

  • Acknowledgment

    The Authors are sincerely grateful to the Hon’ble Vice-Chancellor, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj and to PPV-FRA, Ministry of Agriculture and farmer Welfare Government of India for providing the necessary facilities to complete my research work.

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