Correlation and Path Coefficient Analyses in Sweet Melon (Cucumis melo Var. Aegyptiacus L.) Under Irrigated and Drought Conditions

Abstract

Genotypic correlation and path analyses were carried out for growth, yield and fruit quality traits in 13 sweet melon genotypes collected from different places in Egypt. Seeds of these melon populations were sown under irrigated and drought stress conditions. The analysis of variance for the studied traits showed that the differences among genotypes were highly significant for all studied traits under irrigation and drought stress. Under irrigated conditions, total yield per plant was positively and significantly correlated with fruit weight, flesh fruit thickness and fruit length. Positive direct effects were exhibited for fruit weight, number of fruits per plant and stem length on total yield per plant, while maximum positive indirect effects on total yield per plant were exhibited by fruit length and flesh fruit thickness through fruit weight. In case of drought stress conditions, total yield per plant had the highest positive and significant correlation with fruit weight followed by flesh fruit thickness, fruit length and stem length. Fruit weight had the greatest positive direct effect on total yield per plant followed by number of fruits per plant, fruit length and total soluble solid content. Flesh fruit thickness and fruit length had high positive indirect effect on total yield per plant via fruit weight. The results obtained from correlation and path analyses showed that the efficiency in the selection for total yield per plant in sweet melon should increased through the selection of fruit weight under irrigated conditions and fruit weight and fruit length under drought conditions.

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

“…, Pandey et al (2003), and Tomar et al (2008), in Sweet melon by Ibrahim and Ramadan (2013) and in Watermelon by .…”

Genetic variability studies in response to drought under different water regimes in muskmelon (Cucumis melo L.)

“…Similar observations have been found by Torkadi et al (2007) for days taken to first female flowering, number of fruits per vine and weight of fruits per vine; Rashidi and Seyfi (2007) for number of fruits per plant and fruit weight; Rad et al (2010) for sugar percentage, fruit weight and fruit yield ; Keshavarzpour et al (2011) for fruit yield, number of fruits per plant and fruit weight; Reddy et al (2013) for vine length, number of primary branches per vine, days to appearance of first pistillate flower, average fruit weight and fruit yield per plant; Ibrahim and Ramadan (2013) for stem length, number of primary branches per plant, days to first female flower appearance, fruit weight, number of fruits per plant and total fruit yield per plant attributes respectively in muskmelon (Cucumis melo L.). Genetic variability is important in order to realize response to selection pressure.…”

Parámetros de selección para el rendimiento en melón (Cucumis melo) cultivado bajo invernadero

“…El énfasis principal en fitomejoramiento de melón es el desarrollo de variedades de alto rendimiento y buena calidad del fruto. El rendimiento del melón es un rasgo cuantitativo complejo, pues es gobernado por un gran número de genes, y es afectado considerablemente por el ambiente (Reddy, Begum, Sunil, & Reddy, 2017;Ibrahim & Ramadan, 2013); por lo tanto, el fitomejoramiento para el rendimiento debe ser realizado mediante el enfoque de componentes de rendimiento. La influencia de cada característica sobre el rendimiento puede ser conocida a través de la correlación y los estudios de sendero (Reddy et al, 2017).…”

“…Sin embargo, la correlación por sí misma no revela el panorama completo de la dependencia de un componente sobre otro. Por lo tanto, el entendimiento de los efectos directos e indirectos de las principales variables que contribuyen con el rendimiento, es de suma importancia para la selección de genotipos de alto rendimiento (Choudhary, Fageria, & Dhaka, 2004;Ibrahim & Ramadan, 2013;Reddy et al, 2017). El análisis de coeficiente de sendero brinda un mejor índice de selección que solamente el coeficiente de correlación, por medio de la separación de los coeficientes de correlación del rendimiento y sus componentes, en efectos directos e indirectos (Tomar et al, 2008;Mehta et al, 2009).…”