ASSESSMENT OF EGGPLANT (Solanum melongena L.) GENOTYPES UNDER NORTH SINAI CONDITIONS

Abstract

The present investigation aimed to assess twenty genotypes of eggplant under open field conditions of El-Arish region during two seasons (2016 and 2017) at the Experimental Farm, Faculty of Environmental Agricultural Sciences, Arish University. The evaluation was conducted using a randomized complete block design in three replications. Results of mean performance showed highly significant differences among genotypes for all traits, the best lines were Jor-2 for early flowering, PIG-4 for both early and total yield (kg/plant) and Spa-3 for average fruit weight (g). Estimation of phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) for all traits. However, close estimates of GCV and PCV indicated that genetic variance contributed with large portion in phenotypic expression of most characters. Therefore, phenotypic selection is effective and suitable for improvement. The genotypic (GCV) and phenotypic (PCV) coefficients of variation were moderate for plant height, early yield/plant, total yield and fruit firmness. On the other hand, estimations were high for number of branches/plant, average fruit weight, fruit length, fruit diameter and TSS (%), indicating sufficient genetic variability for these traits and so, genetic improvement through selection is effective. Heritability estimates in broad sense were high for early yield/plant, total yield /plant, average fruit weight, fruit length, fruit diameter and TSS (%). High heritability accompanied with high GAM were found for early yield/plant, total yield/plant, average fruit weight, fruit length, fruit diameter and TSS (%) , suggesting preponderance of additive gene action and improvement through selection is effective. The genetic divergence based on Euclidean distance among twenty genotypes were grouped into five divergent clusters. The pattern of distribution showed that cluster 5 involved the largest number (nine lines), followed by cluster 1 (consisted of six lines) and cluster 4 (included three lines). While, both clusters 2 and 3 involved one genotype. Cluster means showed that first cluster gave high performance for only fruit firmness, second cluster recorded the highest mean values for total yield /plant, fruit length and TSS (%). also, third cluster produced the highest mean value for plant height, early yield/plant, average fruit weight and fruit diameter. However, fourth cluster exhibited maximum values for number of branches/plant and early flowering. So, more emphasis should be given on clusters 1, 2, 3 and 4 for choosing parents for crossing which may produce new recombinants with desired economic traits.

Growth and Yield of Two Eggplant Cultivars During Summer Plantations Affected by Foliar Spray With Some Safety Materials

“…There was positive correlation between number of branches/plant and yield/plant, average fruit weight and fruit diameter. There was positive correlation between yield/plant and average fruit weight, fruit length and fruit diameter and also, between average fruit weight , length and diameter (Mahmoud and El-Mansy, 2018).…”

Molecular and Morphological Characterization of Turkish Local Eggplant (Solanum melongena L.) Populations

“…The results of genetic relationships showed that the genotypes were divided into two main groups. ISSR analysis and dendrograms demonstrated the relationships and revealed six cultivars (S3, S6, Moshtouhr, PIG-4, Jo=3, Black beauty) as the best ones which have a broad genetic background and must be introduced into breeding programs to produce hybrid seeds of eggplant (Mahmoud and El-Mansy, 2012). Li et al (2010) analyzed 56 Solanum species with the use of 55 SRAP primer combinations.…”

Relaciones entre variables en berenjena (Solanum melongena)

“…El éxito de cualquier programa de fitomejoramiento depende de la existencia de variabilidad genética en la población base, y de la eficiencia de la selección; para una selección eficaz es necesario estudiar la naturaleza de la asociación del carácter de interés con otros caracteres relevantes, y también la variabilidad genética disponible [6] [15] [9]. La herramienta estadística del coeficiente de correlación indica el grado y dirección de la asociación entre variables dependientes e independientes [16] [17] [11] [18] [1]. La correlación entre caracteres es importante cuando se quiere realizar selección simultánea de caracteres, o cuando un carácter de interés presenta baja heredabilidad, problemas de medición o identificación; en este caso, al seleccionar otro carácter de alta heredabilidad, de fácil medición o identificación y que registre alta correlación con el carácter deseado, el fitomejorador podrá obtener progresos más rápidos con respecto a la selección directa [18] [1].…”