Correlations and path analysis for quantitative characteristics in semi-prostrate cowpea bean genotypes (Vigna unguiculata (L.) Walp)

Abstract

The cowpea is the most important legume in the Colombian Caribbean, due to its positive impact on the food and nutritional security of low-income rural families. It is cultivated by small producers, but its yields per hectare do not exceed 600 kg, due to the use of obsolete cultivars. The objective of the research was to estimate the correlations between seven quantitative characters and the path analysis between grain yield and six quantitative characters, with the results of the evaluation of 10 genotypes of semi-prostrate growth habit, high grain yield, grown in eight environments of the humid and dry tropics of the Colombian Caribbean region, under the randomized complete blocks design, with four repetitions. Significant differences between environments, genotypes and genotype x environment interaction were detected. Genotypic correlations were of greater magnitude than phenotypic, highlighting the correlation between grain width (GW) and grain yield (GY), rP = 0.69 *, rG = 0.78 *, also between the weight of 100 seeds (100SW) and GW, rP = 0.97 **, rG = 0.99 **. The characters GW and number of pods per plant (NPP) had positive direct effects on the GY, with an indirect negative effect of NPP by way of GW, while the height of the first pod (HFP), the number of seeds per pod (NSP) and the 100SW directly and negatively influenced the GY of the 10 semi-prostrate cowpea cultivars.

Screening the Soybean Varietal Lines for Selecting High-Yielding and Better Agronomic Traits Producing lines

“…Erect varieties showed an increase in yield and a spreading variety showed no response (Table 6). (Li et al, 2022;Kuzbakova et al, 2022;Kushwah et al, 2020;Araméndiz-Tatis et al, 2023;Choi et al, 2021). In terms of Flower color (FC), twenty varietal lines and two control varieties, Rawal and Jack, have white flowers while the remaining varieties had pink flowers (Table 6).…”

Path analysis between fruit biometric traits of Caesalpinia ebano H. Karst

“…In genetic improvement programs, correlations between traits of agronomic and silvicultural interest are important to facilitate and increase selection efficiency (Espitia et al, 2017). The improvement of a trait of interest can be done through the indirect selection of other traits that are associated with it and less complex, with higher heritability, which would make the selection more efficient and safe (Gupta et al, 2017;Araméndiz-Tatis et al, 2020;. Studies of associations between traits based on their phenotypic and genetic correlations make it possible to improve the efficiency of selection in genetic improvement programs, improve the quality of the products, and achieve greater genetic progress (Pérez-Pelea et al, 2018;Araméndiz-Tatis et al, 2020;Araméndiz-Tatis et al, 2021).…”

“…The improvement of a trait of interest can be done through the indirect selection of other traits that are associated with it and less complex, with higher heritability, which would make the selection more efficient and safe (Gupta et al, 2017;Araméndiz-Tatis et al, 2020;. Studies of associations between traits based on their phenotypic and genetic correlations make it possible to improve the efficiency of selection in genetic improvement programs, improve the quality of the products, and achieve greater genetic progress (Pérez-Pelea et al, 2018;Araméndiz-Tatis et al, 2020;Araméndiz-Tatis et al, 2021). Several authors have developed correlation studies between the biometric traits of the fruit and its seeds in forest species (Leão et al, 2017;Dos-Santos et al, 2018;Ristau et al, 2018).…”

“…According to Gupta et al (2017) some traits are often influenced by variations in other traits, so care must be taken with the simple interpretation of the correlation value since direct selection ends up being inefficient (Araméndiz-Tatis et al, 2020). In this sense, Lekshmanan & Vahab (2018) pointed out that the statistical analysis of the path is proposed as a solution to decompose the correlations into direct effects of X on Y and the indirect effects of X on Y via other independent variables in a correlation system.…”