Cowpea data for three environments in the main rainy season in northern Ghana for 2016 cropping season.
The research hypothesis was that, F2-derived F8 Recombinant inbred lines could perform differently and even yield better than the parental checks under main growing season conditions in the three agro ecologies of northern Ghana. Specifically, the study was designed to identify promising inbred lines with high yield potential, and then identify inbred lines with stable mean yield performance either with specific adaptation to a particular environment or across the three environments that will subsequently be recommended to farmers in the Guinea, Sudan and Transitional agro ecologies of Ghana The experimental design used at each test location was a randomized complete block design with four replications. The seeds were planted according to the conditions for each location but were thinned to one plant per hill. Plot size was 3 m long; each plot contained 5 rows of 10 plants per row; with plant spacing of 60 cm between rows and 20 cm within rows with the number of entries being 24. Thus, each experimental unit consisted of 50 plants per plot, and each block contained 24 plots giving the total plots as 96 plots for the whole experiment for each location. Data were recorded on plot bases for all three locations. Days from planting to first flowering for each plot was recorded, the date to 50% flowering data was recorded when half of the plants per plot produced flowers. Based on this information, the days to 50% flowering were estimated. At harvest, number of pods per plant, number of seeds per pod and hundred seed weight were taken as average of five randomly selected plants within a plot excluding the border plants. The weight of hundred seeds (g) for each treatment was determined by the use of an electronic balance. Data on grain yield was recorded on plot bases using three middle rows of 10 plants (30 plants per plot) in grams extrapolated to t/ha The data for each location were subjected to Analysis of Variance (ANOVA) using GenStat statistical package 12th edition. Combined analysis of variance across locations for grain yield and yield components were also carried out to determine the interactive effects of genotypes by environment. The additive main effect and multiplicative interaction (AMMI) and the genotype, and genotype by environment interaction were concurrently determined using the Breeding management software (BMS) and GenStat. Analysis of variance for each location as well as combined analysis of variance across all the locations revealed that there were significant differences among genotypes and their environments for grain yield and yield components indicating the presence of variability in the inbred lines as well as diversity of growing conditions and locations.