Multivariate analysis for yield and yield-related traits of sesame (Sesamum indicum L.) genotypes

Abstract

Sesame production under irrigation is limited in Ethiopia because of in availability of high yielding varieties, inadequate and inefficient irrigation schemes, and insignificant awareness of producers. This study, comprising 13 sesame genotypes, was conducted around Humera and Werer during 2018 and 2019 under irrigation. The design was randomized completely block design with three replications and the objectives were to develop high yielding genotypes and identify important agronomic traits. Multivariate statistical methods like Additive Main Effect and Multiplicative Interaction (AMMI) model, Principal Component Analysis, Cluster and factor analyses were used. The genotypes (6.22%), environments (42.62) and Genotype × Environment Interactions (25.09%) were statistically (p < 0.001) significant for the agronomic traits. The grain yield in each observation varied from 383 kg/ha to 2044 kg/ha and the grand mean yield was 820.19 kg/ha. The highest mean yield was recorded from G12 (948.6 kg/ha) followed by G4 (938.9 kg/ha) while the lowest was recorded from G8 (703.1 kg/ha). G1, G4, G12, G5, G8, G11 and G13 are identified as unstable genotypes while G2, G3, G6, and G9 are stable genotypes. The genotypes were grouped in to four clusters and cluster-II was characterized as the high yielding cluster and it was also associated with grain yield, pods per plant, branches per plant and thousand seed weight. Branches per plant, pods per plant and thousand seed weight may be most determinant and crucial in developing high yielding sesame varieties. This finding recommends that G4 and G6 are desirable genotypes and can be used for irrigation production.

Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis

“…Days to maturity showed a negative correlation with thousand seed weight and seed yield per plant. This result is in line with the report of Baraki et al (2020).…”

“…The number of primary and secondary branches and increase in basal leaf area contributed to the increase in seeds per capsule in a positive direction. Similar results were reported by Singh et al (2018), Baraki et al (2020) and Deepak Gupta et al (2021).…”

“…The important yield traits both through correlation and PCA analyses showed a negative association with days to maturity which was also observed by Baraki et al (2020).…”

“…Statistical tools such as correlation and multivariate grouping techniques namely cluster analysis and Principal Component Analysis (PCA) reveals the pattern of relationships between genotypes and explain the relative contribution of traits or genotypes to the observed variability in the genotype's collection. PCA has been widely used for studying genetic variability in sesame (Pandey et al, 2015;Baraki et al, 2020;Teklu et al, 2021). With this background, the present study was taken up with the main objective to analyze the genetic relationship and variability for seed yield and its related traits in a collection of 55 genotypes through correlation and multivariate analysis.…”

Multi-environmental evaluation of vegetable soybean for adaptation and stability in Benin

“…However, there are no documented studies on edamame in West Africa. For edamame production to become commercially viable, growers need cultivars that will perform well in their environment, as yields and agronomic traits in crop varieties are often affected by the so-called genotype by environment interaction (GEI) (Agbahoungba et al, 2017;Agoyi et al, 2016Agoyi et al, , 2017Baraki et al, 2020). The objective of this study was to assess vegetable soybean cultivars for adaptation and yield stability in Benin.…”