Study on character association and path analysis in Korarima (Aframomum corrorima (Braun) Jansen) germplasms at Jimma Southwestern, Ethiopia

Abstract

In Ethiopia, the spice Korarima is one of the most important cash crops. The Jimma agricultural research institute recently gathered a large number of Korerima genotypes from Ethiopia's key growing regions to analyze genetic variations between genotypes and produce varieties. However, no characterization or genetic variability research has begun in these korerima collections. Thus, character association and path coefficient analysis was performed on twenty-five Korarima germplasm samples collected from various agro-ecological regions of Ethiopia to estimate the extent of correlation between characters at the phenotypic and genotypic levels, and compare the direct and indirect effects of the characters on yield. Each incomplete block has a 5 × 5 simple lattice design with two replications and five accessions in Jimma agricultural research center during the 2020 main cropping season. Nine plants were planted in each plot, with a row and plant spacing of 1.8 m. The genotypes were grown under Sesbania shade trees. At both the genotypic and phenotypic levels of significance, yield per plant had a positive and significant relationship with the total tiller, bearing tiller, number of leaves per stem, number of capsules per plant, the weight of fresh capsule, and length of dry capsule, indicating the possibility of correlated response to selection. The number of capsules per plant had the greatest direct effect on yield, according to genotypic path analysis. This proves that the correlation is real and that direct selection using these features will be quite effective. The diameter of the dry capsule, total tiller, dry capsule weight, and fresh capsule length all have a direct positive effect on yield. Varietal, environmental, and edaphic elements, as well as management practices, might all contribute to the variation. The findings might help with future breeding and quality-improvement efforts.

Spatial-Temporal Driving Factors of Urban Landscape Changes in the Karst Mountainous Regions of Southwest China: A Case Study in Central Urban Area of Guiyang City

“…The method of path analysis was first proposed by Sewall Wright in 1921 [49,50]. The path analysis was able to effectively indicate the direct effect of the variable of interest on the dependent variable and to estimate the indirect effect of the independent variable on the dependent variable [49].…”

“…But the traditional steps of the residual path analysis are tedious, and after the research conducted by related scholars, the method of implementing the throughput analysis in SPSS 25.0 software (International Business Machines Corporation, Norman, Chicago, IL, USA) is proposed [49,50], and the formula for calculating the residual path coefficient is shown as follows [50]:…”