"11682","9","archive","3170",,,"disk0/00/01/16/82","2020-12-29 14:15:09","2020-12-29 14:15:09","2020-12-29 14:15:09","article",,,"show",,,,"","","","","","","","","","",,,,"Mubai","N","","","","","",,"Okori","P","","","","",,,,,"","",,,,,"","","School of Agricultural Sciences, Save University, Mozambique","Mozambique","Phenotypic correlation, path coefficient and multivariate analysis for yield and yield-associated traits in groundnut accessions","pub","cr1","CRPS5","","public",,,"Groundnut, Correlation, Path analysis, Diversity, Cluster, Principal component, Analysis",,"The technical support in execution of field experiments by
field technicians at the International Crops Research
Institute for the Semi-Arid Tropics is highly appreciated.
The logistical support by the administrative country office
contributed immensely to the success of the research","Yield is a complex quantitative trait largely influenced by the environment.
Direct selection for grain yield is less efficient in improving groundnut productivity.
The selection efficiency can be enhanced by exploiting the relationship
between yield and its related traits. Moreover, the use of genetically diverse parents
is essential to generate genetic variation for successful selection of genotypes in
a breeding program. Therefore, the study aimed at analysing the relationship
between grain yield and its related traits and determining the morphological
diversity among selected groundnut genotypes under natural rosette disease (GRD)
infestation. The genotypes were evaluated in a 7 × 4 alpha lattice design with three
replications. Data were collected on yield and yield-related traits. Correlation, path
coefficient and multivariate analyses were done. The results revealed that yield was
directly associated with plant height, number of pods per plant, hundred seed
weight, GRD incidence and number of secondary branches. Therefore, these traits
should be considered in selection when improving groundnut for yield. Cluster
analysis revealed existence of diversity among the evaluated groundnut genotypes with no influence of geographical origin to the clustering pattern. The Principal
Components Analysis (PCA) biplot was effective in showing the genetic distance
among the genotypes and the results were comparable with those of the cluster
analysis. Moreover, Shannon-Weaver diversity indices revealed existence of high
diversity among the genotypes, an implication that groundnut improvement for
yield is possible through selection in breeding.","2020-10","published",,"Cogent Food & Agriculture","6","1","Cogent OA",,"1-22",,,,,,"doi:10.1080/23311932.2020.1823591",,,,,"TRUE",,"2331-1932",,,,,,"","https://doi.org/10.1080/23311932.2020.1823591","https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=10.1080%2F23311932.2020.1823591&btnG=","pub",,"Bill and Melinda Gates Foundation","",,,,,,"",,,,,,,"",,,,,"",,,,,"","",,,,,"","",,,,,
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