Selection index for economically important traits in Boer crossbred goats using principal component analysis

cg.contactzeleke.t2007@gmail.comen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Livestock Research Institute - ILRIen_US
cg.contributor.centerAmhara Regional Agricultural Research Institute - ARARIen_US
cg.contributor.centerAmhara Regional Agricultural Research Institute, Debre Birhan Agricultural Research Center - ARARI-DBARCen_US
cg.contributor.centerAmhara Regional Agricultural Research Institute, Sirinka Agricultural Research Center - ARARI - SARCen_US
cg.contributor.centerAndasa Livestock Research Centeren_US
cg.contributor.funderAmhara Regional Agricultural Research Institute - ARARIen_US
cg.contributor.projectCODIS - Corporate-Communication and Documentation Information Servicesen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryETen_US
cg.coverage.regionEastern Africaen_US
cg.creator.idGetachew, Tesfaye: 0000-0002-0544-6314en_US
cg.identifier.doihttps://doi.org/10.1371/journal.pone.0310841en_US
cg.isijournalISI Journalen_US
cg.issn1932-6203en_US
cg.issue4en_US
cg.journalPLoS ONEen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.agrovocgenetic parametersen_US
cg.subject.agrovocgoatsen_US
cg.volume20en_US
dc.contributorDeribe, Belayen_US
dc.contributorTilahun, Mekonnenen_US
dc.contributorKefale, Alemuen_US
dc.contributorLakew, Mesfinen_US
dc.contributorGetachew, Tesfayeen_US
dc.contributorAlebachew, Getachewen_US
dc.contributorGizaw, Solomonen_US
dc.creatorTesema, Zelekeen_US
dc.date.accessioned2025-09-11T21:28:08Z
dc.date.available2025-09-11T21:28:08Z
dc.description.abstractThe optimal strategy for genetic selection is a selection index based on economic weight; however, in developing countries where economic weight estimation is not always evident and easy for breeders due to a lack of economic data. Thus, this study aimed to construct selection indices for crossbred goats, which could be used as an alternative to economic selection index and to explore the relationship among economically important traits. The data set contained records of birth weight (BW), weaning weight (WW), pre-weaning weight gain (ADG), pre-weaning Kleiber ratio (KR), pre-weaning relative growth rate (RGR), pre-weaning growth efficiency (GE), and pre-weaning survival (RR) of crossbred goats. Genetic parameter estimates were obtained using a single-trait animal model. General linear model, principal component analysis, and cluster procedures of SAS were also used for data analysis. Kid survival was negatively correlated with all investigated traits except BW. Traits such as KR, GE, RGR, WW, and ADG were highly and positively correlated. According to the Kaiser method, two principal components were selected from seven investigated traits. The first principal component (PC1) explained 57.71%, and the second principal component (PC2) explained 14.57% of the estimated breeding value variance, totaling 72.28% of the total genetic additive variance. PC1 explained most of the direct additive genetic variation and correlated with the estimated breeding value of WW, ADG, KR, GE, and RGR, whereas PC2 was correlated with the estimated breeding value of BW and RR. Besides, the cluster analysis categorized seven traits into two major groups. The first group includes BW and RR, whereas traits such as WW, ADG, KR, GE, and RGR were included in the second group. Therefore, two based selection indices, or principal component scores (PCS) were derived. Animals with higher PCS1 could be used to improve WW, ADG, KR, GE, and RGR, whereas animals with higher PCS2 scores could be used to improve BW and pre-weaning survival of crossbred kids. The selection of the most appropriate and specific selection index regarding the two groups of traits is determined by the breeding objectives defined for specific genetic improvement program. These selection indices could be used as an alternative approach when economic weights for traits of interests are not available to construct the economic selection index. However, further works should be done on refining the selection indices and validating them in independent datasets.en_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/f7df1a7cc2a0eb32cf5df4b33a1d15b9en_US
dc.identifier.citationZeleke Tesema, Belay Deribe, Mekonnen Tilahun, Alemu Kefale, Mesfin Lakew, Tesfaye Getachew, Getachew Alebachew, Solomon Gizaw. (1/4/2025). Selection index for economically important traits in Boer crossbred goats using principal component analysis. PLoS ONE, 20 (4).en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/70105
dc.languageenen_US
dc.publisherPublic Library of Scienceen_US
dc.rightsCC-BY-4.0en_US
dc.sourcePLoS ONE;20,(2025)en_US
dc.subjectcluster analysisen_US
dc.subjecteconomic weightsen_US
dc.subjectcrossbred goatsen_US
dc.subjectbirth weight (bw)en_US
dc.subjectprincipal component analysis (pca)en_US
dc.titleSelection index for economically important traits in Boer crossbred goats using principal component analysisen_US
dc.typeJournal Articleen_US
dcterms.available2025-04-01en_US
dcterms.hasVersionV3 - 2025-09-11en_US
mel.impact-factor2.6en_US

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