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APPLICATION OF MULTIVARIATE ANALYSIS TO DIFFERENTIATE THE HARARGHE HIGHLAND GOAT POPULATIONS REARED IN WEST HARARGHE ZONE, ETHIOPIA: Takele et al. Multivariate analysis to differentiate the Hararghe highland goat populations

APPLICATION OF MULTIVARIATE ANALYSIS TO DIFFERENTIATE HARARGHE HIGHLAND GOAT POPULATIONS REARED IN THE WEST HARARGHE ZONE, ETHIOPIA: Takele et al. Multivariate analysis to differentiate the Hararghe highland goat populations

dc.creatorTakele, Alefe
dc.creatorMelesse, Aberra
dc.creatorTaye, Mestawet
dc.date2021-12-21
dc.date.accessioned2022-11-21T13:44:30Z
dc.date.available2022-11-21T13:44:30Z
dc.identifierhttps://revistas.udec.cl/index.php/chjaas/article/view/4530
dc.identifier10.29393/CHJAAS37-23AMAM30023
dc.identifier.urihttps://revistaschilenas.uchile.cl/handle/2250/215813
dc.descriptionMultivariate analysis of morphological variables has been successfully used to estimate the genetic variation within and between local breeds. The objective of the study was to differentiate the Hararghe highland goat populations based on their morphometric traits by applying multivariate analysis. Sixteen morphometric traits were collected from 450 goats reared in three agro-ecological zones of the West Hararghe zone. Multivariate canonical discriminant analysis in combination with cluster and discriminant analysis was applied to identify the combination of variables that differentiate the three agroecology goats. Results indicated that all the morphometric traits were significantly affected by age. The cluster analysis indicated that two main groups in which the midland agroecology goats were included in one group while group two included the highland and lowland agroecology goats under one sub-cluster. The canonical discriminant analysis identified two canonical variables (CAN) of which CAN1 and CAN2 accounted for 68.2 and 31.8% of the total variation, respectively. The quadratic discriminant analysis correctly assigned the respective 71.3, 77.3, and 81.3% of the lowland, midland, and highland agroecology goat populations into their source populations with an overall 76.7% of accuracy rate. The Mahalanobis distance verified that the lowland and highland agroecology goats are the closest while the midland and highland agroecology goats were the furthest. However, the canonical discriminant analysis indicated a visible overlapping between the three goat populations indicating the existence of homogeneity among them. In conclusion, multivariate analysis identified 11 morphometric traits as the most imperative traits to differentiate the Hararghe highland goat populations effectively.en-US
dc.descriptionMultivariate analysis of morphological variables has been successfully used to estimate geneticvariation within and between local breeds. The objective of this study was to differentiate Hararghehighland goat populations based on their morphometric traits by applying multivariate analysis.Sixteen morphometric traits were collected from 450 goats reared in the three agroecological zones(highland, midland and lowland) of West Hararghe. Multivariate canonical discriminant analysisin combination with cluster and discriminant analysis was applied to identify the combination ofvariables that differentiate goats of the three agroecological zones. The results indicated that allthe morphometric traits were significantly affected by age. The cluster analysis indicated that twomain groups of midland goats were included in one group, while group two included highland andlowland goats under one sub-cluster. The canonical discriminant analysis identified two canonicalvariables (CAN) of which CAN1 and CAN2 accounted for 68.2 and 31.8% of the total variation,respectively. The quadratic discriminant analysis correctly assigned the respective 71.3, 77.3, and81.3% of lowland, midland, and highland goat populations into their source populations, with anoverall accuracy rate of 76.7%. The Mahalanobis distance verified that lowland and highland goats arethe closest, while midland and highland goats were the furthest. However, the canonical discriminantanalysis indicated a visible overlapping between goat populations of the three agroecological zones,indicating the existence of homogeneity among them. In conclusion, multivariate analysis identified11 morphometric traits as the most imperative traits to differentiate Hararghe highland goatpopulations effectively. Genetic potentials of Hararghe highland goat populations can be improvedthrough community-based breeding programs for their sustainable utilization and conservation.es-ES
dc.formatapplication/pdf
dc.languageeng
dc.publisherFacultad de Agronomía, Facultad de Ingeniería Agrícola y Facultad de Ciencias Veterinarias - Universidad de Concepciónes-ES
dc.relationhttps://revistas.udec.cl/index.php/chjaas/article/view/4530/6321
dc.rightsDerechos de autor 2021 Universidad de Concepciónes-ES
dc.rightshttps://creativecommons.org/licenses/by/4.0es-ES
dc.sourceChilean Journal of Agricultural & Animal Sciences (ex Agro-Ciencia); Vol. 37 No. 3 (2021); 209-220en-US
dc.sourceChilean Journal of Agricultural & Animal Sciences; Vol. 37 Núm. 3 (2021); 209-220es-ES
dc.source0719-3890
dc.subjectAgroecology, discriminant analysis, cluster analysis, morphometric traitsen-US
dc.subjectAgroecología, análisis discriminante, análisis de conglomerados, rasgos morfométricoses-ES
dc.titleAPPLICATION OF MULTIVARIATE ANALYSIS TO DIFFERENTIATE THE HARARGHE HIGHLAND GOAT POPULATIONS REARED IN WEST HARARGHE ZONE, ETHIOPIA: Takele et al. Multivariate analysis to differentiate the Hararghe highland goat populationsen-US
dc.titleAPPLICATION OF MULTIVARIATE ANALYSIS TO DIFFERENTIATE HARARGHE HIGHLAND GOAT POPULATIONS REARED IN THE WEST HARARGHE ZONE, ETHIOPIA: Takele et al. Multivariate analysis to differentiate the Hararghe highland goat populationses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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