West African Dwarf goat populations of tropical rainforest zone: application of multivariate analysis tools on their characterization using morpho-biometric traits

Abstract

This research was carried out to characterize the West African Dwarf (WAD) goats using multivariate approach based on their morpho-biometric traits in the Tropical Rainforest Zone of Nigeria. Data on four physical qualitative traits, six morphology indicators and nine morphological characters were generated from 279 goats. Descriptive statistics, non-parametric analysis and one-way approach of ANOVA with post hoc tests, Discriminant Analysis (Canonical), Principal Component Analysis (Categorical) and Regression Tree analysis were employed to discern the effects of location and sex on the parameters, as well as characterize the goats. The frequencies of the qualitative traits show black coat colour predominated (60.2%) over other coat colours, plain colour predominated (75.3%) over other colour patterns, straight horns (38.1%) predominates over other horn shape and beards presence (66.7%) predominated over non-beard presence amongst the goats in terms of locations and sexes.Location and age were signi cantly affected on the biometric characters (P < 0.05 and P < 0.001) with goats from Enugu having higher values than other states, while only HL was affected signi cantly by sex (P < 0.05). The morphological indicators were not signi cant affected by location and sex (P > 0.05 and P > 0.001), while age was signi cant. The discriminant analysis revealed a sparse, non-intermingling populations for the physical traits, biometric characters and body indices implying they are different distinct populations from each other. Generally, the goat populations could be characterized using HG, RH, and BW due to the Principal components, while the CHAID and Exhaustive CHAID algorithms analysis revealed BW and HL as the genetic classi ers of the WAD goats, both in terms of locations. Basically, the goats from the 3 locations appeared to be more homogeneous in nature, implying that a deployment of speci c complimentary genomics work targeted at future selection and breeding programs to improve their productivity in the Tropical rain forest of Nigeria is necessary.