Genetic morphometry in Nigerian and South African Kalahari Red goat breeds

Abstract

Genetic improvement of goat breeds in growth and other traits (e.g. milk production) is limited by the demographics of the goat herds, extensive production system and the seemingly long-term nature of improvement through traditional genetics and breeding methods. We studied the genetic morphometry in Nigerian goats and South African Kalahari Red goat breeds. A total of 192 goats belonging to three Nigerian breeds (Red Sokoto (RS), Sahel (SH) and West African Dwarf (WAD)) and one South African Kalahari Red (KR) goat breed were analysed. Animals were classified into four age groups: A group – less than 1 year, B group – between 1 and 2 years, C group – between 2 and 3 years and C group – older than 3 years based on dentition. Analysis of variance, correlation matrix, regression and discriminant analyses were used to evaluate morphological variability. Results revealed that the effect of breed on the measured morphometric traits was significant (P < 0.05). The best prediction equation for body weight (BW) with R2 = 0.84 was obtained when body length (BL), withers height (WH) and chest depth (CD) were included in the model for KR goat. Growth traits were positively correlated with each other with the highest correlation coefficients found between BL and BW (r = 0.877, P < 0.01), WH and BW (r = 0.541, P < 0.01), WH and BW (0.661, P < 0.01) and CD and BW (0.738, P < 0.01) in KR, RS, SH and WAD goats, respectively, which are important for a conscious selection and breeding programme for desired traits. Stepwise discriminant procedure showed that WH, CD and BL were the most discriminating variables to separate KR, RS, SH and WAD goats. In accessing morphological diversity, efforts should be made to include phenotypic variables of at least ≥ 3 in order to minimize ambiguity in classification. Based on the pair-wise distances from the Discriminant function, the study provided informed decision, reference information on goat breeding and conservation strategy.

Morphometrics Characterization of Thin-Tail Sheep in Lowland and Highland Areas

“…Morphometric data are needed for livestock identification, prediction of production potential, livestock productivity (Hilmawan et al, 2019;Mahmudi et al, 2019), continuity of breeding and livestock breeding (Saputra et al, 2019;Markovic et al, 2019). Several morphometric studies have been carried out on sheep to improve genetic quality based on morphometric data (Vazic et al, 2017;Salvagno & Albarella, 2017;Sanni et al, 2018;Markovic et al, 2019). Linear Body Parameters and Craniometric Analysis in Etawah-Grade goats were used to predict prolificacy (Mulyono et al, 2018).…”