ABSTRACT The body weight (BW) of an animal is a vital economic trait that might help in decision-making in the handling of animals. The objective of the present study was to develop equations for the prediction of BW in Pelibuey sheep using scrotal circumference (SC). The BW (23.40 ± 6.96 kg) and SC (20.25 ± 6.19 cm) have been recorded in 405 male Pelibuey at the Southeastern Center for Ovine Integration, Mexico. Linear, logarithmic, quadratic, exponential, cubic, and power regression models were used for data analysis. Pearson correlation (R), Coefficient of determination (R2), Adjusted coefficient of determination (Adj.R2) Root mean square error (RMSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to select the best model. Power regression model showed the highest R (0.93), R2 (0.86), Adj.R2 (0.86) and lowest RMSE (0.02), AIC (-989.44) and BIC (-981.44). The current study suggests that SC might be used as the only predictor for BW of growing Pelibuey sheep raised under tropical conditions.

RESUMO O peso corporal (PC) do animal é uma característica econômica importante, que pode auxiliar na tomada de decisões no manejo dos animais. O objetivo do presente estudo foi desenvolver equações para a predição do PC em ovinos Pelibuey por meio da circunferência escrotal (CE). O PC (23,40±6,96kg) e a CE (20,25±6,19cm) foram registrados em 405 ovinos machos da raça Pelibuey no Centro de Integração Ovina da Região Sudeste do México. Os modelos lineares, logarítmicos, quadráticos, exponenciais, cúbicos e de regressão de potência foram utilizados para a análise dos dados. A correlação de Pearson (R), o coeficiente de determinação (R2), o coeficiente de determinação ajustado (Adj.R2), o erro do quadrado médio (EQM), o critério de informação de Akaike (AIC) e o critério de informação bayesiano (BIC) foram usados para selecionar o melhor modelo. O modelo de regressão de potência apresentou maiores R (0,93), R2 (0,86), Adj.R2 (0,86) e menores EQM (0,02), AIC (-989,44) e BIC (-981,44). O estudo atual sugere que a CE pode ser usada como um único preditor para o PC de ovinos Pelibuey em crescimento criadas em condições tropicais.

In sub-Saharan Africa, goatfarming has shown to be a significant intervention in the fight against poverty. However, the productivity of goats is threatened by several challenges, such as limited forage availability, especially during dry seasons when the quantity and quality decline. The study aimed to gather smallholder farmers' knowledge on the identity and nutritional qualities of fodder trees browsed by goats in the study area. Fourteen smallholder goat farmers were interviewed using a semi-structured questionnaire. Botanical identification and nutritional analysis of mentioned browse plants were conducted at the Animal Production Laboratory, University of Limpopo, South Africa. Capparis tomentose, Euclea crispa and Cassine transvaalensis had higher (p<0.05) dry matter content. Ziziphus mucronata had higher (p<0.05) ash content. Maerua angolensis had higher (p<0.05) crude protein content, while Colophospermum mopane had a higher (p<0.05) energy content. Colophospermum mopane was ranked the most browsed plant (43%), whereas Ziziphus mucronata and Maerua angolensis were ranked the least browsed plants. Colophospermum mopane and Sclerocarya birrea were classified as bad sources of goat feed. Most of the identified feed materials had crude protein and energy levels higher than the recommended minimum required levels for the maintenance of essential functions of goats. Findings from this study indicate thatfarmers had some knowledge of the feed materials available for goat feeding, even though most farmers in the study area did not know how to determine the nutritional qualities of the available feed materials. The knowledge gathered from this study contributes to the body of literature on the use of indigenous feed resources to improve goat production, which has the potential to alleviate poverty and reduce unemployment in line with the National Development Plan 2030 of the South African government.

Principal component analysis (PCA) is a vital statistical technique for defining the morphological structure of livestock but has not been used in South African Kalahari Red goats. Thirteen morphometric traits and eleven body indices from two hundred and ninety-six (296) South African Kalahari Red goats (269 does and 27 bucks) aged 2-3 years were used to define morphological structure using PCA. The coefficient of determination (R²), root mean square error (RMSE), Akaike's information criterion (AIC), Mallows' Cp-statistic (Cp), and coefficient of variation (CV) were used to select the best fit model. Body weight was correlated with all morphometric traits in both sexes. The first two principal components explained 87.31% of the variation in measurements from male goats and 62.32% of the trait variation in the females. The inclusion of head length, body length, canon circumference, rump length, rump width, body condition score, wither height, and rump height increased the accuracy to 98% with smaller RMSE (2.42), AIC (55.35), Cp (10.00), and CV (3.98), and the use of PC1 and PC2 included 94% of the variation (RMSE, 3.62; AIC, 72.26; Cp, 3.00; CV, 5.94 in males). In females, the inclusion of all morphometric traits included 87% of the variation (RMSE, 2.93; AIC, 590.63; Cp, 13.00; CV 5.87). The use of PC1 and PC2 included 82% of the variation (RMSE, 3.41; AIC, 663.60; Cp, 3.00; CV, 6.84). PCA can therefore be used in breeding programs to define the morphological structure of South African Kalahari Red goats with a severe reduction in the number of morphometric traits to be recorded.

The study examined single nucleotide polymorphisms (SNPs) in the growth hormone gene (GH1) in Boer goat does and their relationship with body measurement traits, namely bodyweight, body length, heart girth, rump height, rump width, ear length, cannon circumference, and head width. Seventy-six Boer goat does between the ages of 2 and 4 years were used as experimental animals. Polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) and deoxyribonucleic acid (DNA) sequencing techniques were used to detect SNPs. Chi-square test was used to measure the genetic equilibrium and a general linear model was used for the marker-trait association analysis. The PCR-RFLP and DNA sequencing results discovered one SNP (G505C) in the exon 5 of the candidate gene with two genotypes observed (AA and AB). The association analysis indicated that bodyweight was associated with the genotypes (P <0.01), but not with any of the morphometric traits. A chi-square analysis indicated that the genotypic frequencies were in Hardy-Weinberg equilibrium. The polymorphism discovered in this study is a putative marker that might assist farmers in improving their does' bodyweight through marker-assisted selection.