Concentrate supplementations of grazing pregnant Kalahari Red goats: Effects on pregnancy variables, reproductive performance, birth types and weight of kids.

A study was conducted for 22 weeks to determine the effects of concentrate supplementations at three crude protein (CP) levels, i.e. low protein diet-LPD 12.42% CP (124.93 g day-1); medium protein diet-MPD 14.18% CP (145.87 g day-1) and high protein diet-HPD 16.35% CP (168.19 g day-1) on some pregnancy variables, reproductive performance, birth types and weight of kids kidded by pregnant Kalahari Red goats grazed on Chloris gayana. Thirty-three matured Kalahari Red goats of first parity within age range of 2 to 21/2 years with an average body weight of 38.10 ± 1.13 kg were randomly allotted to the diets with 11 goats per treatment. Data obtained were subjected to analysis of variance in a completely randomised design. It was observed that goats fed HPD had the highest (p < 0.05) values for products of pregnancy (10.35 kg) taken within 24hour before kidding and foetal growth rate (88.37 g day-1) during pregnancy. Goats fed MPD had the lowest values (p < 0.05) of 9.28 kg and 80.07 g day-1 for each of the respective parameters. Afterbirth weight was also the highest and lowest (p < 0.05) for goats supplemented with HPD (3.38 kg) and MPD (3.04 kg), respectively. On the other hand, MPD-supplemented goats had the highest values (p < 0.05) for litter size (2.14) and litter weight (6.80 kg) at birth, the value which was the least for HPD supplementation. From the results obtained from this study, it could be concluded that concentrate diet supplementation with 14.18% CP improved litter size and weight at birth with resultant reduction in weights of pregnancy variables of pregnant Kalahari Red goats grazed on Rhodes grass.

Age- and sex-dependent regression models for predicting the live weight of West African Dwarf goat from body measurements.

The relationships between live weight and eight body measurements of West African Dwarf (WAD) goats were studied using 211 animals under farm condition. The animals were categorized based on age and sex. Data obtained on height at withers (HW), heart girth (HG), body length (BL), head length (HL), and length of hindquarter (LHQ) were fitted into simple linear, allometric, and multiple-regression models to predict live weight from the body measurements according to age group and sex. Results showed that live weight, HG, BL, LHQ, HL, and HW increased with the age of the animals. In multiple-regression model, HG and HL best fit the model for goat kids; HG, HW, and HL for goat aged 13-24 months; while HG, LHQ, HW, and HL best fit the model for goats aged 25-36 months. Coefficients of determination (R(2)) values for linear and allometric models for predicting the live weight of WAD goat increased with age in all the body measurements, with HG being the most satisfactory single measurement in predicting the live weight of WAD goat. Sex had significant influence on the model with R(2) values consistently higher in females except the models for LHQ and HW.

Body measurements of west African dwarf sheep as parameters for estimation of live weight.

The relationships between live weight and eight body measurements of West African Dwarf (WAD) sheep were studied using 210 animals under on farm condition. Data obtained on height at withers (HW), heart girth (HG), body length (BL), head length (HL), head width (HDW), loin girth (LG), length of hindquarter (LHQ) and width of hindquarter (WHQ) were fitted into linear, allometric and multiple regression models to predict live weight from the body measurements. Results revealed that body measurements of WAD sheep were generally higher in the rams than in the ewes. Coefficient of determination (R(2)) values computed for the body measurements were generally higher (0.87-0.99) using allometric regression model than linear regression model (0.44-0.94). Heart girth (HG) and WHQ depicted the highest relationship to live weight in linear and allometric models compared to other body measurements. Based on stepwise elimination procedure, HG, HL and WHQ were better in predicting live weight in multiple linear regression models. The magnitude of correlation coefficient (r) indicate that WHQ shows the highest correlation with live weight (r = 0.96) compared to HG (r = 0.94).