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This study investigates the effect of non-genetic factors on the birth weight of Kalahari Red goats, a critical economic parameter in livestock production. Analysing data from 1902 goat kids born between 2008 and 2017 in different regions of South Africa, including the Northern (Gauteng, Mpumalanga, Northwest, and Limpopo), Southern (Eastern Cape and the eastern part of Western Cape), and Eastern (KwaZulu-Natal and the eastern part of Eastern Cape), the research employs a least-squares analysis of variance (ANOVA) using the General Linear Model (GLM) procedure. The results highlight the significance of various factors in determining birth weight. Season of birth, sire age, doe age, sex of the kid, breeder, year of birth, and birth type emerge as influential sources of variation (p < 0.05). Notably, region and kidding interval show no significant effect on birth weight (p > 0.05). Male kids generally have a higher average birth weight compared to females. Single births result in higher weights than multiple births (twins, triplets, and quadruplets). The study underscores the importance of considering these factors in genetic evaluation models. It emphasises their relevance in enhancing the understanding of prenatal growth and postnatal development in Kalahari Red goats within the context of livestock production. [ABSTRACT FROM AUTHOR]

Well-defined breeding objectives form the basis of sound genetic improvement programmes. Breeding objectives for Holstein cattle in South Africa were developed in the current study. Economic values were calculated for those economically relevant traits that had adequate bio-economic data, namely milk volume, fat yield, protein yield, liveweight, longevity, calving interval and somatic cell score (SCS). A bio-economic herd model for pasture-based and concentrate-fed systems in South Africa was used to calculate economic values by determining changes in profit arising from an independent unit increase in each trait. Alternative payment systems were used from four major milk buyers in South Africa. Relative economic values, standardized to the value of protein yield, were used to compare the relative importance of traits. Protein yield and longevity consistently had positive economic values and the converse was true for liveweight and calving interval. Economic value for volume was positive or negative, depending on whether the payment system rewarded or ignored volume. Sensitivity analysis showed that economic values were reasonably robust against fluctuations in the cost of feed and price of beef; with the exception of fat yield, whose value became negative when feed price exceeded ZAR 3.50. Generally, protein yield was the most important trait, although volume, longevity and SCS were more important in some situations. Calving interval was the least important trait, its value ranging from 4% to 22% of protein yield, although the model may have underestimated its value. Further work should focus on facilitating the wide adoption of these breeding objectives by industry. [ABSTRACT FROM AUTHOR]

Economic values of milk volume (VOL), fat yield (FYLD), protein yield (PYLD), live weight (LWT), longevity (LON), calving interval (CIV) and somatic cell score (SCS) were derived for Holstein and Jersey cattle, based on milk payment systems of four major milk buyers in South Africa. The economic value of somatic cell score was calculated for only two of the payment systems. A bio-economic model was used to calculate economic values by determining changes in profit arising from an independent unit increase in each trait. Economic values for VOL, FYLD and PYLD varied substantially among the payment systems; particularly PYLD which ranged from ZAR 7.62/kg to ZAR 21.88/kg. Payment systems that do not pay for milk volume resulted in a negative economic value (-ZAR 0.49/l) for VOL. Live weight and CIV had constant economic values across payment systems (-ZAR 6.62/kg and -ZAR 5.75/day for Holstein and - ZAR 7.49/kg and -ZAR 4.19/day for Jersey, respectively, for LWT and CIV). Economic value of LON varied slightly with payment system (ZAR 1.09/day to ZAR 1.23/day in the Jersey and ZAR 3.59/day to ZAR 3.68/day in the Holstein). The economic value of SCS differed substantially between the two payment systems and was higher in the Holstein (-ZAR 949.26/score and -ZAR 1795.57/score) than in the Jersey (-ZAR 433.87/score and -ZAR 912.90/score). Relative emphasis of traits in the breeding objectives for South African dairy cattle should take due cognisance of the diversity in milk payment systems. [ABSTRACT FROM AUTHOR]

Female fertility is increasingly gaining importance in national dairy cattle breeding objectives worldwide. In South Africa, there is no routine prediction of breeding values for reproductive performance in dairy cattle and selection is mainly focused on production traits. The objective of this study was to estimate genetic parameters among female fertility traits (age at first calving and calving interval) and first, second and third lactation production traits in South African Holstein cattle to determine the effect that selection on production per se may have on female fertility. Performance records on 40 437 South African Holstein cows in 766 herds were used. (Co)variance estimates were obtained by multitrait analysis, using the REML procedure. Heritability estimates were moderate for age at first calving (0.24 ± 0.02) and low for calving interval (0.03 ± 0.01). Genetic correlations between age at first calving and yield traits were low to moderately negative, ranging from -0.17 ± 0.07 with second lactation butterfat percentage to -0.50 ± 0.05 with first lactation butterfat yield. Calving interval had moderate to highly positive genetic correlations with yield traits, ranging from 0.37 ± 0.10 with second lactation milk yield to 0.69 ± 0.06 with first lactation milk yield. Correlations between female fertility and butterfat and protein percentages across all lactations, were close to zero. The observed antagonistic relationship between calving interval and production traits highlights the need to include calving interval in breeding objectives for South African Holstein cattle. [ABSTRACT FROM AUTHOR]

Selection accuracy for resistance to mastitis may be increased by combining somatic cell score (SCS) and udder type into an udder health index, using genetic parameter estimates among them. A multi-trait animal model was used to estimate genetic parameters among lactation average SCS and udder type traits in South African Holstein cattle, through REML procedures. Data comprised records on 22 999 Holstein cows in 722 herds, collected through the National Milk Recording Scheme from 1996 to 2002. Average SCS in the first three lactations (SCS1, SCS2, SCS3) were considered as different traits and the udder type traits were fore udder attachment (FUA), rear udder height (RUH), udder cleft (UC), udder depth (UD), fore teat length (FTL) and fore teat placement (FTP). Heritability estimates for SCS were 0.19 ± 0.02, 0.17 ± 0.02 and 0.19 ± 0.02, respectively for SCS1, SCS2 and SCS3. Udder type traits had heritability estimates ranging from 0.13 ± 0.01 for UC to 0.34 ± 0.01 for FTL. The genetic correlations between lactation SCS ranged from 0.82 ± 0.04 to 0.99 ± 0.03 for correlations of SCS3 with SCS1 and SCS2, respectively. Genetic correlations between SCS and udder type traits were in the range -0.01 ± 0.07 between FUA and SCS3 to -0.38 ± 0.04 between UD and SCS1 and SCS2. Slow genetic progress is expected when selection is applied independently on SCS and udder type traits, due to the generally low heritability estimates. Low, shallow udders with narrowly placed teats are associated with low SCS in the South African Holstein population. [ABSTRACT FROM AUTHOR]

This study assessed the feasibility of across-country genetic evaluation of dairy cattle in sub-Saharan Africa where data on livestock production are scarce. Genetic parameters were estimated for the 305-day milk yield in the first lactation and across five lactations, for age at first calving and for interval between first and second calving. Estimated breeding values of individual animals for these traits were calculated. There were records from 2 333, 25 208, and 5 929 Holstein cows in Kenya, South Africa, and Zimbabwe, and 898 and 65134 Jersey cows from Kenya and South Africa. Genetic gain from sire selection within and across countries. was predicted Genetic links between countries were determined from sires with daughters that had records in two or more countries, and from common ancestral sires across seven generations on both the maternal and paternal sides of the pedigree. Each country was treated as a trait in the across-country evaluation. The results showed that genetic variance and heritability were not always estimable within country, but were significantly different from zero in the across-country evaluation. In all three countries, there was greater genetic gain in all traits from an across-country genetic evaluation owing to greater accuracy of selection compared with within country. Kenya stood to benefit most from an across-country evaluation, followed by Zimbabwe, then South Africa. An across-country breeding programme using joint genetic evaluation would be feasible, provided that there were genetic links across countries, and would provide a platform for accelerated genetic progress through selection and germplasm exchange between sub-Saharan African countries. [ABSTRACT FROM AUTHOR]

The current study investigated the effects of sex and stocking density and their interaction on growth performance and carcass characteristics of broiler chickens in a semi-arid sub-tropical environment. A total of 1008 day-old Cobb Avian48 chicks, namely 462 males and 546 females, were reared at final stocking densities of 30, 35, and 40 kg bodyweight per square metre (BW/m2) corresponding to 44, 51 and 59, and 52, 61 and 69 chicks per pen for males and females, respectively, during a 42-day production period. The experiment was a 2 × 3 factorial completely randomized design, with each sex-stocking density combination being replicated three times. After the initial weighing, the birds were weighed individually [grams (g)] each week until the 42nd day. At day 42, four birds from each pen were randomly sampled and slaughtered, and carcass characteristics were measured after 48 hours, and expressed as percentages of bodyweight. Growth performance and carcass characteristic parameters were subjected to analysis of variance using the general linear model procedures of Minitab statistical software version 17. Treatment means were compared using Tukey's test at (α = 0.05). Males gained more weight and were significantly heavier at slaughter age (2649 ± 43.1 g) than females (2270 ± 43.1 g). There was a progressive reduction in feed intake with increasing stocking density, but neither sex nor stocking density influenced feed conversion ratio and mortality rate. Sex significantly affected dressing percentage and carcass parts percentages, namely breast, neck, shank, heart and abdominal fat and thigh, liver and gizzard. On the other hand, stocking density significantly influenced dressing percentage and carcass parts percentages such as breast, thigh, drumstick, neck, shank, liver and gizzard. There was a significant sex x stocking density interaction effect on percentages of thigh and liver. It is therefore suggested that for efficient 42-day production cycles of broilers in the subtropics, Cobb Avian48 males reared at the stocking density of 40 kg BW/m2 could be considered the best option. [ABSTRACT FROM AUTHOR]

Longevity is a major component of the breeding objective for dairy cattle in many countries because of its high economic value. The trait has been recommended for inclusion in the breeding objective for dairy cattle in South Africa. Linear models, random regression (RR) models, threshold models (TMs) and proportional hazard models (PH) have been used to evaluate longevity. This paper discusses these methodologies and their advantages and disadvantages. Heritability estimates obtained from these models are also reviewed. Linear methodologies can model binary and actual longevity, while RR and TM methodologies model binary survival. PH procedures model the hazard function of a cow at time t derived from survival from first calving to culling, death or censoring. It is difficult to compare methodologies for sire evaluation and ranking across countries because of the variation in the definition of longevity and the choice of model. Sire estimated breeding values (EBVs) are derived differently for the models. Sire EBVs from PH models are expressed as deviations of the culling risk from the mean of the base sires, expected percentage of daughters still alive after a given number of lactations, expected length of productive life in absolute terms or as standard deviation units. In linear, TM and RR modelling, sire EBVs for longevity have been expressed as deviations of survival from the mean estimated with Best Linear Unbiased Prediction (BLUP). Appropriate models should thus be developed to evaluate functional longevity for possible inclusion in the overall breeding objective for South African dairy cattle. [ABSTRACT FROM AUTHOR]

Milkability is an important functional trait, which is directly related to milking costs and udder health. There are no milkability traits incorporated in the South African dairy cattle breeding objectives and genetic parameter estimates for these traits are not available in this population. The main objective of the study was, therefore, to estimate the genetic parameters for milkability traits and its correlation with somatic cell scores in South African Holstein cattle. Data consisted of production and milkability records of 2719 Holstein cows, from ten herds, collected from 2016 to 2018. Genetic parameters were estimated by a multi-trait animal model using the restricted maximum likelihood (REML) procedure. Means for milking time (MT), average milk flow (AMF), maximum milk flow (MMF), and somatic cell score (SCS) were 5.20 min, 1.91 kg/min, 2.99 kg/min, and 2.06, respectively. The heritability estimates were low to moderate from 0.19 ± 0.07, 0.24 ± 0.06, 0.36 ± 0.11, and 0.41 ± 0.12, respectively, for SCS, AMF, MT, and MMF. The genetic correlations were significant (P < 0.05) among the three milkability traits ranged from - 0.31 ± 0.05 between AMF and MT to 0.85 ± 0.02 between AMF and MMF. Positive genetic correlations were observed between AMF and MMF, while the correlations for MT with the remaining milkability traits were negative. Genetic correlations of SCS with AMF, MMF, and MT were - 0.13 ± 0.04, 0.13 ± 0.04, and - 0.25 ± 0.12, respectively. The mean estimated breeding value (EBV) was estimated using cattle birth dates, and there was an increase in AMF of 0.0001 kg/min EBV per year on cattle born during the period 2002 to 2014. Maximum milk flow also showed an increasing genetic trend of 0.0003 kg/min per year over the same period. On the other hand, the genetic trend for MT was undesirable, as it increased by 0.0003 kg/min per year. The moderate to high heritability estimates for milkability traits showed that selection for improvement was possible in South African Holstein cattle. High genetic correlation between AMF and MMF implied that these two may be regarded as the same trait. Milking time can contribute towards improving the accuracy of estimating EBVs for SCS in a multi-trait analysis, and vice versa, due to the moderate correlation between the two traits. The marginal genetic trend in milkability traits may be an interrelated response to selection of other traits already under selection in the population such as SCS. Results of the current study provided a basis for including milkability traits of South African Holstein cattle in the breeding objectives.

Non-genetic factors influencing functional longevity and the heritability of the trait were estimated in South African Holsteins using a piecewise Weibull proportional hazards model. Data consisted of records of 161,222 of daughters of 2,051 sires calving between 1995 and 2013. The reference model included fixed time-independent age at first calving and time-dependent interactions involving lactation number, region, season and age of calving, within-herd class of milk production, fat and protein content, class of annual variation in herd size and the random herd-year effect. Random sire and maternal grandsire effects were added to the model to estimate genetic parameters. The within-lactation Weibull baseline hazards were assumed to change at 0, 270, 380 days and at drying date. Within-herd milk production class had the largest contribution to the relative risk of culling. Relative culling risk increased with lower protein and fat per cent production classes and late age at first calving. Cows in large shrinking herds also had high relative risk of culling. The estimate of the sire genetic variance was 0.0472 ± 0.0017 giving a theoretical heritability estimate of 0.11 in the complete absence of censoring. Genetic trends indicated an overall decrease in functional longevity of 0.014 standard deviation from 1995 to 2007. There are opportunities for including the trait in the breeding objective for South African Holstein cattle., (© 2017 Blackwell Verlag GmbH.)

A multi-trait animal model was used to estimate genetic parameters among lactation somatic cell score (SCS) and udder-type traits in South African Jersey cattle, through restricted maximum likelihood (REML) procedures. Data comprised records on 18 321 Jersey cows in 470 herds, collected through the National Milk Recording Scheme from 1996 to 2002. Average SCS in the first three lactations (SCS1, SCS2 and SCS3) were considered as different traits and the udder-type traits were fore udder attachment (FUA), rear udder height (RUH), rear udder width (RUW), udder cleft (UC), udder depth (UD), fore teat placement (FTP), rear teat placement (RTP) and fore teat length (FTL). Heritability estimates for the respective lactation SCS were 0.07 ± 0.01, 0.11 ± 0.01 and 0.11 ± 0.02. Udder-type traits had heritability estimates ranging from 0.14 ± 0.01 for UD to 0.30 ± 0.02 for FTL. Genetic correlations between SCS and udder-type traits ranged from -0.003 ± 0.07 between FUA and SCS3 to -0.50 ± 0.07 between UD and SCS3. Slow genetic progress is expected when selection is applied independently on SCS and udder-type traits, due to the generally low heritabilities. Tightly attached shallow udders with narrowly placed rear teats are associated with low SCS in the Jersey population.