Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle.

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

Prediction of dry matter intake and gross feed efficiency using milk production and live weight in first-parity Holstein cows.

Direct measurement of dry matter intake (DMI) presents a major challenge in estimating gross feed efficiency (GFE) in dairy cattle. This challenge can, however, be resolved through the prediction of DMI and GFE from easy-to-measure traits such as milk production (i.e. milk yield, energy-corrected milk (ECM), butterfat, protein, lactose) and live weight (LW). The main objective of this study was, therefore, to investigate the feasibility of predicting dry matter intake and gross feed efficiency for first-parity Holstein cows using milk production traits and LW. Data comprised of 30 daily measurements of DMI and milk production traits, and 25 daily LW records of a group of 100 first-parity Holstein cows, fed a total mixed ration. Gross feed efficiency was calculated as kg ECM divided by kg DMI. The initial step was to estimate correlations of milk production traits and LW with DMI and GFE, to identify the best potential predictors of DMI and GFE. Subsequently, a forward stepwise regression analysis was used to develop models to predict DMI and GFE from LW and milk production traits, followed by within-herd validations. Means for DMI, butterfat yield (BFY) and LW were 21.91 ± 2.77 kg/day, 0.95 ± 0.14 kg/day and 572 ± 15.58 kg/day, respectively. Mean GFE was 1.32 ± 0.22. Dry matter intake had positive correlations with milk yield (MY) (r = 0.32, p < 0.001) and LW (r = 0.76, p < 0.0001) and an antagonistic association with butterfat percent (BFP) (r = - 0.55, p < 0.001). On the other hand, GFE was positively associated with MY (r = 0.36, p < 0.001), BFP (r = 0.53, p < 0.001) and BFY (r = 0.83, p < 0.0001), and negatively correlated with LW (r = - 0.23, p > 0.05). Dry matter intake was predicted reliably by a model comprising of only LW and MY (R2 = 0.79; root mean squared error (RMSE) = 1.05 kg/day). A model that included BFY, MY and LW had the highest ability to predict GFE (R2 = 0.98; RMSE = 0.05). Live weight and BFY were the main predictor traits for DMI and GFE, respectively. The best models for predicting DMI and GFE were as follows: DMI (kg/day) = - 54.21 - 0.192 × MY (kg/day) + 0.146 × LW (kg/day) and GFE (kg/day) = 4.120 + 0.024 × MY (kg/day) + 1.000 × BFY (kg/day) - 0.008 × LW (kg/day). Thus, daily DMI (kg/day) and GFE can be reliably predicted from LW and milk production traits using these developed models in first-parity Holstein cows. This presents a big promise to generate large quantities of data of individual cow DMI and GFE, which can be used to implement genetic improvement of feed efficiency.

Genetic diversity and relationships among three Southern African Nguni cattle populations.

The Nguni cattle breed has distinct populations that are adapted to the different ecological zones of Southern Africa. This study was carried out to assess genetic diversity and establish the relationships among South African (SA), Mozambican (Landim), and Swazi Nguni cattle populations, using 25 microsatellite markers. Genotypic data were generated from deoxyribonucleic acid (DNA) samples of 90 unrelated individuals of the three cattle populations, collected from government conservations and stud herds. DNA profiles of five local beef breeds were used as the reference populations. Most of the 25 microsatellite markers were highly polymorphic across the studied populations, with an overall polymorphic information content (PIC) mean of 0.676. Genetic diversity within populations was high with expected heterozygosity varying from 0.705 ± 0.024 (Landim) to 0.748 ± 0.021 (SA Nguni) and mean number of alleles being highest in the SA Nguni (7.52 ± 0.42). Average observed heterozygosity (0.597 ± 0.046) compared to the expected heterozygosity (0.719 ± 0.022) was lowest for the Swazi Nguni, which also had a high number of Hardy-Weinberg Equilibrium (HWE) deviated loci (13), confirming the relatively high level of inbreeding (0.158 ± 0.058) in that population. Analysis of molecular variance revealed only 9.61% of the total variation between the populations and 90.39% within populations. A short genetic distance (0.299) was observed between Landim and Swazi Nguni, with the SA Nguni (> 0.500) being the most genetically distant population. The distant relationship between SA Nguni and the other two Nguni cattle populations was further confirmed by a principal coordinates analysis. The three Nguni populations clustered independently from each other, despite some evidence of admixture. Therefore, it can be concluded that SA Nguni, Landim, and Swazi Nguni populations in Southern Africa exhibit high levels of genetic diversity and are genetically distant; with the two latter populations being less genetically apart. These results present useful information for the development of strategies for regional management of animal genetic resources, through conservation and sustainable utilisation.