The dairy industry is characterized by a dual production system, comprising of a high input commercial production system and low input smallholder and emerging systems. Performance data from both systems are included in the official national genetic evaluation database, with models which assume homogeneous variances. If variances are heterogeneous, above average animals in more variable herds will be favoured over high performing animals in the less variable herds. This may result in biased selection and inaccurate estimation of breeding values. With intensified selection, genetically inferior animals are chosen, thereby decreasing the realised genetic gain. Therefore, there is a need to investigate the extent of variance between the two dairy production systems in South Africa, which was the purpose of the study by the authors cited below.
Milk Production data was obtained from the INTERGIS. The high input production system data set consisted of 68 000 performance records from 741 herds recorded between 2006 and 2018. The pedigree file comprised of 38 126 daughters of 2 472 sires and 4 305 dams. The data set for the low input production system comprised of 32 388 records from 3 325 daughters of 134 sires and 253 dams from 59 herds recorded from 2006 to 2018. The initial statistical analysis included mean milk, fat and protein analyses and their least square errors, and ascertained significant non-genetic factors affecting milk, fat and protein yields. A further statistical programme was then used to test for heterogeneous variances.
The mean milk, fat and protein yields were respectively 8 123 ± 1 270kg, 310.6 ± 43.78kg and 262.7 ± 24.53kg for the high input production system and 4 127 ± 833.9kg, 167.3 ± 28.88kg and 136.4 ± 24.53kg for the low input production system. The average mean, standard deviation and coefficient of variation increased with production level, which could be attributed to general management and genetic superiority of animals. A significant (P>0.0001) heterogeneity of variance of milk, fat and protein existed between the two production systems. Heard-year-season, parity, age at calving affected milk production traits and contributed significantly to heterogeneity of variance (P>0.05).
Conclusions: Heterogeneity of variance does exist between the low and high input dairy production systems, which should be taken into consideration during cow and sire genetic evaluations. The obtained results may optimise genetic evaluation models that may be useful in estimating more accurate ranking of sires, which subsequently may lead to improved genetic gain within the Holstein dairy cattle population.
Reference:
M.N. Tlabela, O. Tada, B. Dube & C.B. Banga, 2019. Heterogeneity of variance for milk production traits between low and high input production systems of South African Holstein cattle. In: Proc. of the 51st Annual SASAS Congr., Bloemfontein, 10-12 June 2019, Abstr. 196.