Selection for Profit in Cattle: I. Economic Weights for Purebred Dairy Cattle in the Czech Republic

Abstract

A bioeconomic model for dairy cattle production was used to estimate economic values of 18 traits for dairy sires in purebred Holstein and Czech Fleckvieh populations. Economic values were defined as partial derivatives of the profit function with respect to each trait in a closed production system with dairy cow herds and integrated fattening of bulls. All revenues and costs associated with cows calving in the herds within one year and with their progeny were discounted at 5% per annum back to the date of calving. Calculations were carried out for the situation in the Czech Republic in 2005 (scenario 1: market quotas for milk yield and fat percentage) and for the expected situation in 2015 (scenario 2: free market). The relative economic importance of each trait was expressed as a ratio of the standardized economic value of that trait (its marginal economic value multiplied by its genetic standard deviation) to the standardized economic value of 305-d milk yield, with average fat and protein percentages. In addition to milk yield, somatic cell score was the second most important trait, achieving 32% to 43% of the value for milk yield in both scenarios. The relative importance of milk components differed notably between scenarios. The relative importance was approximately zero for protein and from -14 to -23% for fat percentage in scenario 1, but changed to 38% for protein and 27 to 31% for fat percentage in scenario 2. In both scenarios and for both breeds, the relative economic values for somatic cell score and length of productive life of cows were similar to those for fat and protein percentages in scenario 2. The smallest relative economic values (less than 4% of the relative importance of milk yield) were for birth weight, conception rate of heifers, and carcass traits. In conclusion, relative emphasis among traits in the breeding objective for Czech dairy cattle should be reassessed according to the expected situation after shifting to a free market economy in 2015.

Strategies for defining traits when calculating economic values for livestock breeding: a review

“…The economic impact of the change in age at first mating (and therefore also in the age at first parturition) is then included in the EV of growth rate (Wolfová et al, 2007 and2009).…”

“…This approach allows taking into account different management and feeding strategies in different life periods of animals intended for selling, breeding or fattening. Wolfová et al (2005Wolfová et al ( , 2007Wolfová et al ( and 2009) divided the growth period of young animals of both sexes in cattle and sheep into segments, which were consistent with management calendar and feeding practices, and then used the population means for weights at the start and end of each segment to calculate the average growth rate for that segment (e.g. growth rate till weaning, post-weaning growth rate for animals fattened or reared as replacements).…”

“…These EVs may be strongly influenced by the definition of the traits, by the whole complex of traits considered for selection purposes and by assumptions made on inter-relationships among traits in the algorithm for the calculation of EVs (Wolfová et al, 2007).…”

“…Similarly, Dekkers (1991) and Veerkamp et al (2002) increased the involuntary culling rate and conception rate of cows in each lactation and the lactation month proportionally by the same relative factor, when calculating the EVs of those traits. Wolfová et al (2007 and2009) changed the daily milk production of dairy cows and ewes during the entire milking period in all lactations proportionally by 0.5% and expressed the resulting change in profit per kg change in the average standardised milk production per 305 days in cows and per 150 days in sheep.In our opinion, proportional changes of all repeated trait expressions (e.g. among milk production or litter size in different parities) when calculating EV seem to be more appropriate and more close to the biological reality than changes by the same absolute value.…”

“…The EV of conception rate presented by Koots and Gibson (1998) included economic effects from related changes in cow culling rate (changes in calving score, milk yield and calf weaning weight caused by changes in herd structure). Similarly, the EVs of reproductive and health traits calculated by Wolfová et al (2007) reflected changes in the age structure of the cow herd and included changes in the total milk yield, even though the genetic potential for milk production was held constant.The EV of growth rate of replacement females calculated by Wolfová et al (2005) included the economic impact of the change in average age of heifers at calving, because heifers were assumed to be mated at fixed (optimal) weight. On the other hand, the EV of cow mature weight included the correlated effect of an increase in age at first mating of heifers (Wolfová et al, 2001), because the weight at first mating was expressed as a proportion of mature weight.…”