Abstract
Submitted 2020-08-02 | Accepted 2020-09-21 | Available 2020-12-01 https://doi.org/10.15414/afz.2020.23.mi-fpap.326-330 Feed efficiency has a major influence on farm profitability and environmental stewardship in the dairy industry. The aim of this study was to describe a new selection index adopted by the Italian Holstein and Jersey Association (ANAFIJ, Cremona, Italy) to improve feed efficiency using data recorded by the official dairy recording system. Predicted dry matter intake (pDMI) was derived from milk yield, fat content, and estimated cow body weight. Fat-protein corrected milk (FPCM) was derived from milk yield corrected for fat, protein, and a fixed coefficient for lactose content (4.80%). Therefore, the predicted feed efficiency (pFE) was estimated as ratio between FPCM and pDMI. Average pFE was 1.27±0.18 (kg.d -1 ) with heritability of 0.32. Predicted Feed Efficiency index (pFEi), traditional and genomic, has been implemented in the Italian Holstein Friesian evaluation system. Results suggest that pFEi may be a new breeding objective for Italian Friesians. The official selection index (PFT), in use since 2002, is positively correlated with pFEi. However, the introduction of pFEi will improve the positive feed efficiency trend. This approach will permit the Italian Holstein Friesian breeders to improve feed efficiency, without increasing costs of recording system. However, to avoid the risk of selecting animals with an excessive negative energy balance after calving, it would be useful to include in the pFE a correction for body condition score and reproductive performances. Meanwhile, in order to increase the accuracy of the predicted phenotype, an Italian consortium is creating a consistent phenotypic critical mass of individual data for dry matter intake in cows, heifers and young bulls. Keywords: feed efficiency, cattle breeding, dry matter intake, breeding value estimation References Cassandro, M. (2020). Animal breeding and climate change, mitigation and adaptation. Journal of Animal Breeding and Genetics, 137(2), 121-122. https://doi.org/10.1111/jbg.12469 Cassandro, M. et al. (2010). Genetic parameters of predicted methane production in Holstein Friesian cows. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany. Cassandro, M., Mele, M. and Stefanon, B. (2013). Genetic aspects of enteric methane emission in livestock ruminants. Italian Journal of Animal Science, 12(3), 450-458. De Haas, Y. et al. (2012). Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets. Journal of Dairy Science, 95(10), 6103-6112. De Vries, M. and Veerkamp, R. (2000). Energy balance of dairy cattle in relation to milk production variables and fertility. Journal of Dairy Science, 83(1), 62-69. Finocchiaro, R. et al. (2017). Body weight prediction in Italian Holstein cows. ICAR Technical Series, 22, 95-98. Hegarty, R. et al. (2007). Cattle selected for lower residual feed intake have reduced daily methane production. Journal of Animal Science, 85(6), 1479-1486. Hurley, A. M. et al. (2018). Characteristics of feed efficiency within and across lactation in dairy cows and the effect of genetic selection. Journal of Dairy Science, 101(2), 1267-1280. https://doi.org/https://doi.org/10.3168/jds.2017-12841 Meuwissen, T. H., Hayes, B. J. and Goddard, M. E. (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157(4), 1819-1829. National Research Council. (2001). Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001. The National Academies Press. http://www.nap.edu/catalog.php?record_id=9825 Pryce, J. et al. (2014). Genomic selection for feed efficiency in dairy cattle. Animal, 8(1), 1-10. Sjaunja, L. et al. (1990). A Nordic proposal for an energy corrected milk formula. Proceedings of the 2nd Session of Committee for Recording and Productivity of Milk Animal, Paris, p. 156. Veerkamp, R. et al. (2000). Genetic correlation between days until start of luteal activity and milk yield, energy balance, and live weights. Journal of Dairy Science, 83(3), 577-583. Verbyla, K. et al. (2010). Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information. Journal of Dairy Science, 93(6), 2757-2764. Wall, E., Coffey, M. and Brotherstone, S. (2007). The relationship between body energy traits and production and fitness traits in first-lactation dairy cows. Journal of Dairy Science, 90(3), 1527-1537. Wallace, R. J. et al. (2019). A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions. Science Advances, 5(7), eaav8391.
Highlights
Feed costs are half of the total costs of dairy production
One way to produce estimated breeding values (EBV) for traits difficult to collect at population level is to use genomic selection (Meuwissen et al, 2001), where phenotypes such as dry matter intake (DMI) are measured in a subset of the population, and genomic predictions are calculated for other animals that have genotypes but not phenotypes (Pryce et al, 2014)
Genetic parameters were applied to the entire test-day dataset to obtain estimated breeding values (EBV) for Predicted Feed Efficiency index on a score scale of 100±5 in order to make possible the comparison of pFEi with all other functional traits published by ANAFIJ
Summary
Feed costs are half of the total costs of dairy production. One possibility to increase profitability of dairy production is to reduce feed costs by improving feed efficiency. One way to produce estimated breeding values (EBV) for traits difficult to collect at population level is to use genomic selection (Meuwissen et al, 2001), where phenotypes such as DMI are measured in a subset of the population, and genomic predictions are calculated for other animals that have genotypes but not phenotypes (Pryce et al, 2014). This approach is appealing, allowing industry-wide selection for improved efficiency, the size of the reference population from which the genomic prediction equations are derived is currently too small within each country to achieve satisfactory
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