Application of Machine Learning in Estimating Milk Yield According to the Phenotypic and Pedigree Data of Holstein-Friesian Cattle in Serbia

Chafai N., Hayah I., Houaga I., Badaoui B. (2023): A review of machine learning models applied to genomic prediction in animal breeding. Frontiers in Genetics, 14: 1150596. https://doi.org/10.3389/fgene.2023.1150596 Search in Google Scholar

Chollet F. (2017): Deep Learning with Python. Manning Publications Co. Search in Google Scholar

Dekkers J.C.M. (2004): Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons. Journal of Animal Science, 82 E-Suppl: E313-328. https://doi.org/10.2527/2004.8213_supplE313x Search in Google Scholar

FAO (2018): The state of Food and Agriculture. In: The State of the World. https://www.fao.org/3/i9549en/I9549EN.pdf Search in Google Scholar

Foley J.A., Ramankutty N., Brauman K.A., Cassidy E.S., Gerber J.S., Johnston M., Mueller N.D., O’Connell C., Ray D.K., West P.C., Balzer C., Bennett E.M., Carpenter S.R., Hill J., Monfreda C., Polasky S., Rockström J., Sheehan J., Siebert S., Tilman D., Zaks D.P.M. (2011): Solutions for a cultivated planet. Nature, 478(7369): 337-342. https://doi.org/10.1038/nature10452 Search in Google Scholar

González-Recio O., Rosa G.J.M., Gianola D. (2014): Machine learning methods and predictive ability metrics for genome-wide prediction of complex traits. Livestock Science, 166: 217-231. https://doi.org/https://doi.org/10.1016/j.livsci.2014.05.036 Search in Google Scholar

Hayes B.J., Bowman P.J., Chamberlain A.J., Goddard M.E. (2009): Invited review: Genomic selection in dairy cattle: Progress and challenges. Journal of Dairy Science, 92(2): 433-443. https://doi.org/https://doi.org/10.3168/jds.2008-1646 Search in Google Scholar

ICAR (2023): The Global Standard for Livestock Data. Statistics 2023. Available at: https://my.icar.org/stats/list (accessed on 17 January 2023). Search in Google Scholar

Meyer K. (2007): WOMBAT - A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). Journal of Zhejiang University SCIENCE B, 8(11): 815-821. https://doi.org/10.1631/jzus.2007.B0815 Search in Google Scholar

Morota G., Ventura R.V, Silva F.F., Koyama M., Fernando S.C. (2018): Big Data Analytics and Precision Animal Agriculture Symposium: Machine learning and data mining advance predictive big data analysis in precision animal agriculture 1. Journal of Animal Science, 96(4): 1540-1550. https://doi.org/10.1093/jas/sky014 Search in Google Scholar

Nayeri S., Sargolzaei M., Tulpan D. (2019): A review of traditional and machine learning methods applied to animal breeding. Animal Health Research Reviews, 20(1): 31-46. https://doi.org/10.1017/S1466252319000148 Search in Google Scholar

Shahinfar S., Mehrabani-Yeganeh H., Lucas C., Kalhor A., Kazemian M., Weigel K.A. (2012): Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems. Computational and Mathematical Methods in Medicine, 127130. https://doi.org/10.1155/2012/127130 Search in Google Scholar

Stanojević D., Đedović R., Bogdanović V., Popovac M., Perišić P., Beskorovajni R., Lazarević M. (2015): The potentials of using selection index in the assessment of breeding values of Holstein breeds in Serbia. Biotechnology in Animal Husbandry, 31(4): 523–532. https://doi.org/10.2298/bah1504523s Search in Google Scholar

Štrbac L., Pracner D., Šaran M., Janković D., Trivunović S., Ivković M., Tarjan L., Dedović N. (2023): Mathematical Modeling and Software Tools for Breeding Value Estimation Based on Phenotypic, Pedigree and Genomic Information of Holstein Friesian Cattle in Serbia. Animals, 13(4): 597. https://doi.org/10.3390/ani13040597 Search in Google Scholar

Tarjan L., Šenk I., Pracner D., Rajković D., Štrbac L. (2021): Possibilities for applying machine learning in dairy cattle breeding. 20^th International Symposium INFOTEH - Jahorina (INFOTEH), 1-6. https://doi.org/10.1109/INFOTEH51037.2021.9400672 Search in Google Scholar

UN (2019): World Population Prospects 2019. Available at: https://reliefweb.int/attachments/f46d3fce-97bb-327f-a065-a813f9969af7/WPP2019_Highlights.pdf Search in Google Scholar

Walstra P., Walstra P., Wouters J.T.M., Geurts T.J. (2005): Dairy Science and Technology (2^nd ed.). CRC Press, Taylor & Francis. https://doi.org/10.1201/9781420028010 Search in Google Scholar