[
Atasever S. & Erdem H. (2008): An investigation on the determination of mastitis risk levels and milk production traits in holstein cows. Journal of Applied Animal Research, 34(1): 13-16.
]Search in Google Scholar
[
Babnik D., Verbič J., Podgoršek P., Jeretina J., Perpar T., Logar B., Sadar M., Ivanovič B. (2004): Priročnik za vodenje prehrane krav molznic ob pomoči rezultatov mlečne kontrole. Kmetiljsi inštitut Slovenije.
]Search in Google Scholar
[
Costa A., Lopez-Villalobos N., Sneddon N.W., Shalloo L., Franzoi M., De Marchi M., Penasa M. (2019): Invited review: Milk lactose-Current status and future challenges in dairy cattle. Journal of Dairy Science, 102(7): 5883-5898.
]Search in Google Scholar
[
Ebrahimi M., Mohammadi-Dehcheshmeh M., Ebrahimie E., Petrovski K.R (2019): Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models. Computers in Biology and Medicine, 114: 103456.
]Search in Google Scholar
[
Gantner V., Mijić P., Kuterovac K., Solić D., Gantner R. (2011): Temperature-humidity index values and their significance on the daily production of dairy cattle. Mljekarstvo, 61(1): 56-63.
]Search in Google Scholar
[
Halasa T., Huijps, K., Østerås O., Hogeveen H. (2007): Economic effects of bovine mastitis and mastitis management: A review. Veterinary Quarterly, 29(1), 18-31.
]Search in Google Scholar
[
ICAR (2017): Guidelines for Dairy Cattle Milk Recording. Guidelines.
]Search in Google Scholar
[
Nóbrega D.B. & Langoni H. (2011): Breed and season influence on milk quality parameters and in mastitis occurrence. Pesqui. Vet. Bras., 31(12): 1045-1052.
]Search in Google Scholar
[
Özkan Gülzari Ş., Vosough Ahmadi B., Stott A.W. (2018): Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway. Preventive Veterinary Medicine, 150: 19-29.
]Search in Google Scholar
[
Pyorala S. (2003): Indicators of inflammation in the diagnosis of mastitis. Veterinary Research, 34(5): 565-578.
]Search in Google Scholar
[
SAS Institute Inc. (2019): SAS User’s Guide, Version 9.4. SAS Institute Inc. Cary, NC.
]Search in Google Scholar
[
Tomazi T., Ferreira G.C., Orsi A.M., Gonçalves J.L., Ospina P.A., Nydam D.V., Moroni P., dos Santos M.V. (2018): Association of herd-level risk factors and incidence rate of clinical mastitis in 20 Brazilian dairy herds. Preventive Veterinary Medicine, 161: 9-18.
]Search in Google Scholar
[
Silanikove N., Merin U., Shapiro F., Leitner G. (2014): Milk metabolites as indicators of mammary gland functions and milk quality. Journal of Dairy Research, 81(3): 358-363.
]Search in Google Scholar
[
Valdrina F., Dimitar N., Besirm J., Metodija T. (2014): Economics of milk yield losses in one dairy farm in Macedonia associated with clinical mastitis. International Journal of Business & Technology, 3(1): 42-50.
]Search in Google Scholar
[
Weber C.T., Corrêa Schneider C.L., Busanello M., Bandeira Calgaro J.L., Fioresi J., Gehrke C.R., da Conceição J.M., Haygert-Velho I.M.P. (2020): Season effects on the composition of milk produced by a Holstein herd managed under semi-confinement followed by compost bedded dairy barn management. Semina: Ciencias Agrarias, 41(5): 1667-1678.
]Search in Google Scholar