[Aguilar M., Hanigan M.D., Tucker H.A., Jones B.L., Garbade S.K., Mc Gilliard M.L., Stallings C.C., Knowlton K.F., James R.E. (2012). Cow and herd variation in milk urea nitrogen concentrations in lactating dairy cattle. J. Dairy Sci., 95: 7261–7268.]Search in Google Scholar
[Ali A.K.A, Shook G.E. (1980). An optimum transformation for somatic cell concentration in milk. J. Dairy Sci., 63: 487–490.]Search in Google Scholar
[ANAFIJ(Italian Holsteinand Jersey Breeders Association). (2020). Index calculation cards. Accessed Apr. 5, 2020. http://www.anafi.it/en/genetic-indexes/index-calculation-cards]Search in Google Scholar
[ANAPRI(Italian Simmental Cattle Breeders Association). (2020). L’indice di selezione. Accessed Apr. 4, 2020. https://www.anapri.eu/index.php?option=com_content&view=article&id=68&Itemid=97]Search in Google Scholar
[ANARB(Italian Brown Cattle Breeders Association). (2020). Italian Brown breed. Accessed Apr. 5, 2020. http://www.anarb.it/en/about-us/italian-brown-breed]Search in Google Scholar
[Breeders Associationof Bolzano Province. (2018). Annual activity report for the production year 2018. Accessed Feb. 15, 2020 https://www.vstz.it/de/suedtiroler-tierzuchtvereinigung-service/downloads]Search in Google Scholar
[Brinkmann J., Ivenmeyer S., Pelzer A., Winckler C., Zapf R. (2016). Tierschutzindikatoren: Leitfaden für die Praxis-Rind. Vorschläge für die Produktionsrichtungen Milchkuh, Aufzuchtkalb, Mastrind. KTBL.]Search in Google Scholar
[Bruckmaier R.M., Ontsouka C.E., Blum J.W. (2004). Fractionized milk composition in dairy cows with subclinical mastitis. Veterinární medicína, 49: 283–290.]Search in Google Scholar
[Buttchereit N., Stamer E., Junge W., Thaller G. (2012). Genetic parameters for energy balance, fat/protein ratio, body condition score and disease traits in German Holstein cows. J. Anim. Breed. Genet., 129: 280–288.]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. J. Dairy Sci., 102: 5883–5898.]Search in Google Scholar
[Dal Zotto R., Penasa M., De Marchi M., Cassandro M., López-Villalo-bos N., Bittante G. (2009). Use of crossbreeding with beef bulls in dairy herds: Effect on age, body weight, price, and market value of calves sold at livestock auctions. J. Anim. Sci., 87: 3053–3059.]Search in Google Scholar
[De Marchi M., Toffanin V., Cassandro M., Penasa M. (2014). Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. J. Dairy Sci., 97: 1171–1186.]Search in Google Scholar
[Fatehi F., Zali A., Honarvar M., Dehghan-Banadaky M., Young A.J., Ghiasvand M., Eftekhari M. (2012). Review of the relationship between milk urea nitrogen and days in milk, parity, and monthly temperature mean in Iranian Holstein cows. J. Dairy Sci., 95: 5156–5163.]Search in Google Scholar
[Faustini M., Chiesa L.M., Munari E., Curone G., Colombani C., Vigo D. (2016). A survey on mono-polyunsaturated fatty acids, desaturase indices and atherogenic index in the milk fat of local breeds (Cabannina, Varzese and Valdostana) reared in northern Italy. J. Dairy Vet. Anim. Res., 3: 207–211.]Search in Google Scholar
[Franzoi M., Niero G., Visentin G., Penasa M., Cassandro M., De Marchi M. (2019 a). Variation of detailed protein composition of cow milk predicted from a large database of midinfrared spectra. Animals, 9: 176.10.3390/ani9040176652343331003454]Search in Google Scholar
[Franzoi M., Manuelian C.L., Penasa M., De Marchi M. (2019 b). Effects of somatic cell score on milk yield and mid-infrared predicted composition and technological traits of Brown Swiss, Holstein Friesian, and Simmental cattle breeds. J. Dairy Sci., 103: 791–804.10.3168/jds.2019-1691631733847]Search in Google Scholar
[Gorlier A., Lonati M., Renna M., Lussiana C., Lombardi G., Battaglini L.M. (2012). Changes in pasture and cow milk compositions during a summer transhumance in the western Italian Alps. J. Appl. Bot. Food Qual., 85: 216–223.]Search in Google Scholar
[Hein L., Sørensen L.P., Kargo M., Buitenhuis A.J. (2018). Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations. J. Dairy Sci., 101: 2148–2157.]Search in Google Scholar
[Hossein-Zadeh N.G., Ardalan M. (2011). Estimation of genetic parameters for milk urea nitrogen and its relationship with milk constitutes in Iranian Holsteins. Livest. Sci., 135: 274–281.]Search in Google Scholar
[Ikonen T., Morri S., Tyrisevä A.M., Ruottinen O., Ojala M. (2004). Genetic and phenotypic correlations between milk coagulation properties, milk production traits, somatic cell count, casein content, and pH of milk. J. Dairy Sci., 87: 458–467.]Search in Google Scholar
[Kirchnerová K., Vršková M. (2015). Milk fatty acid profile in different breeds of dairy cattle. J. Microbiol. Biotech. Food Sci., 4: 78–81.]Search in Google Scholar
[Koczura M., Martin B., Turille G., De Marchi M., Kreuzer M., Berard J. (2019). Milk composition, but not cheese properties, are impaired the day after transhumance to alpine pastures. Int. Dairy J., 99: 104540.]Search in Google Scholar
[Koczura M., Bouchon M., Turille G., De Marchi M., Kreuzer M., Berard J., Martin B. (2020). Consequences of walking or transport by truck on milk yield and quality, as well as blood metabolites, in Holstein, Montbéliarde, and Valdostana dairy cows. J. Dairy Sci., 103: 3470–3478.]Search in Google Scholar
[Kühl S., Flach L., Gauly M. (2020). Economic assessment of small-scale mountain dairy farms in South Tyrol depending on feed intake and breed. Ital. J. Anim. Sci., 19: 41–50.]Search in Google Scholar
[Litwińczuk Z., Król J., Brodziak A., Barłowska J. (2011). Changes of protein content and its fractions in bovine milk from different breeds subject to somatic cell count. J. Dairy Sci., 94: 684–691.]Search in Google Scholar
[Magne M.A., Thénard V., Mihout S. (2016). Initial insights on the performances and management of dairy cattle herds combining two breeds with contrasting features. Animal, 10: 892–901.]Search in Google Scholar
[Manuelian C.L., Penasa M., Visentin G., Benedet A., Cassandro M., De Marchi M. (2019). Multi-breed herd approach to detect breed differences in composition and fatty acid profile of cow milk. Czech. J. Anim. Sci., 64: 11–16.]Search in Google Scholar
[Mattiello S., Battini M., Andreoli E., Barbieri S. (2011). Short communication: Breed differences affecting dairy cattle welfare in traditional alpine tie-stall husbandry systems. J. Dairy Sci., 94: 2403–2407.]Search in Google Scholar
[Mc Dermott A., Visentin G., De Marchi M., Berry D.P., Fenelon M.A., O’Connor P.M., Kenny O.A., Mc Parland S. (2016). Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics. J. Dairy Sci., 99: 3171–3182.]Search in Google Scholar
[Negussie E., Stradén I., Mäntysaari E.A. (2013). Genetic associations of test-day fat:protein ratio with milk yield, fertility, and udder health traits in Nordic Red cattle. J. Dairy Sci., 96: 1237–1250.]Search in Google Scholar
[Penasa M., Tiezzi F., Sturaro A., Cassandro M., De Marchi M. (2014). A comparison of the predicted coagulation characteristics and composition of milk from multi-breed herds of Holstein-Friesian, Brown Swiss and Simmental cows. Int. Dairy J., 35: 6–10.]Search in Google Scholar
[Perathoner G., Kasal A., Plitzner C. (2010). Stima del bilancio foraggero per l’Alto Adige. Quaderno Sozooalpino, 6: 111–122.]Search in Google Scholar
[Raboisson D., Albaaj A., Nonne G., Foucras G. (2017). High urea and pregnancy or conception in dairy cows: A meta-analysis to define the appropriate urea threshold. J. Dairy Sci., 100: 7581–7587.]Search in Google Scholar
[Rajala-Schultz P.J., Saville W.J.A. (2003). Sources of variation in milk urea nitrogen in Ohio dairy herds. J. Dairy Sci., 86: 1653–1661.]Search in Google Scholar
[Rasmussen B.M., Vessby B., Uusitupa M., Berglund L., Pedersen E., Riccardi G., Rivellese A.A., Tapsell L., Hermansen K. (2006). Effects of dietary saturated, monounsaturated, and n-3 fatty acids on blood pressure in healthy subjects. Am. J. Clin. Nutr., 83: 221–226.]Search in Google Scholar
[Rupp R., Boichard D. (2003). Genetics of resistance to mastitis in dairy cattle. Vet. Res., 34: 671–688.]Search in Google Scholar
[South Tyrolean Dairy Association. (2018). Annual activity report from the South Tyrolean Dairy Association. Accessed Feb. 15, 2020. https://www.suedtirolermilch.com/ueber-milch/sennereiverbandsuedtirol]Search in Google Scholar
[Stergiadis S., Bieber A., Franceschin E., Isensee A., Eyre M.D., Maurer V., Chatzidimitriou E., Cozzi G., Bapst B., Stewart G., Gordon A., Butler G. (2015). Impact of US Brown Swiss genetics on milk quality from low-input herds in Switzerland: Interactions with grazing intake and pasture type. Food Chem., 175: 609–618.]Search in Google Scholar
[Sturaro E., Marchiori E., Cocca G., Penasa M., Ramazin M., Bittante G. (2013). Dairy systems in mountainous areas: Farm animal biodiversity, milk production and destination, and land use. Livest. Sci., 158: 157–168.]Search in Google Scholar
[Vilas Boas D., Vercesi Filho A., Pereira M., Roma Junior L., El Faro L. (2017). Association between electrical conductivity and milk production traits in Dairy Gyr cows. J. Appl. Anim. Res., 45: 227–233.]Search in Google Scholar
[Visentin G., Mc Dermott A., Mc Parland S., Berry D.P., Kenny O.A., Brodkorb A., Fenelon M.A., De Marchi M. (2015). Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows. J. Dairy Sci., 98: 6620–6629.]Search in Google Scholar
[Visentin G., Penasa M., Gottardo P., Cassandro M., De Marchi M. (2016). Predictive ability of mid-infrared spectroscopy for major mineral composition and coagulation traits of bovine milk by using the uninformative variable selection algorithm. J. Dairy Sci., 99: 8137–8145.]Search in Google Scholar
[Visentin G., Penasa M., Niero G., Cassandro M., De Marchi M. (2018). Phenotypic characterization of major mineral composition predicted by mid-infrared spectroscopy in cow milk. Ital. J. Anim. Sci., 17: 549–556.]Search in Google Scholar
[Wang L., Manson J.E., Forman J.P., Gaziano J.M., Buring J.E., Sesso H.D. (2010). Dietary fatty acids and the risk of hypertension in middle-aged and older women. Hypertension, 56: 598–604.]Search in Google Scholar
[Wattiaux M.A., Nordheim E.V., Crump P. (2005). Statistical evaluation of factors and interactions affecting dairy herd improvement milk urea nitrogen in commercial Midwest dairy herds. J. Dairy Sci., 88: 3020–3035.]Search in Google Scholar