Population-level phenotyping is, for some traits, hardly achievable due to limitation of reference analyses. Mid-infrared spectroscopy (MIRS) is a quick and cost-effective laboratory technique allowing the prediction of innovative milk quality features on a large scale. The present study aimed at investigating factors associated with milk Ca, K, Mg, Na and P contents predicted by MIRS models on a large multi-breed spectral data set of 123,240 test-day records. Two dairy (Holstein–Friesian and Brown Swiss) and two dual-purpose (Simmental and Alpine Grey) cattle breeds were considered. Sources of variation of predicted milk mineral contents were studied using linear mixed models, including the fixed effects of breed, month of sampling, stage of lactation, parity and interactions between the main effects. Random factors were herd nested within breed, cow nested within breed and the residual. Calcium content was greater in milk of dual-purpose than dairy cattle breeds. Simmental cows produced milk with the greatest content of Ca and Na, and milk of Holstein-Friesian had the lowest P content. Variation of content of Ca, Mg, Na and P throughout lactations exhibited an opposite trend to that of milk yield, with the lowest values around the peak of lactation. On the other hand, K content mirrored the trend of milk yield. Multiparous cows had lower content of milk minerals, with the exception of Na, compared with first parity animals. Environmental factors identified in the present study can be considered for within-breed genetic evaluation to adjust records of milk mineral contents for these effects.

Phenotypic characterisation of major mineral composition predicted by mid-infrared spectroscopy in cow milk / Visentin, Giulio; Penasa, Mauro; Niero, Giovanni; Cassandro, Martino; De Marchi, Massimo. - In: ITALIAN JOURNAL OF ANIMAL SCIENCE. - ISSN 1828-051X. - STAMPA. - 17:3(2018), pp. 549-556. [10.1080/1828051X.2017.1398055]

Phenotypic characterisation of major mineral composition predicted by mid-infrared spectroscopy in cow milk

Visentin, Giulio;
2018

Abstract

Population-level phenotyping is, for some traits, hardly achievable due to limitation of reference analyses. Mid-infrared spectroscopy (MIRS) is a quick and cost-effective laboratory technique allowing the prediction of innovative milk quality features on a large scale. The present study aimed at investigating factors associated with milk Ca, K, Mg, Na and P contents predicted by MIRS models on a large multi-breed spectral data set of 123,240 test-day records. Two dairy (Holstein–Friesian and Brown Swiss) and two dual-purpose (Simmental and Alpine Grey) cattle breeds were considered. Sources of variation of predicted milk mineral contents were studied using linear mixed models, including the fixed effects of breed, month of sampling, stage of lactation, parity and interactions between the main effects. Random factors were herd nested within breed, cow nested within breed and the residual. Calcium content was greater in milk of dual-purpose than dairy cattle breeds. Simmental cows produced milk with the greatest content of Ca and Na, and milk of Holstein-Friesian had the lowest P content. Variation of content of Ca, Mg, Na and P throughout lactations exhibited an opposite trend to that of milk yield, with the lowest values around the peak of lactation. On the other hand, K content mirrored the trend of milk yield. Multiparous cows had lower content of milk minerals, with the exception of Na, compared with first parity animals. Environmental factors identified in the present study can be considered for within-breed genetic evaluation to adjust records of milk mineral contents for these effects.
2018
Phenotypic characterisation of major mineral composition predicted by mid-infrared spectroscopy in cow milk / Visentin, Giulio; Penasa, Mauro; Niero, Giovanni; Cassandro, Martino; De Marchi, Massimo. - In: ITALIAN JOURNAL OF ANIMAL SCIENCE. - ISSN 1828-051X. - STAMPA. - 17:3(2018), pp. 549-556. [10.1080/1828051X.2017.1398055]
Visentin, Giulio; Penasa, Mauro; Niero, Giovanni; Cassandro, Martino; De Marchi, Massimo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/776618
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