The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry
Tobin, John T.
Crowley, Shane V.
Kelly, Alan L.
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CitationParmar, P.; Lopez-Villalobos, N.; Tobin, J.T.; Murphy, E.; McDonagh, A.; Crowley, S.V.; Kelly, A.L.; Shalloo, L. The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry. Foods 2020, 9, 1004. https://doi.org/10.3390/foods9081004
AbstractThe objective of this study was to determine the effect of seasonal variation on milk composition and establish an algorithm to predict density based on milk composition to enable the calculation of season-based density conversion calculations. A total of 1035 raw whole milk samples were collected from morning and evening milking of 60 spring-calving individual cows of different genetic groups, namely Jersey, Elite HF (Holstein–Friesian) and National Average HF, once every two weeks for a period of 9 months (March–November, 2018). The average mean and standard deviation for milk compositional traits were 4.72 ± 1.30% fat, 3.85 ± 0.61% protein and 4.69 ± 0.30% lactose and density was estimated at 1.0308 ± 0.002 g/cm3 . The density of the milk samples was evaluated using three methods: a portable density meter, DMA 35; a standard desktop version, DMA 4500M; and an Association of Official Agricultural Chemists (AOAC) method using 100-mL glass pycnometers. Statistical analysis using a linear mixed model showed a significant difference in density of milk samples (p < 0.05) across seasonal and compositional variations adjusted for the effects of days in milk, parity, the feeding treatment, the genetic group and the measurement technique. The mean density values and standard error of mean estimated for milk samples in each season, i.e., spring, summer and autumn were 1.0304 ± 0.00008 g/cm3 , 1.0314 ± 0.00005 g/cm3 and 1.0309 ± 0.00007 g/cm3 , respectively.
FunderEnterprise Ireland; Science Foundation Ireland; Department of Agriculture, Food and Marine
Grant NumberTC20140016; 16/RC/3835
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