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Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits.

Authors :
McDermott, A.
Visentin, G.
McParland, S.
Berry, D. P.
Fenelon, M. A.
De Marchi, M.
Source :
Journal of Dairy Science. May2016, Vol. 99 Issue 5, p3267-3273. 7p.
Publication Year :
2016

Abstract

The color of milk affects the subsequent color features of the resulting dairy products; milk color is also related to milk fat concentration. The objective of the present study was to quantify the ability of mid-infrared spectroscopy (MIRS) to predict color-related traits in milk samples and to estimate the correlations between these color-related characteristics and traditional milk quality traits. Mid-infrared spectral data were available on 601 milk samples from 529 cows, all of which had corresponding gold standard milk color measures determined using a Chroma Meter (Konica Minolta Sensing Europe, Nieuwegein, the Netherlands); milk color was expressed using the CIELAB uniform color space. Separate prediction equations were developed for each of the 3 color parameters (L* = lightness, a* = greenness, b* = yellowness) using partial least squares regression. Accuracy of prediction was determined using both cross validation on a calibration data set (n = 422 to 457 samples) and external validation on a data set of 144 to 152 samples. Moderate accuracy of prediction was achieved for the b* index (coefficient of correlation for external validation = 0.72), although poor predictive ability was obtained for both a* and L* indices (coefficient of correlation for external validation of 0.30 and 0.55, respectively). The linear regression coefficient of the gold standard values on the respective MIRS-predicted values of a*, L*, and b* was 0.81, 0.88, and 0.96, respectively; only the regression coefficient on L* was different from 1. The mean bias of prediction (i.e., the average difference between the MIRS-predicted values and gold standard values in external validation) was not different from zero for any of 3 parameters evaluated. A moderate correlation (0.56) existed between the MIRS-predicted L* and b* indices, both of which were weakly correlated with the a* index. Milk fat, protein, and casein were moderately correlated with both the gold standard and MIRS-predicted values for b*. Results from the present study indicate that MIRS data provides an efficient, low-cost screening method to determine the b* color of milk at a population level. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00220302
Volume :
99
Issue :
5
Database :
Academic Search Index
Journal :
Journal of Dairy Science
Publication Type :
Academic Journal
Accession number :
114283415
Full Text :
https://doi.org/10.3168/jds.2015-10424