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Investigation on the effectiveness of mid-infrared spectroscopy to predict detailed mineral composition of bulk milk

Published online by Cambridge University Press:  22 February 2018

Massimo Malacarne ,
Giulio Visentin ,
Andrea Summer ,
Martino Cassandro ,
Mauro Penasa ,
Giuseppe Bolzoni ,
Giorgio Zanardi  and
Massimo De Marchi
Massimo Malacarne
Affiliation:
Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
Giulio Visentin*
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Andrea Summer
Affiliation:
Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
Martino Cassandro
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Mauro Penasa
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Giuseppe Bolzoni
Affiliation:
Centro Referenza Nazionale Qualità Latte Bovino, IZSLER, Via Bianchi 9, 25124 Brescia, Italy
Giorgio Zanardi
Affiliation:
Centro Referenza Nazionale Qualità Latte Bovino, IZSLER, Via Bianchi 9, 25124 Brescia, Italy
Massimo De Marchi
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
*
*For correspondence; e-mail: [email protected]
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Abstract

This Research Communication investigated the potential of mid-infrared spectroscopy to predict detailed mineral composition of bovine milk. A total of 153 bulk milk samples were analysed for contents of Ca, Cl, Cu, Fe, K, Mg, Na, P and Zn. Also, soluble and colloidal fractions of Ca, Mg and P were quantified. For each milk sample the mid-infrared spectrum was captured and stored. Prediction models were developed using partial least squares regression and the accuracy of prediction was evaluated using both cross- and external validation. The proportion of variance explained by the prediction models in cross-validation ranged from 34% (Na) to 77% (total P), and it ranged from 13% (soluble Mg) to 54% (Cl−) in external validation. The ratio of the standard deviation of each trait to the standard error of prediction in external validation, which is an indicator of the practical utility of the prediction model, was low and never greater than 2. Results from the current study supported the limited usefulness of mid-infrared spectroscopy to predict minerals present in low concentration in bulk milk. For major mineral components, results from the present research did not match previous findings demonstrating the need for further studies using larger reference datasets.

Keywords

Fourier transform infrared spectrometrymilk mineralhuman healthdairy processing
Type
Research Article
Information
Journal of Dairy Research , Volume 85 , Issue 1 , February 2018 , pp. 83 - 86
Copyright
Copyright © Hannah Dairy Research Foundation 2018 

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References

Aleandri, R, Schneider, JC & Buttazzoni, LG 1989 Evaluation of milk for cheese production based on milk characteristics and Formagraph measures. Journal of Dairy Science 72 1967–1975 Google Scholar
Allen, R 1940 The estimation of phosphorus. Biochemical Journal 34 858–865 CrossRefGoogle ScholarPubMed
De Man, JM 1962 Measurement of the partition of some milk constituents between the dissolved and colloidal phases. Journal of Dairy Research 29 279–283 CrossRefGoogle Scholar
De Marchi, M, Toffanin, V, Cassandro, M & Penasa, M 2014 Invited review: Mid-infrared spectroscopy as a phenotyping tool for milk traits. Journal of Dairy Science 97 1171–1186 Google Scholar
Hermansen, JE, Badsberg, JH, Kristensen, T & Gundersen, V 2005 Major and trace elements in organically or conventionally produced milk. Journal of Dairy Research 72 362–368 CrossRefGoogle ScholarPubMed
Holt, C 2011 Interaction with casein. In Encyclopedia of Dairy Sciences, 2nd edition, pp. 917–924 (Eds Fuquay, J, Fox, P & Roginski, H). San Diego: Academic Press Google Scholar
Malacarne, M, Franceschi, P, Formaggioni, P, Sandri, S, Mariani, P & Summer, A 2014 Influence of micellar calcium and phosphorus on rennet coagulation properties of cows milk. Journal of Dairy Research 81 129–136 Google Scholar
Savini, E 1946 Analysis of Milk and Dairy Products. Milano: Hoepli Google Scholar
Soyeurt, H, Bruwier, D, Romnee, JM, Gengler, N, Bertozzi, C, Veselko, D & Dardenne, P 2009 Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry. Journal of Dairy Science 92 2444–2454 CrossRefGoogle ScholarPubMed
Toffanin, V, De Marchi, M, Lopez-Villalobos, N & Cassandro, M 2015 Effectiveness of mid-infrared spectroscopy for prediction of the contents of calcium and phosphorus, and titratable acidity of milk and their relationship with milk quality and coagulation properties. International Dairy Journal 41 68–73 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. Journal of Dairy Science 99 8137–8145 Google Scholar