HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Interpretive Summary Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Etzion, Y. Articles by Shmulevich, I. Search for Related Content PubMed PubMed Citation Articles by Etzion, Y. Articles by Shmulevich, I.

Determination of Protein Concentration in Raw Milk by Mid-Infrared Fourier Transform Infrared/Attenuated Total Reflectance Spectroscopy

¹ The Interdisciplinary Program of Biotechnology,
² Department of Civil and Environmental Engineering,
³ Department of Biotechnology and Food Engineering, Technion–Israel Institute of Technology, Haifa, Israel

Corresponding author: R. Linker; e-mail: linkerr{at}tx.technion.ac.il.

This study investigates the potential use of attenuated total reflectance spectroscopy in the mid-infrared range for determining protein concentration in raw cow milk. The determination of protein concentration is based on the characteristic absorbance of milk proteins, which includes 2 absorbance bands in the 1500 to 1700 cm^–1 range, known as the amide I and amide II bands, and absorbance in the 1060 to 1100 cm^–1 range, which is associated with phosphate groups covalently bound to casein proteins. To minimize the influence of the strong water band (centered around 1640 cm^–1) that overlaps with the amide I and amide II bands, an optimized automatic procedure for accurate water subtraction was applied. Following water subtraction, the spectra were analyzed by 3 methods, namely simple band integration, partial least squares (PLS) and neural networks. For the neural network models, the spectra were first decomposed by principal component analysis (PCA), and the neural network inputs were the spectra principal components scores. In addition, the concentrations of 2 constituents expected to interact with the protein (i.e., fat and lactose) were also used as inputs. These approaches were tested with 235 spectra of standardized raw milk samples, corresponding to 26 protein concentrations in the 2.47 to 3.90% (weight per volume) range. The simple integration method led to very poor results, whereas PLS resulted in prediction errors of about 0.22% protein. The neural network approach led to prediction errors of 0.20% protein when based on PCA scores only, and 0.08% protein when lactose and fat concentrations were also included in the model. These results indicate the potential usefulness of Fourier transform infrared/attenuated total reflectance spectroscopy for rapid, possibly online, determination of protein concentration in raw milk.

Key Words: raw milk • mid-infrared • attenuated total reflectance • Fourier transform infrared spectroscopy

Abbreviation key: ATR = attenuated total reflectance, AU = absorbance units, FTIR = Fourier transform infrared, IR = infrared, MIR = mid infrared, NN = neural networks, PCA = principal component analysis, PLS = partial least squares.

This article has been cited by other articles:

				S. T. Martin-del-Campo, D. Picque, R. Cosio-Ramirez, and G. Corrieu Evaluation of Chemical Parameters in Soft Mold-Ripened Cheese During Ripening by Mid-Infrared Spectroscopy J Dairy Sci, June 1, 2007; 90(6): 3018 - 3027. [Abstract] [Full Text] [PDF]