Fourier Transform Infrared Spectrometric Method for the Rapid Determination of Casein in Raw Milk

Hewavitharana, Amitha K.; Brakel, Bram van

doi:10.1039/a700953d

Cited by 77 publications

(53 citation statements)

References 7 publications

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“…Before PLS analyses, two spectra regions (3040 to 3470 cm À1 and 1600 to 1700 cm À1 ) characterised by high noise levels were removed according to Hewavitharana and Brakel (1997), Jørgensen andNaes (2004), andDe Marchi et al (2013), and anomalous spectra and reference values were discarded according to the procedures reported by De . Models were developed using raw spectra data.…”

Section: Discussionmentioning

confidence: 99%

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

Toffanin

Marchi

López‐Villalobos

et al. 2015

International Dairy Journal

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Section: Discussionmentioning

confidence: 99%

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

Toffanin

Marchi

López‐Villalobos

et al. 2015

International Dairy Journal

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“…Several papers have also described the potential of this technology to measure a wide variety of components in milk, e.g. casein [12], acetone [13] and urea [14], in addition to the main components such as fat, protein and lactose as described for example in Reference [15].…”

Section: Spectroscopymentioning

confidence: 99%

A design and analysis strategy for situations with uncontrolled raw material variation

Jørgensen

Næs

2004

Journal of Chemometrics

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To be able to control an industrial process, it is necessary to know the relationship between raw materials, process settings and end-product results. In many situations the raw materials are highly complex and difficult to vary in a systematic way. This makes the use of standard experimental design techniques with a systematic variation in the variables difficult. To solve this, one might measure the raw materials at hand, but then the problem is to know what to measure. In this paper we present a general approach for such situations based on an experimental design in factors that are possible to control, a set up of raw material in blocks in combination with multivariate measurements (using FT-IR) of the raw material. To analyse the results, we include these measurements as principal components of the spectra. The usefulness of the approach is demonstrated with an example from cheese production. It is shown that it is possible to obtain a model for the amount of 'cheese fines' (a yield loss parameter) based on this approach. The final model contains readily measurable information about the raw materials but is obtained without any prior hypothesis about their contribution.

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“…A portion of the spectrum was truncated before the analysis due to its low signal-to-noise ratio (Pillonel et al, 2003); two spectra regions (3470 to 3040 cm 21 and 1700 to 1600 cm 21 ) were omitted from PLS analysis. The high level of noise at these wavelengths may be the consequence of the absorption of water in the spectral regions (Hewavitharana and Brakel, 1997;Jørgensen and Naes, 2004 ) and C-O stretching. PCA of the untreated spectra allowed for the investigation of the influence plot and hence the identification of possible outliers.…”

Section: Fa Compositionmentioning

confidence: 99%

Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk

Marchi

Penasa

Cecchinato

et al. 2011

Animal

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Mid-infrared spectroscopy (MIR) is used to predict fatty acid (FA) composition of individual milk samples (n 5 267) of Brown Swiss cows. FAs were analyzed by gas chromatography as a reference method. Samples were scanned (4000 to 900 cm 21) by MIR, and predictive models were developed using modified partial least squares regressions with full cross-validation. The methods using a first derivative or multiplicative scatter corrected plus first derivative resulted, on average, in the best predictions. Coefficients of correlation between measured and predicted C8:0, C10:0, C12:0, C14:0, anteiso-C17:0, c9-C18:1, and medium-and long-chain FA, and saturated, monounsaturated and unsaturated FA ranged from 0.71 to 0.77, suggesting that prediction models can be implemented in milk recording schemes to routinely collect information on FA composition from the whole Brown Swiss population for breeding purposes.Keywords: bovine milk, fatty acid, mid-infrared spectroscopy, Brown Swiss ImplicationMid-infrared spectroscopy demonstrated the potential to predict fatty acid (FA) composition by non-destructive, low cost and fast analysis. The prediction models were able to identify high and low values of individual and groups of FA in milk. Models developed in this study might be used in Brown Swiss population breeding programs aimed at improving the value of milk for human health and nutrition.

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Fourier Transform Infrared Spectrometric Method for the Rapid Determination of Casein in Raw Milk

Cited by 77 publications

References 7 publications

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

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

A design and analysis strategy for situations with uncontrolled raw material variation

Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk

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