Common components and specific weights analysis: A chemometric method for dealing with complexity of food products

Mazerolles, Gérard; Hanafi, Mohamed; Dufour, Éric; Bertrand, Dominique; Qannari, El Mostafa

doi:10.1016/j.chemolab.2005.09.004

Cited by 75 publications

(54 citation statements)

References 16 publications

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“…The objective of CCSWA, presented in detail elsewhere [24], is to determine a space of representation common to all data tables, each table having a specific weight associated with each dimension of this common space. A customdesigned CCSWA algorithm programmed in MatLab was used in this study.…”

Section: Discussionmentioning

confidence: 99%

Investigation of the effects of season, milking region, sterilisation process and storage conditions on milk and UHT milk physico-chemical characteristics: a multidimensional statistical approach

Gaucher¹,

Boubellouta

Beaucher³

et al. 2008

Dairy Sci. Technol.

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-Milk samples were collected in five dairy plants located in different regions of France (North, North-West, South-West and centre of France), during spring and autumn, at receipt (bulkraw milk), and following pasteurisation and UHT sterilisation. Corresponding UHT milks were then stored at three temperatures (4, 20 and 40• C) and analysed after different times (21, 42, 62, 90, 110 and 180 d). The physico-chemical characteristics of these different milks, including composition, micellar properties and stability as assessed by heat, ethanol and phosphate tests, were determined. The database was processed by principal component analysis and common components and specific weights analysis. The effects of season, milking zone, process and storage conditions were highlighted, and the involved physico-chemical characteristics were determined. For the region effect, numerous parameters related to the global composition and the casein micelles intervened. Some differences in milk stability as evaluated by the ethanol and phosphate tests were also observed. Considering the season, spring milks had higher values of pH, lactose, soluble phosphate and micellar hydration than milks collected in autumn. These spring milks also had lower values of fat and heat stability than autumn milks. The UHT process effect was observed through decreases in non-casein nitrogen content and in micellar hydration and by an increase in casein micelle size for UHT milks. The stability values derived from phosphate and ethanol tests were increased following the UHT process. Concerning storage conditions, the temperature of 40• C led to a decrease in pH and increases in non-casein and non-protein nitrogen contents of milks. At 40• C, low values of stability for the heat test and high values for the phosphate test were observed.

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Section: Discussionmentioning

confidence: 99%

Investigation of the effects of season, milking region, sterilisation process and storage conditions on milk and UHT milk physico-chemical characteristics: a multidimensional statistical approach

Gaucher¹,

Boubellouta

Beaucher³

et al. 2008

Dairy Sci. Technol.

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“…Recently, spectroscopic techniques coupled with CCSWA were used as an accurate tool to monitor the molecular changes that occur in cheese throughout ripening (Mazerolles et al 2002(Mazerolles et al , 2006Kulmyrzaev et al 2005). The CCSWA showed its ability to describe the overall information collected from fluorescence and physico-chemical data tables and to extract relevant information at the molecular level throughout ripening of semi-hard cheese.…”

Section: Dairy Productsmentioning

confidence: 99%

Fluorescence spectroscopy and chemometrics in the food classification - a review

Sádecká¹,

Tóthová²

2007

Czech J. Food Sci.

180

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Sádecká J., Tóthová J. (2007): Fluorescence spectroscopy and chemometrics in the food classification − a review. Czech J. Food Sci., 25: 159-173.This review deals with the last few years' articles on various fluorescence techniques (conventional, excitation-emission matrix, and synchronous fluorescence spectroscopy) as a tool for the classification of food samples. Chemometric methods as principal component analysis, hierarchical cluster analysis, parallel factor analysis, and factorial discriminate analysis are briefly reminded. The respective publications are then listed according to the food samples: dairy products, eggs, meat, fish, edible oils, and others.

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“…The objective of CCSWA presented in detail elsewhere (Mazerolles et al 2006) is determining a common space of representation for all the data tables, each table having a specific weight associated with each dimension of this common space. The model of CCSWA can be presented as:…”

Section: Multidimensional Analysis Of Experimental Datamentioning

confidence: 99%

“…The advantages of CCSWA have recently been demonstrated by a statistical treatment of multiple tables presenting cheese composition, cheese rheology, and cheese fluorescence and mid-infrared spectra (Mazerolles et al 2006). The authors established and evaluated the relations among the tables characterizing different properties of cheeses.…”

Section: Introductionmentioning

confidence: 99%

Relations Between Spectral and Physicochemical Properties of Cheese, Milk, and Whey Examined Using Multidimensional Analysis

Kulmyrzaev

Dufour

2008

Food Bioprocess Technol

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Using standard technologies, 36 experimental hard, semi-hard, and soft cheeses were manufactured from milk produced at three different locations. Infrared, fluorescence, and physicochemical properties of cheeses and corresponding milks and wheys were measured, and a data collection consisting of 16 tables characterizing measured properties was built. This data collection was then subjected to statistical treatment using common components and specific weights analysis (CCSWA). As a result, specific weights of the data tables relating them to the common components, latent variables, and loadings of the data tables were calculated. Analysis of the CCSWA results along with the physicochemical properties of the experimental cheeses demonstrated that cheeses can be discriminated according to the properties of corresponding milk and whey.

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Common components and specific weights analysis: A chemometric method for dealing with complexity of food products

Cited by 75 publications

References 16 publications

Investigation of the effects of season, milking region, sterilisation process and storage conditions on milk and UHT milk physico-chemical characteristics: a multidimensional statistical approach

Investigation of the effects of season, milking region, sterilisation process and storage conditions on milk and UHT milk physico-chemical characteristics: a multidimensional statistical approach

Fluorescence spectroscopy and chemometrics in the food classification - a review

Relations Between Spectral and Physicochemical Properties of Cheese, Milk, and Whey Examined Using Multidimensional Analysis

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