Inherent and process-induced hydrophobicity influences aroma retention in fat-free dairy matrices

Heilig, Andrej; Çetin, Sümeyye; Erpenbach, Kerstin; Höhn, Judith; Hinrichs, Jörg

doi:10.1016/j.idairyj.2011.01.002

Cited by 9 publications

(20 citation statements)

References 54 publications

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“…Heilig et al . () have shown that the hydrophobicity of acidified model dairy matrices increases with increasing protein content. This means that at higher protein contents, there are more hydrophobic binding sites to which hydrophobic volatiles can attach, which apparently impedes their diffusion.…”

Section: Resultsmentioning

confidence: 98%

“…The model dairy matrices were produced as described by Heilig et al (2011). Micellar casein and whey protein isolate were dissolved in ultrafiltration permeate at a casein protein to whey protein ratio (CWR) of 80:20.…”

Section: Preparation and Analysis Of Flavored And Nonflavored Model Dmentioning

confidence: 99%

“…Between a log P of +1.8 (ethyl butanoate) and +2.8 (ethyl hexanoate), a direct proportionality between Da and log P was observed, independent of the protein content. Heilig et al (2011) have shown that the hydrophobicity of acidified model dairy matrices increases with increasing protein content. This means that at higher protein contents, there are more hydrophobic binding sites to which hydrophobic volatiles can attach, which apparently impedes their diffusion.…”

Section: Effect Of Protein Content and Dwpdmentioning

confidence: 99%

“…3B). An analysis of bonds, performed according to Heilig et al (2011), showed that in the acidified matrix made from model milk with a DWPD of 91.9%, 35.4 Ϯ 1.6% of the total protein was stabilized by disulfide bonds, but still 52.9 Ϯ 1.5% was stabilized by hydrophobic interactions. Model milk with a DWPD of 2.7% resulted in an acidified matrix where none of the protein was stabilized by disulfide bonds, and 80.7 Ϯ 5.0% was stabilized by hydrophobic interactions.…”

Section: Effect Of Protein Content and Dwpdmentioning

confidence: 99%

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Determination of Aroma Volatile Diffusion Coefficients in Set‐Type Acidified Dairy Matrices of Different Composition and Microstructure by Means of the Concentration Profile Technique in Combination with Headspace Gas Chromatography

Heilig

Hahn

Erpenbach

et al. 2013

Journal of Texture Studies

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The diffusion of aroma volatiles in set-type acidified dairy matrices of different composition and structure was investigated using the concentration profile technique (CPT) in combination with headspace gas chromatography (HSGC). Multiphase confocal laser scanning microscopy and puncture testing were used to characterize the micro-and macrostructure of the matrices. Aroma volatiles under investigation included diacetyl, (Z)-3-hexenol, ethyl butanoate, ethyl-2-methylbutanoate, (Z)-3-hexenyl acetate, ethyl hexanoate and limonene, and covered a wide range of hydrophobicity. CPT in combination with HSGC was found suitable to determine apparent diffusion coefficients at equilibrium. Increased overall protein content decreased the diffusivity of hydrophobic volatiles. At 4% protein content, diffusivity remained unaffected by process-induced changes in the protein network density. Addition of milk fat substantially decreased the mobility of hydrophobic volatiles. In milk fat-containing matrices, the addition of pectin did not change the diffusion properties of the volatiles, independent of their hydrophobicity. PRACTICAL APPLICATIONSThis study is relevant to the producers of acidified dairy products such as yoghurt, fresh cheese and quarg. The results specify within which boundaries several core parameters of manufacture, such as the addition of pectin, the intensity of milk heating, shearing and adaptations in protein and fat content, may be changed at a minimized risk of altered aroma delivery during consumption. This information amplifies the technological possibilities of the manufacturers and increases their flexibility in terms of product composition and processing. Aroma suppliers could use the outcomes of this study to modify the composition of their aromas based on dairy product specifications and the hydrophobicity of the individual aroma compounds they are using.

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Section: Resultsmentioning

confidence: 98%

Section: Preparation and Analysis Of Flavored And Nonflavored Model Dmentioning

confidence: 99%

Section: Effect Of Protein Content and Dwpdmentioning

confidence: 99%

Section: Effect Of Protein Content and Dwpdmentioning

confidence: 99%

See 2 more Smart Citations

Determination of Aroma Volatile Diffusion Coefficients in Set‐Type Acidified Dairy Matrices of Different Composition and Microstructure by Means of the Concentration Profile Technique in Combination with Headspace Gas Chromatography

Heilig

Hahn

Erpenbach

et al. 2013

Journal of Texture Studies

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“…Preparation and Analysis of Flavored Model Dairy Matrices. Model dairy matrix production and K MG value determination were performed according to Heilig et al 15,16 Preparation of Flavored Model Dairy Matrices. Model milk solutions were composed of micellar casein powder (in-house production) and whey protein isolate powder (DSE 5627, Fonterra co-operative Group Ltd., Auckland, New Zealand) dissolved in reconstituted ultrafiltration permeate (Bayolan PT, BMI, Landshut, Germany).…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Determination of Aroma Compound Partition Coefficients in Aqueous, Polysaccharide, and Dairy Matrices Using the Phase Ratio Variation Method: A Review and Modeling Approach

Heilig

Sonne

Schieberle

et al. 2016

J. Agric. Food Chem.

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The partition of aroma compounds between a matrix and a gas phase describes an individual compound's specific affinity toward the matrix constituents affecting orthonasal sensory perception. The static headspace phase ratio variation (PRV) method has been increasingly applied by various authors to determine the equilibrium partition coefficient K in aqueous, polysaccharide, and dairy matrices. However, reported partition coefficients are difficult to relate and compare due to different experimental conditions, e.g., aroma compound selection, matrix composition, equilibration temperature. Due to its specific advantages, the PRV method is supposed to find more frequent application in the future, this Review aims to summarize, evaluate, compare, and relate the currently available data on PRV-determined partition coefficients. This process was designed to specify the potentials and the limitations as well as the consistency of the PRV method, and to identify open fields of research in aroma compound partitioning in food-related, especially dairy matrices.

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Interactions between aroma compounds and food matrix

Paravisini

Guichard

2016

Flavour

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Inherent and process-induced hydrophobicity influences aroma retention in fat-free dairy matrices

Cited by 9 publications

References 54 publications

Determination of Aroma Volatile Diffusion Coefficients in Set‐Type Acidified Dairy Matrices of Different Composition and Microstructure by Means of the Concentration Profile Technique in Combination with Headspace Gas Chromatography

Determination of Aroma Volatile Diffusion Coefficients in Set‐Type Acidified Dairy Matrices of Different Composition and Microstructure by Means of the Concentration Profile Technique in Combination with Headspace Gas Chromatography

Determination of Aroma Compound Partition Coefficients in Aqueous, Polysaccharide, and Dairy Matrices Using the Phase Ratio Variation Method: A Review and Modeling Approach

Interactions between aroma compounds and food matrix

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