Determination of Aroma Compound Partition Coefficients in Aqueous

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Review

Determination of aroma compound partition coefficients in aqueous, polysaccharide and dairy matrices using the Phase Ratio Variation (PRV) method: a review and modeling approach Andrej Heilig, Alina Sonne, Peter Schieberle, and Jorg Hinrichs J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b01482 • Publication Date (Web): 16 May 2016 Downloaded from http://pubs.acs.org on May 17, 2016

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Journal of Agricultural and Food Chemistry

Title: Determination of aroma compound partition coefficients in aqueous, polysaccharide and dairy matrices using the Phase Ratio Variation (PRV) method: a review and modeling approach

Andrej Heilig†, Alina Sonne†* Peter Schieberle‡, Jörg Hinrichs†

Affiliations: †

University of Hohenheim, Institute of Food Science and Biotechnology, Department

of Soft Matter Science and Dairy Technology, Garbenstrasse 21, 70599 Stuttgart, Germany ‡

Technical University of Munich, Department of Chemistry, Lise-Meitner-Strasse 34,

85354 Freising, Germany

Corresponding author: *Alina Sonne Tel.: +49 711 459 23616; fax: +49 711 459 23617. E-mail: [email protected]

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Abstract

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The partition of aroma compounds between a matrix and a gas phase describes the

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individual compounds specific affinity towards the matrix constituents affecting

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orthonasal sensory perception. The static headspace phase ratio variation (PRV)

5

method has been increasingly applied by various authors to determine the

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equilibrium partition coefficient K in aqueous, polysaccharide and dairy matrices.

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However, reported partition coefficients are difficult to relate and compare due to

8

different

9

composition, equilibration temperature. As due to its specific advantages, the PRV

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method is supposed to find more frequent application in the future, this review aimed

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to summarize, evaluate, compare and relate the currently available data on PRV

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determined partition coefficients. This process was designed to specify the potentials

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and the limitations, as well as the consistency of the PRV method, and to identify

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open fields of research in aroma compound partitioning in food-related, especially

15

dairy matrices.

experimental

conditions,

e.g.

aroma

compound

selection,

matrix

16 17

Keywords: dairy matrix, aroma-matrix interaction, hydrophobicity, log P, multiple

18

regression


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Introduction

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Distribution of aroma compounds in the headspace above food-related

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matrices under equilibrium conditions has been intensively studied in the past ten

22

years. Aroma concentration in the headspace enables an estimation of the

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prospective nasal and retronasal sensory perception during the consumption of food

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matrices.1-3 Several approaches exist towards the determination of aroma compound

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partition under equilibrium, and those most frequently used can be generally divided

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into dynamic and static headspace analysis methods. Techniques of dynamic

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headspace analysis, also known as “purge & trap” methodology, accumulate the

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analyte and hence offer high sensitivity, but require complex instrumentation that is

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susceptible to faults. Static headspace techniques utilize only a small fraction of the

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analyte and are therefore less sensitive, but very robust and easy to automate.

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Independent of the methodology used, some techniques require aroma compound

32

specific calibration and are referred to as “direct” techniques, while others are

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calibration independent and are hence called “indirect” techniques. Aroma compound

34

partition in aqueous, polysaccharide and dairy matrices has been investigated in

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numerous studies using the above techniques. However, the results obtained by

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various dynamic and static headspace analysis show a considerable lack of

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agreement.4,5 A review on the headspace analysis of aroma compounds has been

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given by Biniecka & Caroli.6

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Of late, the phase ratio variation (PRV) method, an indirect static headspace

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technique, has become increasingly popular to determine the aroma compound

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partition coefficient K.7-12 The PRV method has been explained in detail by Ettre,

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Welter & Kolb7, who showed that within certain boundaries, K can be ascribed to the

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relation of peak area A and phase ratio β.


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 1 c ME  1 = −  A cGE   f ⋅ c0

   ⋅ β  ⋅ f ⋅ c 0  

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K MG =

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where KMG is the matrix/gas partition coefficient, cME is the concentration of the

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analyte in the sample matrix phase, and cGE is the concentration of the analyte in the

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sample gas phase, i.e. the headspace of a closed vial under equilibrium conditions. A

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is the chromatographic peak area, f is a proportional factor, c0 is the initial aroma

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compound concentration in the matrix and β is the phase ratio of headspace volume

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VGE and matrix volume VME in the vial under equilibrium conditions.

(1)

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Rearranging Eq. (1) according to the experimentally assessable terms 1/A and

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β results in a linear relationship with (KMG/ (f*c0)) as the intercept and (1/(f*c0)) as the

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slope.

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1 =  K MG A  f ⋅c 0 

  1   +   ⋅ β   f ⋅ c0 

(2)

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KMG is then calculated from the ratio of the intercept and the slope. Inversion of

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the matrix/gas partition coefficient yields the gas/matrix partition coefficient KGM,

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which many studies report instead of the KMG.

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K GM =

1 K MG

(3)

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The main advantages of the PRV method are the calibration-free approach

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to K-value measurement, easy sample preparation, the high degree of analysis

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automation, the possibility to measure the partition coefficients of numerous

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compounds added together in the matrix during the same experiment (aroma


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compounds with distinct Kovats retention indexes), and good reproducibility. After

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comparison with other well-established static headspace techniques, Athes et al.4

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concluded that the PRV method offers the best compromise in terms of accuracy,

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reliability, and simplicity.

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Downsides of the PRV-method include restrictions in the determination of

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very large (> 102) and very small (< 10-2) K-values, which originates from the

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insufficient change in chromatographic peak area in both cases.13 In the case of

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highly viscous matrices, the transfer of exact volume of matrix can be challenging.

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However if the density is known, such matrices can be weighed instead as well.

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Furthermore, single K-values from linear regression are statistically less reliable

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than from non-linear regression, i.e. from the reciprocal function 1/A. This results in

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tighter and more reliable confidence intervals.14

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Past studies dealing with PRV-based K-value determination have used a

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wide variety of aroma compounds with different physico-chemical properties to

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determine the partition coefficient in water, as well as in polysaccharide and dairy

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matrices of different composition, and various data processing methods have been

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used. Despite its frequent application, a quantitative comparison of PRV-results

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obtained by different researches is not easy to perform, as matrix composition is

85

not defined and expressed in a uniform way, and partition coefficient analysis

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temperature varies. This complicates the use of past results and the identification

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of main parameters, potential correlations, as well as existing knowledge gaps in

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the PRV analysis of partition coefficients.

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In this context, it was the aim of this review to establish a K-value database

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that is relevant to dairy matrices and to identify future areas of research. Although

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this review is primarily concerned with the results of PRV-determined aroma

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compound partition, studies that have used other methods of analysis will be ACS Paragon Plus Environment

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mentioned, where appropriate. Statistic analysis was performed to derive

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equations that allow for the calculation of K-values depending on aroma

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compound and dairy matrix properties, as well as analytical conditions.

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Materials and methods

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Preparation and analysis of flavored model dairy matrices. Model dairy matrix

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production and KMG-value determination was performed according to Heilig et al.15,16

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Preparation of flavored model dairy matrices. Model milk solutions were

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composed of micellar casein powder (in-house production) and whey protein isolate

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powder (DSE 5627, Fonterra co-operative Group Ltd., Auckland, New Zealand)

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dissolved in reconstituted ultrafiltration permeate (Bayolan PT, BMI, Landshut,

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Germany). In-house produced cream and amidated low-methoxy pectin (CU-L

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082/07, Herbstreith & Fox, Neuenbürg, Germany) were added for the production of

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fat and hydrocolloid containing matrices. All solutions were batch pasteurized at 65

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°C with a holding time of 30 min. Subsequently, the solutions were cooled down to 10

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°C in ice water and then stored overnight at 4 °C. Resulting model milk matrices were

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then flavored with 1.0 % (w/w) of a commercial strawberry aroma from Symrise AG

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(Holzminden, Germany). Limonene and diacetyl, obtained from Symrise AG, were

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added to extend the log P range of the aroma compounds under investigation. Table

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1 lists the final composition of the propylene glycol based aroma. The pH of the final

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flavored model milk matrices was 6.75 ± 0.05.

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Model yoghurt systems were produced according to Krzeminski et al.17 Briefly,

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raw milk was separated, pasteurized (74 °C, 30 s), adjusted in protein content by

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using low heat skim milk powder (type Instant C, Schwarzwaldmilch GmbH,

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Offenburg, Germany) and fat content by using cream (in-house production),

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homogenized (65 °C, 15/3 MPa), heated in a tubular heat exchanger (95 °C, 5 min),

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cooled to 35 °C, fermented either with glucono-δ-lactone GDL (Art.-No. 49210, CAS

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604-69-3, Sigma-Aldrich, Munich, Germany) or with FD-DVS Yo-Flex® 812 (Chr.

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Hansen GmbH, Nienburg, Germany) at 35 °C to a pH of 4.4 – 4.2. Resulting set

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yoghurt gel was manually stirred while adding 1.0 % (w/w) of a commercial

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strawberry aroma from Symrise AG (Table 1).


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The degree of whey protein denaturation (DWPD) was determined by RP-

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HPLC.18 Own KMG-values, which have not been published by the authors in previous

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papers, are marked as such by an asterisk in Table 2.

127 128

Determination of the matrix/gas partition coefficient KMG. Vials containing

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flavored model milk matrices were equilibrated for 15 min at 40 °C in an automatic

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headspace sampler QHSS40 (QUMA Elektronik & Analytik GmbH, Wuppertal,

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Germany). The vials were gently agitated using the QHSS40 integrated shaker. After

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equilibration, 1 mL of vial headspace was automatically withdrawn at a valve

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temperature of 90 °C and a tube temperature of 150 °C. Headspace analysis was

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performed on a CP-3800 gas chromatograph (Varian Deutschland GmbH,

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Darmstadt, Germany), equipped with a split/splitless injector CP-1177 (240 °C) and a

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flame ionisation detector (250 °C, H2 28 mL min-1, synthetic air 300 mL min-1, N2 30

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mL min-1). For samples with 2 % fat, a split-ratio of 1:50 was used, and 1:20 for the

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higher fat contents. An HP-FFAP capillary column with an inner diameter of 0.32 mm,

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a film thickness of 0.25 µm and a length of 30 m (Agilent Technologies, Waldbronn,

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Germany), was used for chromatographic analysis. A deactivated silica-coated with

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an inner diameter of 0.53 µm and a length of 5 m served as pre-column. The carrier

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gas was H2 (2 mL min-1). The oven program started at 40 °C for 5 min, followed by

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heating up with 5 °C min-1 to 100 °C and 40 °C min-1 to 240 °C with a holding time of

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5 min.

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Vials containing model yoghurt systems were equilibrated at 40 °C for 30 min,

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and split-ratios of 1:50 and 1:20 were used for 0 % and 4 % fat, respectively. The

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determination of the matrix/gas partition coefficient KMG was performed by means of

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the phase ratio variation (PRV) method as described by Ettre, Welter, & Kolb7.

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Different volumes (50, 75, 100, 150, 200, 500, 1000, 2000 µL) of the flavored model

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dairy matrix were transferred into headspace vials of 22 mL (QUMA Elektronik &

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Analytik GmbH, Wuppertal, Germany). After filling, the vials were immediately sealed

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with PTFE septa in metallic caps (QUMA Elektronik & Analytik GmbH, Wuppertal,

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Germany).

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Transformation of dairy matrix and partition coefficient data from the

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literature. If not given as ppm (w/w) in the literature, the aroma concentration present ACS Paragon Plus Environment

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in the final product was calculated either from the molecular weight (if added as

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mol/L) or the specific gravity ρs (if added as µL/L) of the respective aroma compound

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(Table 2).

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Where the casein protein to whey protein ratio (CWR), the degree of whey

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protein denaturation (DWPD) and the lactose content in the analyzed dairy matrices

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have not been given explicitly, the following assumptions were made:

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For dairy matrices made (or reconstituted) from skim milk (powder) CWR =

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80:20, lactose content = protein content * 1.37 and ash content = protein content *

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0.21.19 Ash content in dairy matrices made from ultrafiltrated skim milk retentate was

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calculated as protein content * 0.11.20 For dairy matrices made from whole milk CWR

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= 80:20, lactose content = protein content * 1.43 and ash content = protein content *

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0.22. For skim and whole milk, protein contents of 3.50 and 3.33 were assumed,

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respectively. The DWPD was estimated according to Kessler19 from the time-

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temperature data of the (reconstituted) milk treatment given by the authors.

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In cases where the gas/matrix partition coefficient KGM instead of the KMGvalue was reported, KMG was obtained by simply inverting KGM according to Eq. (3).

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Statistics. The influence of aroma compound properties, dairy matrix

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composition and analytical conditions on the matrix/gas partition coefficient KMG was

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assessed by means of multiple regression using Statgraphics Plus Version 5.1

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(Statpoint Technologies Inc., Warrenton, USA).

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Results and discussion

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Review of literature data. Table 2 summarizes 375 experimental K-values

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that were published in 15 scientific papers, as well as 167 additional K-values

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determined by the review authors. K-values from the studies of other authors were ACS Paragon Plus Environment

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either taken from the depicted tables or extracted from figures if possible. 56 different

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aroma compounds have been investigated by means of the PRV method. They

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comprise a wide variety of chemical classes, including several aldehydes, ketones,

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carboxylic acids, esters, alcohols and terpenoids. In total, 542 data sets describe the

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aroma compounds partition between 90 different matrices and air at thirteen different

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equilibration temperatures that range from 4 to 80 °C. The reported 542 KMG-values

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range from as little as 2.67 to as much as 3.31 * 104 (Table 2, lines 1 and 52,

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respectively).

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Apart from pure water (95 data sets) and aqueous solutions or gels of

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polysaccharides (125 data sets), 40 differently composed dairy matrices with protein

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contents of 3.2 to 12.0 % (305 data sets on 11 levels), fat contents of 0.1 to 14.8 %

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(105 data sets on 9 levels), a CWR of 0.0 to 100 (305 data sets on 11 levels),

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thickener concentrations of 0.05 to 4.01 % (43 data sets on 3 levels), disaccharide

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concentrations of 4.3 to 12.5 % (305 data sets on 23 levels), ash contents of 0.49 to

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4.11 % (305 data sets on 25 levels), a DWPD of 2.7 to 99 % (303 data sets on 8

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levels) and pH values of 4.0 to 6.8 (305 data sets on 6 levels) have been analyzed

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for their aroma retentive capacity at aroma compound concentrations (ACC) from 1 to

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1000 ppm (w/w).

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Next to the investigated aroma compounds log P-value and vapor pressure,

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which are measurands of hydrophobicity and volatility, most studies list further aroma

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compound specific physico-chemical properties, such as molecular weight, boiling

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point, melting point, water solubility, specific gravity etc. Mostly, this is done without

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any apparent reason, as the named parameters are seldom used to explain the

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obtained analytic results. If the intention is to adequately specify the investigated

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compounds, which is highly recommended given the confusing multitude of

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sometimes conflicting trivial names that exist for one and the same compound, such ACS Paragon Plus Environment

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a specification should include the Chemical Abstracts Service (CAS) number. The

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CAS-No. is highly specific and even differentiates between the enantiomers of a

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compound.

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In Table 2 the CAS-No. is given together with the compounds molecular

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structure, as well as its log P-value, molecular mass (M), boiling point (BP) and

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saturated vapor pressure (pi0). These parameters were preferred over others,

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because they are considered to contain the most valuable information regarding the

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aroma compounds partition behavior and detectability, as it will be discussed later. If

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the reviewed studies did not list the CAS-No., the most likely number was selected

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after taking into account additional information and parameters that were provided by

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the respective authors.

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Regarding the above named physico-chemical parameters, the investigated

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compounds span log P values of -1.48 to +4.51 (Fig. 1 (A)), molecular masses of 41

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to 172, boiling points of -2 to 286 °C and vapor pressures of 0.00 to 1.20 * 103 hPa.

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In Table 2, the aroma compounds have been arranged in descending order

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according to their log P mean value. The log P mean value was calculated from the

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mostly inconsistent log P-values that are reported by various studies and databases.

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This was done because log P is an important parameter with regard to the retention

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of aroma compounds. The log P-value is seldom determined experimentally

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according to OECD guidelines21, but rather calculated by various software programs

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that use different QSPR-assumptions based on the methods of Rekker22 or Hansch &

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Leo23.

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Fig. 1 (B) displays the magnitude distribution of the 542 KMG-values listed in

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Table 2. As it is indicated by the dashed lines, 95 % of the values lie in between 1.01

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* 101 and 3.85 * 103, 90 % lie in between 1.55 * 101 and 2.33 * 103, and 75 % are

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located in between 2.56 * 101 and 8.89 * 102 (bordered by the outer, intermediate ACS Paragon Plus Environment

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and inner dashed lines, respectively). The fact that the outer 5 % of the partition

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coefficients comprise, in comparison to the majority of values, very low and very high

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KMG-values, will be a matter of discussion in the following sections.

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While log P influences the magnitude of the KMG-value in aqueous and fat

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containing matrices, it is rather unimportant with regard to compound detectability.

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The latter depends more on BP and pi0, which becomes obvious when summarizing

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the aroma compounds that could not be detected via static-HS-GC using a flame

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ionization detector (Table 3).

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When these mostly non-detectable compounds are compared with the ones

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listed in Table 2, their high boiling point and / or low saturated vapor pressure

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becomes obvious. However, KMG-values from ten of the 20 compounds listed in

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Table 3 have been reported by other authors. In the case of δ-decalactone, methyl

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cinnamate and vanillin, KMG-values are only given by Atlan et al.14 in water, while

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KMG-values for benzyl acetate and 3-methylbutanal have only been reported by

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Martuscelli et al.24 and Bylaite et al.25, respectively. The non-detectability of ethyl

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octanoate, linalool, octanal and diacetyl is most likely to be a combined result of low

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concentration, partly coupled with low equilibration temperature and highly aroma

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retentive matrices in the respective studies.

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When examining the physico-chemical properties of the aroma compounds

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listed in Table 2 and linking that information to the non-detectable compounds in

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Table 3, it appears that aroma compounds with a boiling point >> 200 °C at 1013

256

hPa and / or a saturated vapor pressure < 0.1 hPa at 25 °C are hard to detect via

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static-HS-GC using an FID-detector, for infinitely dilute solutions.7

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Regarding aroma compounds with elsewhere reported KMG-values, this would

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include decanoic acid, δ-decalactone, methyl cinnamate and vanillin. With these

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considerations in mind, the extremely high KMG-values for decanoic acid and vanillin ACS Paragon Plus Environment

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in water (3.31 * 104 and 3.19 * 103, Table 2, lines 52 and 439, respectively), as

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reported by Atlan et al.14, appear extraordinary, especially when taking into account

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the aroma compounds log P mean values of +4.09 and +1.20. The high KMG-values

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are most likely the result of the compounds low volatility (Table 3), not the one of

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actual retention in water.

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Modeling of KMG from literature data.

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Selection of model parameters. It is neither the obligation nor the aim of this

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review to derive the best possible or most plausible fit to the available data. Data

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fitting is neither a science nor a uniform process, and many goal-dependent

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approaches exist towards the multiple regression of large data sets.26 However, it is

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of great practical interest to determine to which degree the partition of aroma

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compounds can be forecasted from the available data. A potential application is the

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reformulation of aroma compositions in the dairy product development process.

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Accompanied by statistical analysis, a fitting attempt can furthermore help to extract

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experimental areas that are worth of future investigation, as well as questionable data

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sets, i.e. outliers in highly heterogeneous data.

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While Table 2 makes for an impressive set of experimentally determined KMG-

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values, which covers an exceptionally wide range of aroma compounds and

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differently composed matrices as well as analytic conditions, the multiple regression

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of these values is complicated to perform.

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First, the data to be fit must be defined. When plotting the listed log P-values

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according to their magnitude and frequency (Fig. 1 (A)), it becomes obvious that at

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both ends of the magnitude spectrum, relatively few values will execute a high, and

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probably misleading, influence on the fit.


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Second, the number of independent variables that are included in the model

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should be carefully observed and reduced to a well-considered minimum. Although

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an increased number of independent variables, i.e. fitting parameters, will always

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lead to an improved coefficient of determination (R²) value of the fit, the inclusion of

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insignificant parameters will also increase the residual mean square and hence the

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standard error of the estimate SEE, as well as the mean absolute error MAE.26 With

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regard to aromatized dairy matrices, a multitude of composition and process-related

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variables, and hence potential regression parameters, exist. These will be discussed

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in the following.

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Aroma compound physico-chemical properties. The included parameters

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should exert their effect on aroma compound partition founded preferably on

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fundamental physico-chemical interrelationships, such as the affinity for hydrophobic

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binding. Otherwise, such parameters will only obscure the principles that lie beneath

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the aroma compound-matrix interaction, and unnecessarily complicate the model.

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From the information summarized in Table 3, boiling point, as well as

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saturated vapor pressure pi0, must be respected as a regression parameter,

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especially in combination with the variety of applied equilibration temperatures listed

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in Table 2. Molecular mass can be neglected, as it is linearly correlated with boiling

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point BP (R2 of 0.80 for the present data set).

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Log P is a measure of aroma compound hydrophobicity / lipophilicity and

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numerous studies have shown its influence on aroma compound partition in a vast

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variety of matrices. While to some degree, log P is correlated with molecular mass,

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too, this is not for fundamental reasons. Both parameters’ relationship originates from

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the fact that a higher hydrophobicity, and hence a higher log P, greatly depends on

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the length of the aliphatic chain that forms part of most aroma compound molecules. ACS Paragon Plus Environment

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Still, a comparably “light” compound like limonene (molecular mass 136) can be

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exceptionally hydrophobic (mean log P = +4.51) if an aromatic ring is formed. Vice

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versa, an aroma compound with intermediate molecular mass, like diacetyl with 86,

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can be exceptionally hydrophilic (mean log P = -1.48). In the case of diacetyl, this is

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due to the ability of the molecules to form dimers and hydrogen bonds.27

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Aroma compound concentration (ACC). The thermodynamic principles, on

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which the determination of the partition coefficient is based, are only valid in ideal

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diluted solutions. In general, such a condition exists when the concentration of the

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volatile compound in the matrix does not exceed 0.1 %.13 Aroma compound

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concentrations in the reviewed literature range from 1 to 1000 ppm (w/w), i.e. 0.0001

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to 0.1 %, which means that aroma compound concentration can be neglected as a

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fitting parameter. In a comparative study that included several PRV operating

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parameters, Athes et al.4 found that at aroma compound concentrations of 20 to 50

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ppm (w/w), the compound specific K-values that were obtained at analyzing solutions

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that contained either a single or 15 different compounds were comparable.

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Consequently, the composition of aromatization can be neglected, too.

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Dairy protein content. Protein content can be considered to be the single most

331

important factor in the design of dairy matrix texture. An excellent review on the dairy

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protein-aroma compound interaction has been given by Kühn et al.28. Several studies

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have proved the aroma binding potential of milk proteins. Merabtine et al.29,

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Gierczynski et al.30 and Heilig et al.15 used the PRV method and reported an up to

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ten-fold, aroma compound dependent increase in retention at 4 to 12 % milk protein,

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as compared to aqueous solutions. Meynier et al.31 and Paçi-Kora et al.32 compared


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aroma retention in skim milk and water using other static HS methods, but with

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comparable results.

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The main component of dairy protein is casein, which effect was studied by

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Landy et al.33 and Fares et al.34 using sodium caseinate at concentrations from 0.5 to

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7.5 % (w/v). A higher caseinate content led to an aroma compound and caseinate

342

dependent retention (diacetyle, benzaldehyde, ethyl hexanoate) or release (diacetyl,

343

2-propanol) as determined by static and dynamic methods of HS-analysis. Acetone

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and ethyl acetate showed no change compared to water. Andriot et al.35 investigated

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different concentrations of β-lactoglobulin (0.5, 1, 2, 3, and 4 %), the second most

346

important protein in milk, and observed a higher retention as well as a lower odor

347

intensity of methyl ketones (2-heptanone, 2-octanone and 2-nonanone) at increased

348

β-lactoglobulin contents.

349

305 KMG-values, originating from 40 protein-containing matrices, are available

350

to assess the influence of protein content on aroma compound retention via multiple

351

regression.

352 353

Milk fat content / type. The contribution of milk fat to the flavor of dairy

354

products becomes increasingly important, although more because of its gradually

355

increasing absence in fat-reduced varieties rather than its presence. Flavor research

356

regarding the aroma compound fat interaction can be roughly distinguished into

357

works dealing with either the type of fat, the fat content, or the particle size

358

distribution (PSD) properties of the fat phase, as well as combinations thereof. With

359

regard to the assessment of milk fat influence, the PRV method has been applied by

360

Martuscelli et al.24, Deleris et al.36 and Benjamin et al.37, and for hydrophobic

361

compounds such as limonene, 500 times higher KMG-values in comparison to

362

aqueous solutions have been reported between fat contents of 0.5 % and 14.8 %. ACS Paragon Plus Environment

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363

The influence of fat type on aroma partition at equilibrium has been

364

investigated by Roberts et al.38, Relkin et al.39 and Benjamin et al.37. They found that

365

more hydrophobic aroma compounds are comparably less retained at higher shares

366

of solid fat, originating either from fat origin or equilibration temperature. Kopjar et

367

al.40 used standard and high melting AMF for PRV experiments with full-fat yoghurt,

368

but unfortunately only listed aroma retention relative to fat-free yoghurt instead of

369

absolute K-values. While high-melting AMF appeared to retain approximately 20 %

370

less ethyl acetate, ethyl butanoate and ethyl hexanoate than standard AMF, no other

371

dairy related PRV study has been concerned with the share of solid, i.e. high-melting

372

fractions in milk fat.

373

Independent of the type of fat investigated, i.e. paraffin oil1, sunflower oil41, soy

374

oil3,37, rapeseed oil2,42 ,coconut oil38, hydrogenated palm kernel oil39, hydrogenated

375

palm fat38, MCT-oil38,43, AMF31,36,37,39 or cream fat31,38,44, less hydrophobic aroma

376

compounds were either not affected or less retained. This means that the dairy

377

matrices were equally or more odorant at higher fat contents. Conversely, more

378

hydrophobic compounds had a higher retention (Table 4). The extent of increased

379

retention was found to be positively correlated with the aroma compounds

380

hydrophobicity as expressed by their log P-value.

381

Conflicting results are reported with regard to the particle size distribution of

382

the fat phase. Many factors such as fat type, fat content, aroma compound

383

hydrophobicity and equilibration temperature have been argued to explain this

384

variation.2,41,43

385

Table 2 lists 105 KMG-values that were determined in 26 fat-containing

386

matrices, and due to its well-known effect on aroma compound partition, fat content

387

was included as a fitting parameter. Due to the insufficient data base that is available


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388

on the influence of solid fat share and PSD, these two fat-associated parameters

389

were neglected.

390 391

Casein to whey protein ratio (CWR). With membrane filtration fractionation

392

techniques becoming the standard in dairy production processes, the CWR is of

393

increasing practical importance. Different ratios of casein protein to whey protein

394

have been investigated via the PRV method concerning the aroma partition above

395

milk protein solutions15 and stirred yoghurts.45,46

396

An increased share of micellar casein protein did not affect the partition of

397

diacetyl and ethyl hexanoate in solutions of 4 % protein, but caused a higher

398

retention of limonene, which was attributed to the hydrophobic core of the casein

399

micelle.15

400

In stirred yoghurt, most of the aroma compounds investigated by Saint-Eve et al.45

401

and Deleris et al.46 were more retained by addition of sodium caseinate than by whey

402

protein concentrate.

403

As already mentioned, a comprehensive review on the interaction of dairy

404

proteins and aroma compounds has been published by Kühn et al.28 Non-covalent as

405

well as covalent binding mechanisms exist, and their respective prevalence and

406

extent depends on the aroma compound properties, the protein functionality and the

407

composition of the aqueous environment. Given the variety in which both caseins and

408

whey proteins appear, such as native casein micelles, different caseinate salts, whey

409

protein isolates and concentrates etc., there is no such thing as “casein” and “whey

410

protein”. The often conflicting results regarding the aroma retention potential of both

411

fractions are likely to originate from these differences, which should be specified

412

accordingly. However, CWR has the potential to influence aroma partition, and 305


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413

data sets on 11 levels are available. Therefore, CWR was assessed as specified in

414

Table 2 and included as a fitting parameter.

415 416

Thickener content / type. Thickeners are routinely applied in a multitude of

417

dairy products, and especially in fat-reduced varieties, where they are intended to

418

contribute to texture formation. The effect of thickeners, i.e. polysaccharides such as

419

agar, carrageenan, cellulose, guar, locust bean, maltodextrin, pectin, starch, xanthan,

420

as well as their varieties, on aroma compound retention has been extensively studied

421

in protein-free, aqueous systems, as well as in dairy matrices. Studies mostly varied

422

the thickener concentration, and sometimes the salt content at constant contents of

423

ionic thickeners. In both cases not only the composition, but also the texture of the

424

aqueous solution changes.

425

PRV primary data are available from Bylaite et al.25, Savary et al.47, Deleris et

426

al.48, Lauverjat et al.5 and Merabtine et al.29 for proteinfree aqueous systems and

427

from Merabtine et al.23 for stirred yoghurt. In aqueous systems, it appears that as a

428

rule of thumb, retention sets in once the thickener concentration is high enough to

429

translate the viscous solution into a gel network49,often supported by the addition of

430

sucrose50, and that the extent of retention is positively correlated with aroma

431

compound hydrophobicity.51-53

432

Concerning dairy matrices it was found that depending on the concentration

433

and the presence of sucrose, thickeners can either increase or decrease the aroma

434

compound retention in stirred fat-free, but not in full-fat yoghurt54,55. A “salting-out”

435

effect has also been proposed.40,55 No thickener effect was seen in the non-acidified,

436

sucrose containing yoghurt base32, nor in fat-free and full-fat dairy custards.56

437

The general role of thickeners in the partition of aroma compounds is nearly

438

impossible to assess with reference to the literature, as the physico-chemical ACS Paragon Plus Environment

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439

properties of the investigated thickeners vary greatly from study to study, even within

440

one thickener type (i.e. high-methoxy, low-methoxy, amidated low-methoxy pectin),

441

and a multitude of additional matrix constituents complicate the comparison of

442

results. Regarding the various individual thickeners reported in Table 2, most of them

443

have not been sufficiently varied to respect them as single parameters in multiple

444

regression. The PRV-database contains 168 thickener-associated K-values on 12

445

levels of thickener content, and all water-binding polysaccharides were summarized

446

as thickeners. In order to assess whether and to which degree their addition results in

447

a directed change of the partition coefficient or not, thickener content was included as

448

a fitting parameter.

449

Disaccharide content. As it has already been stated, various studies contribute

450

a considerable effect on aroma partition to the presence of sucrose in thickened

451

aqueous systems. A 25 to 75 % decrease of ethyl acetate, ethyl hexanoate and n-

452

hexanol solubility in sucrose and maltodextrin solutions (30.0 to 57.5 %) as compared

453

to water has been reported by Covarrubias-Cervantes et al.57. A variation of the

454

sucrose content between 2.5 and 10 % in dairy custards had no effect on the

455

partition of various esters and aldehydes.58

456

Independent of additional sucrose, changes in the composition of a dairy

457

matrix, especially with regard to the protein and fat content, will always lead to a shift

458

in the concentration of disaccharides because of the inherent lactose, which has also

459

been suspected to cause a “salting-out” of ester aroma compounds.32 This shift

460

affects not only the overall disaccharide concentration, but even more so the

461

concentration in the aqueous phase. Because of the potential “salting-out” effect, the

462

disaccharide content should be included in modeling the matrix-aroma interaction.

463

Accordingly, the disaccharide content in PRV investigated matrices has been

464

calculated with reference to established protein to lactose coefficients. As a result, ACS Paragon Plus Environment

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465

Table 2 includes 423 KMG-values associated with disaccharide containing matrices

466

on 27 levels of disaccharide content.

467 468

Ash content. The addition of salts to aqueous solutions of aroma compounds

469

increases the compounds headspace concentration due to a “salting-out” effect.

470

Although this “salting-out” effect of salt on aroma compounds release is mainly

471

observed in aqueous solutions, it is also known to vary with compound

472

characteristics59, and has also been reported for β-lactoglobulin solutions.60 However,

473

in more complex matrices, salt can also be responsive of aroma compounds

474

retention since it induces proteins or polysaccharides structure modifications. As it is

475

the case with disaccharides, the salt concentration will inevitably change upon

476

modifications in the concentration of original dairy constituents, which should be

477

respected accordingly. Dairy matrix inherent salt, i.e. ash content, was therefore

478

calculated using the protein to ash ratios specified in Table 2, and there are 411 KMG-

479

values available to assess the potential “salting-out” effect of ash content on aroma

480

compound retention.

481 482

Degree of whey protein denaturation (DWPD). The kinetics of thermally

483

induced whey protein denaturation have been the subject of intense investigation and

484

were summarized for example by Kessler19. In dairy technology, the DWPD decides

485

over the gel forming properties during the manufacture of fermented milk products

486

such as yoghurt and cheese.20 It is therefore important to notice the results of

487

numerous studies, which have focused on the structure-property relationship with

488

regard to aroma compound binding by β-lactoglobulin.28 β-lactoglobulin is the by

489

quantity major dairy whey protein and its tertiary structure is lost upon heating, which

490

can result in increased or decreased binding, depending on the aroma compound ACS Paragon Plus Environment

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491

and the degree of denaturation.28 Perreault et al.61 used static HS-GC to determine

492

the aroma concentration above non-heated and 90 °C / 5 min heated skim milk as

493

well as acid gels made from it and reported an aroma compound dependent

494

influence of heating. It is important to note that acidified dairy matrices possess less

495

hydrophobic potential if made from milk with a high DWPD, as our own results have

496

shown.62 This could influence the retention of hydrophobic aroma compounds, and

497

with 303 available data sets on 8 levels, DWPD was included as a regression

498

parameter.

499 500

pH. The production of dairy products is often accompanied by a change

501

towards lower pH. Heilig et al.15 used PRV methodology to describe the effect of pH-

502

reduction, i.e. acidification, on aroma partition in fat-free dairy matrices. Hydrophilic

503

diacetyl was less retained in acidified matrices, while hydrophobic aroma compounds

504

were rather unaffected, which is in accordance with the results of Paçi-Kora et al.32,

505

Leksrisompong et al.3 and Perreault et al.61

506

Heilig et al.15 attributed this behavior to increased matrix hydrophobicity at acid

507

pH. In aqueous solutions of β-lactoglobulin, acid pH was also shown to decrease

508

aroma compound retention, due to changes in β-lactoglobulin tertiary structure.63,64

509

Given the potential synergistic or antagonistic effects with DWPD via the hydrophobic

510

binding of proteins, pH (542 available data sets on 8 levels) was included as a fitting

511

parameter.

512 513

Equilibration temperature (ϑ). The saturated vapor pressure, and hence the

514

distribution of an aroma compound between two media, is temperature-dependent.

515

Saturated vapor pressure at different temperatures can be calculated according to

516

the Antoine equation. Using such conversions, Kopjar et al.40 reviewed the effect of ACS Paragon Plus Environment

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Page 22 of 66

517

temperature on aroma partition in dairy relevant food matrices. The temperature-

518

dependence of aroma compound K-values, determined via the PRV method, has

519

been investigated in aqueous matrices with and without added thickeners within a

520

temperature range of 10-80 °C.47,52 As expected, Arrhenius-plots showed a linear

521

dependency of ln K vs. 1/T.

522

Meynier et al.31, Roberts et al.38 and Nongonierma et al.54 used static-HS

523

methods to determine the aroma partition in fat-free and fat-containing dairy matrices

524

between 4 and 80 °C. The temperature-dependent change in retention was more

525

pronounced in fat-containing matrices than in fat-free matrices attributed to the share

526

of solid fat at a given temperature. The retention was lower at higher temperatures

527

and the change in fat-containing matrices was larger. This is because the proportion

528

of solid fat decreases at higher temperatures and the retention of aroma compounds

529

decreases.

530

As equilibration temperature not only governs the aroma compounds vapor

531

pressure, but also influences the solid to liquid ratio of milk fat, it is an essential

532

parameter in the assessment of aroma partition. The thirteen equilibration

533

temperatures summarized in Table 2 vary from as little as 4 °C to as much as 80 °C.

534 535

Texture. Dairy matrices do not only differ in composition, but due to process

536

technology operations, in texture, too. Texture is known to greatly influence aroma

537

perception during the consumption of dairy products.31 PRV studies that considered

538

the effect of texture on aroma compound equilibrium partition include those of Bylaite

539

et al.25, Saint-Eve et al.45, Gierczynski et al.30 and Deleris et al.46 In pectin thickened

540

aqueous solutions, there was no influence of viscosity on levels up to 1000 times the

541

viscosity of water.25 Gierczynski et al.30 found no influence of model fresh-cheese gel

542

hardness on aroma partition at equilibrium, and similar observations were made by ACS Paragon Plus Environment

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543

Saint-Eve et al.45 and Deleris et al.46 regarding the viscosity of full-fat stirred

544

yoghurts.

545

measured at the thermodynamic equilibrium and reflect the affinity of aroma

546

compounds with the matrix i.e. interactions with matrix ingredients. Thus, it was

547

expected that texture affects the kinetic of the release in the headspace and could be

548

evaluated through diffusion or transfer coefficients. One should distinguish two

549

phenomena: on the one hand, the binding of aroma compounds with pectin (effect at

550

equilibrium) and on the other hand, the increase in viscosity inducing a decrease in

551

the time to reach equilibrium. However, because most food, and especially dairy

552

matrices, show non-newtonian, shear thinning behavior, it is not possible to

553

determine absolute viscosities. The methodology dependent apparent viscosities

554

given in the literature are by no means comparable and cannot be used for

555

regression purposes. Therefore, texture parameters were neglected for the modeling

556

of K-values.

It is generally assumed in the literature that partition coefficients are

557

The above summarized information shows that a considerable effect on aroma

558

compound partition can be expected from the log P, BP and pi0 on the aroma

559

compound side, the protein, fat, thickener, disaccharide and ash content, as well as

560

CWR, DWPD and pH on the matrix side, and equilibration temperature on the

561

analytical side. All these parameters have been sufficiently varied and interaction

562

effects between some of them are likely. The direction and extent to which these

563

parameters influence aroma partition depends on the aroma compounds and dairy

564

constituents physico-chemical properties. Therefore, they were chosen as fitting

565

parameters.

566 567

Modeling all matrices. An undifferentiated modeling approach, which only

568

excludes the anomalous KMG-values reported for decanoic acid and vanillin (Table 2, ACS Paragon Plus Environment

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Page 24 of 66

569

lines 52 and 439, respectively) for the reasons explained above, results in a

570

regression model with an R2 of 0.44 (SEE = 1078, MAE = 579, i = 540). As it can be

571

seen from the plot of observed versus predicted KMG-values (Fig. 2 (A)), only a

572

handful of KMG values > 5000 exerts a disproportional influence on the fit. Excluding

573

the smallest and the largest 2.5 % of the KMG-values listed in Table 2 improves the fit

574

to an R2 of 0.53 (SEE = 466, MAE = 306, i = 512; Fig 2 (B)).

575

Both diacetyl and limonene15,16 were shown to demonstrate anomalous

576

partition behavior in dairy matrices. After excluding these two by far most hydrophilic

577

and hydrophobic aroma compounds (Fig. 1 (A)) from the model, and excluding the

578

smallest and the largest 2.5 % of the remaining 433 KMG-values, an R2 of 0.69 is

579

obtained (SEE = 263, MAE = 167, i = 411; Fig. 3). However, the partition of both

580

diacetyl and limonene will be discussed separately further below (see Chapter

581

Modeling selected aroma compounds).

582

As it has been stated initially, it is not the aim of this review to establish the

583

best probable fit. With respect to the available data base, and the wide range of

584

experimental conditions covered, the fitting attempts presented here intend to

585

investigate to which degree a satisfactory forecast of PRV-determined partition

586

coefficients is possible, and if the K-values that were reported by numerous

587

researchers are coherent.

588 589

Modeling selected matrices. The above fittings, which included all

590

constituents alike, might be considered as too comprehensive. A more specific point

591

of view could distinguish three principally different types of matrices, namely protein

592

and fat-free aqueous solutions, such as milk permeate, as well as protein-containing

593

matrices with and without milk fat. Separate processing of the partition coefficient

594

data that is available on these fundamentally different matrices can help to correctly ACS Paragon Plus Environment

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Page 25 of 66


595

assess the influence of the compositional parameters that define them. In Table 2,

596

the available data has already been arranged accordingly by empty lines within the

597

single aroma compounds.

598

As it is well known from previous research, some dairy constituents impose

599

more effect on aroma compound retention than others. Examination of the KMG-data

600

listed in Table 2 shows that for most of the investigated aroma compounds, three

601

levels of magnitude exist. These levels correspond to protein- and fat-free matrices,

602

protein containing but fat-free matrices, and protein- and fat-containing matrices. The

603

KMG difference between these levels is approximately one decade, i.e. increasing

604

from 1-10 to 10-100 and 100-1000 with increasing matrix complexity, as it is the case

605

for example for limonene (Table 2, lines 1-40). Changes in the constituent

606

composition of less complex matrices, which would probably have a considerable

607

influence on aroma compound retention in the latter, are likely to be underestimated if

608

KMG-data is modeled without respect to matrix complexity.

609 610

Protein- and fat-free matrices. Multiple regression of protein- and fat-free

611

matrices, i.e. matrices that only contain thickeners and / or disaccharides or ash

612

constituents, results in an R2 of 0.26 (SEE = 354, MAE = 197, i = 235; Fig. 4 (A)).

613

Neglecting limonene and diacetyl, as well as the upper and lower 2.5 % of the

614

remaining KMG-values, leads to an R² of 0.49 (SEE = 95.6, MAE = 63.8, i = 201; Fig.

615

4 (B)). In both cases, protein and milk fat content, as well as CWR and DWPD, were

616

not included as fitting parameters.

617 618

Protein-containing, fat-free matrices. If only matrices that contain protein, but

619

no fat, are respected, the multiple regression yields an R2 of 0.34 (SEE = 522, MAE =

620

257, i = 200; Fig. 5 (A)). Neglecting limonene and diacetyl, as well as the upper and ACS Paragon Plus Environment

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Page 26 of 66

621

lower 2.5 % of the remaining KMG-values, leads to an R2 of 0.50 (SEE = 119, MAE =

622

71.9, i = 139; Fig. 5 (B)).

623 624

Protein- and fat-containing matrices. Multiple regression of matrices that

625

contain both protein and fat results in an R2 of 0.44 (SEE = 1632, MAE = 1062, i =

626

105; Fig. 6 (A)). In diacetyl and limonene are excluded from the model, as well as the

627

upper and lower 2.5 % of the remaining KMG-values, an R2 of 0.78 (SEE = 845, MAE

628

= 574, i = 71; Fig. 6 (B)) is obtained.

629 630

Other than expected, the regression of the individual matrix types does not

631

lead to an improved R2, except for the protein- and fat-containing matrices. What is

632

more important, however, is the fact that both the SEE and the MAE are smaller for

633

the protein- and fat-free matrices, as well as for the protein-containing, fat-free

634

matrices. Given the lower magnitude of the respective KMG-values compared to

635

protein- and fat-containing matrices, this results in a more accurate forecast of the

636

partition coefficient.

637 638

Modeling selected aroma compounds. The neglect of diacetyl and

639

limonene, the by far most hydrophilic and hydrophobic compounds, considerably

640

improved the correlation coefficients of the above models, and decreased the error of

641

the estimates. As it will be seen below, this is not due to a lack of consistent data

642

concerning these two compounds, but a result of deviating behavior due to extreme

643

log P-values. This becomes evident when diacetyl and limonene are fitted separately.

644

For the regression of the single aroma compounds, log P, BP, and pi0 were not used

645

as fitting parameters.

646 ACS Paragon Plus Environment

26

Page 27 of 66

647 648


Diacetyl. Multiple regression of all available diacetyl KMG-values gives an R2 of 0.75 (SEE = 1017, MAE = 612, i = 56; Fig. 7).

649 650

Limonene. If the available limonene KMG-data is processed via multiple

651

regression, this results in an R2 of 0.98 (SEE = 55.6, MAE = 31.6, i = 51; Fig. 8). In

652

order to extent the validity of the model, both limonene varieties listed in Table 2

653

were used for the regression. It has to be mentioned that the high correlation

654

coefficient is of only limited significance, as 40 of the 51 KMG-values used for the

655

regression originate from the authors of this review. Consequently, the variability in

656

experimental conditions is very small, which reduces the respective spread.

657 658

Ethyl hexanoate. Ethyl hexanoate is the aroma compound for which the most

659

PRV determined K-values are available. It has been investigated over an

660

exceptionally wide range of parameter settings in ten different studies (Table 2), and

661

with a mean log P of +2.82, it does not show extreme physico-chemical properties.

662

Ethyl hexanoate therefore serves as a good indicator of PRV-data comparability.

663

Multiple regression of the available ethyl hexanoate KMG-values results in an R2 of

664

0.92 (SEE = 201.8, MAE = 98.3, i = 69; Fig. 9).

665

The improvement in R2, that was observed in undifferentiated modeling after

666

the neglect of diacetyl and limonene, was hence not due to a lack of consistent data

667

regarding these two aroma compounds. The problem most likely arouses from the

668

fact that these compounds, which are both located at the far end of the log P

669

spectrum (Fig. 1 (A)), show different matrix interaction mechanisms than the rest of

670

the investigated aroma compounds. In looking at Table 2, it becomes obvious that in

671

between a mean log P of +3.14 (linalool) and +4.48 to +4.51 (limonene), nearly no

672

dairy matrix relevant KMG-values are available. The same is true for the log P range ACS Paragon Plus Environment

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Page 28 of 66

673

of +0.72 (ethyl acetate) to -1.48 (diacetyl). These large gaps in one of the most

674

important physico-chemical parameters impede the creation of a uniform KMG

675

calculation model over the full range of log P-values.

676 677

Multiple regression of aroma compound partition coefficient values showed

678

that the available data, which originates from various, independently acting research

679

groups and was collected under highly different experimental conditions, is consistent

680

over a wide range of parameter settings. As the single-compound approach to KMG-

681

data modelling has shown, the PRV determined partition properties in aqueous,

682

polysaccharide and dairy matrices can be very well described. The PRV method

683

delivers reliable results that, although originating from substantially different studies,

684

can be processed via multiple regression using a limited number of independent

685

variables.

686

In which way, and to which extent, statistic procedures, such as forward or

687

backward elimination of parameters and potential outliers, can and should be used to

688

improve the accuracy of the fitted model and the forecast values, largely depends on

689

the goal and the subjects of the multiple regression. As it has been stated by

690

Piggott26, multiple regression is an art, not a science, and it is largely in the hands of

691

the user to exploit the data that was collected for this review.

692

However, future investigations should focus on a more systematic increase in

693

the complexity of the matrix. The majority of past PRV studies either dealt with

694

comparably simple, i.e. pure water, or highly complex matrices, i.e. polysaccharide

695

mixtures and dairy matrices composed of protein, fat, thickeners and added sucrose.

696

It was then tried to interpret the results based on earlier research, which was

697

predominantly concerned with single polysaccharide or protein constituents in water.

698

Although food research studies are often driven by the intention for industrial ACS Paragon Plus Environment

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Page 29 of 66


699

application, researchers are encouraged to underlay their results on highly complex,

700

industry relevant matrices, with accompanying experiments that involve the single

701

constituents, probably by making use of adequate experimental designs. This would

702

greatly contribute to the understanding of the matrix constituent-aroma compound

703

interaction on a physico-chemical basis. In such supporting studies, more efforts

704

should be made to unmistakeably characterize the raw materials.

705

In the case of polysaccharide matrices, this would include, among other

706

polysaccharide-type specific parameters, the viscosity, the zeta-potential, the overall

707

ash content as well as the individual ion composition. In the case of protein-

708

containing matrices, next to dry matter and overall protein content, the pH in water,

709

the particle size in solution, the DWPD, the overall ash content and the process

710

history of the, mostly powdered, raw material should be specified. Only if the matrix

711

constituents are better specified, highly elaborated quantitative structure property

712

relationships (QSPR) as presented by Tromelin et al.65 for polysaccharide matrices

713

and Tromelin & Guichard66 for β-lactoglobulin, can unfold their potential in more

714

practical applications. In order to increase the reliability of KMG-value forecasts, a

715

sufficiently variable data pool is necessary, and so far does not exist for the majority

716

of the analysed aroma compounds. If the aroma retentive capacity of the matrix

717

constituents or of the matrix structure, and not the matrix’ sensory properties, are the

718

subject of aroma compound partition research, it is therefore recommended to

719

incorporate as many aroma compounds into the matrix as analytically feasible. These

720

compounds should be selected with especial regard to their log P-values and their

721

aroma contribution properties. More data is needed especially in the log P range of -

722

1.5 to +1.0 and +3.0 to +4.5. A recent study reveals partition coefficients for aroma

723

compounds within a log P range of +3.0 to +4.5 in water and in acacia gum

724

solutions.67 Moreover, the authors have distinguished the affinity of aroma ACS Paragon Plus Environment

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Page 30 of 66

725

compounds for water (solubility) from the affinity for the lipid phase (log P). This

726

original approach made possible to understand the retention phenomena in

727

polysaccharide solution and could be applied to dairy matrices as well.

728

Furthermore, as it is seen from both Fig. 1 (B) and the observed versus

729

predicted plots displayed above, more KMG-values in the < 50 and the > 500 range

730

are needed. Future studies should both improve and adjust the experimental

731

conditions that allow for the determination of partition coefficients of this magnitude,

732

especially regarding the optimization of the phase ratio β and the application of

733

different equilibration temperatures.

734

It is also recommended that results of KMG-value determination are not only be

735

presented as retention ratios relative to a reference matrix, as it is the case in some

736

studies15,37,40,52, but also tabulated, which would further extend the available data

737

base. We furthermore agree with Kühn et al.28, that in order to elevate the practical

738

value of the results, future PRV studies should aim to connect their results to

739

orthonasal sensory analysis. This could be achieved by descriptive sensory analysis

740

or at least triangle testing. Triangle testing can be easily performed on selected

741

matrices that are aromatised with only a single compound, using combinations that

742

showed considerable changes in the KMG-value. However, it must be checked that

743

non-aromatised matrices of varying composition are not recognised as different due

744

to their inherent aroma profile.

745 746

Abbreviations used

747

PRV, phase ratio variation; RP-HPLC, reverse phase high performance liquid

748

chromatography; DWPD, degree of whey protein denaturation; CWR, casein protein

749

to whey protein ratio; ACC, aroma compound concentration; CAS, chemical abstract

750

service;

BP,

boiling

point;

M,

molecular

mass;


HS-GC,

headspace-gas 30

Page 31 of 66


751

chromatography; FID, flame ionization detector; SEE, standard error of estimation;

752

MAE, mean absolute error; PSD, particle size distribution; AMF, anhydrous milk fat;

753

MCT, medium chain triglyceride

754 755

Acknowledgments

756

The authors thank Bernd Köhlnhofer from Zott SE & Co. KG and Katja Buhr from

757

SGS Institute Fresenius Austria GmbH for the close cooperation within this research

758

project on the aroma-dairy matrix interaction.

759 760 761 762

Author information

763

Corresponding author

764

*Dr. Alina Sonne. Tel: +49 711 459 23616. Fax: +49 711 459 23617.

765

E-mail: [email protected]

766

Funding

767

This

768

Ernährungsindustrie e.V., Bonn), the AiF and the Ministry of Economics and

769

Technology. AiF-Project No.: 15158 N.

770

Notes

771

The authors declare no competing financial interest.

research

project

was

supported

by

the

FEI

(Forschungskreis

der

772 773


31


774

Page 32 of 66

References

775 776

(1) Guyot, C.; Bonnafont, C.; Lesschaeve, I.; Issanchou, S.; Voilley, A.; Spinnler, H.E. Effect of fat

777

content on odor intensity of three aroma compounds in model emulsions: δ-decalactone, diacetyl, and

778

butyric acid. J. Agric. Food Chem. 1996, 44, 2341-2348.

779

(2) Miettinen, S.M.; Tuorila, H.; Piironen, V.; Vehkalahti, K.; Hyvönen, L. Effect of emulsion

780

characteristics on the release of aroma as detected by sensory evaluation, static headspace gas

781

chromatography, and electronic nose. J. Agric. Food Chem. 2002, 50, 4232-4239.

782

(3) Leksrisompong, P.; Barbano, D. M.; Foegeding, A.E.; Gerard, P.; Drake, M. The roles of fat and pH

783

on the detection thresholds and partition coefficients of three compounds: diacetyl, δ-decalactone and

784

furaneol. J. Sens. Stud. 2010, 25, 347-370.

785

(4) Athes, V.; Peña y Lillo, M.; Bernard, C.; Pérez-Correa, R.; Souchon, I. Comparison of experimental

786

methods for measuring infinite dilution volatilities of aroma compounds in water/ethanol mixtures. J.

787

Agric. Food Chem. 2004, 52, 2021-2027.

788

(5) Lauverjat, C.; Loubens, C. de; Déléris, I.; Tréléa, I.C.; Souchon, I. Rapid determination of partition

789

and diffusion properties for salt and aroma compounds in complex food matrices. J. Food. Eng. 2009,

790

93, 407-415.

791

(6) Biniecka, M. & Caroli, S. Analytical methods for the quantification of volatile aromatic compounds.

792

Trends Anal. Chem. 2011, 30, 1756-1770.

793

(7) Ettre, L.S.; Welter, C.; Kolb, B. Determination of gas-liquid partition coefficients by automatic

794

equilibrium

795

Chromatographia 1993, 35, 73-84.

796

(8) Robbins, G.A.; Wang, S.; Stuart, J.D. Using the static headspace method to determine Henry’s

797

Law constants. Anal. Chem. 1993, 65, 3113-3118.

798

(9) Dewulf, J.; van Langenhove, H.; Everaert, P. Determination of Henry's law coefficients by

799

combination of the equilibration partitioning in closed systems and solid-phase microextraction

800

techniques. J. Chromatogr A. 1999, 830, 353-363.

801

(10) Welke, B.; Ettlinger, K.; Riederer, M. Sorption of volatile organic chemicals in plant surfaces.

802

Environ. Sci. Technol. 1998, 32, 1099-1104.

headspace-gas

chromatography

utilizing

the

phase


ratio

variation

method.

32

Page 33 of 66


803

(11) Helburn, R.; Albritton, J.; Howe, G.; Michael, L.; Franke, D. Henry’s law constants for fragrance

804

and organic solvent compounds in aqueous industrial surfactants. J. Chem. Eng. Data 2008, 53, 1071-

805

1079.

806

(12) Lloyd, N.W.; Dungan, S.R.; Ebeler, S.E. Measuring gas-liquid partition coefficients of aroma

807

compounds by solid phase microextraction, sampling either headspace or liquid. Analyst 2011,

808

136(16), 3375-3383.

809

(13) Kolb, B., & Ettre, L.S. Static headspace-gas chromatography. Theory and practice 2006, pp. 19-

810

50. Hoboken: John Wiley & Sons.

811

(14) Atlan, S.; Trelea, I.C.; Saint-Eve, A.; Souchon, I.; Latrille, E. Processing gas chromatographic

812

data and confidence interval calculation for partition coefficients determined by the phase ratio

813

variation method. J. Chrom. A. 2006, 1110, 146-155.

814

(15) Heilig, A.; Çetin, S.; Erpenbach, K.; Höhn, J.; Hinrichs, J. Inherent and process-induced

815

hydrophobicity influences aroma retention in fat-free dairy matrices. Int. Dairy J. 2011, 21, 696-702.

816

(16) Heilig, A.; Heimpel, K.; Sonne, A.; Schieberle, P.; Hinrichs, J. An approach to adapt aroma in fat-

817

free yoghurt systems: modelling and transfer to pilot scale. Int. Dairy J. 2016, 65, 101-107.

818

(17) Krzeminski, A.; Großhable, K.; Hinrichs, J. Structural properties of stirred yoghurt as influenced by

819

whey proteins. LWT-Food Sci. Technol. 2011, 44(10), 2134–2140.

820

(18) ISO 13875:2005 (IDF 178:2005). Liquid milk - Determination of acid-soluble beta-lactoglobulin

821

content - Reverse-phase HPLC method.

822

(19) Kessler, H.G. Food and Bio Process Engineering – Dairy Technology. 2002, p. 639. München:

823

Verlag A. Kessler.

824

(20) Walstra, P.; Wouters, J.T.M.; Geurts, T.J. (2006). Dairy science and technology. 2006, pp. 341-

825

356. Boca Raton: CRC Press.

826

(21) OECD Guidelines for the testing of chemicals. http://www.oecd-ilibrary.org/environment/oecd-

827

guidelines-for-the-testing-of-chemicals-section-1-physicalchemical-properties_20745753

828

09/02/2016).

829

(22) Rekker, R. F. The hydrophobic fragmental constant. 1977. New York: Elsevier.

830

(23) Hansch, C. & Leo, A.J. Substituent constants for correlation analysis in chemistry and biology.

831

1979. p. 352, New York: John Wiley & Sons.

832

(24) Martuscelli, M.; Savary, G.; Pittia, P.; Cayot, N. Vapour partition of aroma compounds in

833

strawberry flavoured custard cream and effect of fat content. Food Chem. 2008, 108, 1200-1207.


(Accessed

33


Page 34 of 66

834

(25) Bylaite, E.; Meyer, A.S.; Adler-Nissen, J. Changes in macroscopic viscosity do not affect the

835

release of aroma aldehydes from a pectinaceous food model system of low sucrose content. J. Agric.

836

Food Chem. 2003, 51, 8020-8026.

837

(26) Piggott, J.R. Statistical procedures in food research. 1986, pp. 61-100. London: Elsevier.

838

(27) Hinrichs, J. & Schieberle, P. Interaktion von Aromastoff und Milchproduktmatrix. [Interaction of

839

aroma compound and milk product matrix.] 2010. AiF-Project 15158 N.

840

(28) Kühn, J.; Considine, T.; Sing, H. Interactions of milk proteins and volatile flavour compounds:

841

implications in the development of protein foods. J. Food Sci. 2006, 71, 72-82.

842

(29) Merabtine, Y.; Lubbers, S.; Andriot, I.; Tromelin, A.; Guichard, E. Retention/release equilibrium of

843

aroma compounds in fat-free dairy gels. J. Sci. Food Agr. 2010, 90, 1403-1409.

844

(30) Gierczynski, I.; Labouré, H.; Sémon, E.; Guichard, E. Impact of hardness of model fresh cheese

845

on aroma release: in vivo and in vitro study. J. Agric. Food Chem. 2007, 55, 3066-3073.

846

(31) Meynier, A.; Garillon, A.; Lethuaut, L.; Genot, C. Partition of five aroma compounds between air

847

and skim milk, anhydrous milk fat or full-fat cream. Lait, 2003, 83, 223-235.

848

(32) Paçi-Kora, E.; Souchon, I.; Latrille, E.; Martin, N.; Marin, M. Composition rather than viscosity

849

modifies the aroma compound retention of flavored stirred yogurt. J. Agric. Food Chem. 2004, 52,

850

3048-3056.

851

(33) Landy, P.; Druaux, C.; Voilley, A. Retention of aroma compounds by proteins in aqueous solution.

852

Food Chem. 1995, 54, 387-392.

853

(34) Fares, K.; Landy, P.; Guilard, R.; Voilley, A. Physicochemical interactions between aroma

854

compounds and milk proteins: Effect of water and protein modification. J. Dairy Sci. 1998, 81, 82-91.

855

(35) Andriot, I.; Harrison, M.; Fournier, N.; Guichard, E. Interactions between methyl ketones and β-

856

lactoglobulin: Sensory analysis, headspace analysis, and mathematical modeling. J. Agric. Food

857

Chem. 2000, 48, 4246-4251.

858

(36) Deleris, I.; Zouid, I.; Souchon, I.; Trelea, I.C. Calculation of apparent diffusion coefficients of

859

aroma compounds in dairy emulsions based on fat content and physicochemical properties in each

860

phase. J. Food. Eng. 2009, 94, 205-214.

861

(37) Benjamin, O.; Leus, M.; Everett, D.W. Static headspace analysis of volatile compounds released

862

from β-lactoglobulin-stabilized emulsions determined by the phase ratio variation method. Food Res.

863

Int. 2011, 44, 417-424.


34

Page 35 of 66


864

(38) Roberts, D.D.; Pollien, P.; Watzke, B. Experimental and modeling studies showing the effect of

865

lipid type and level on flavor release from milk-based liquid emulsions. J. Agric. Food Chem. 2003, 51,

866

189-195.

867

(39) Relkin, P.; Fabre, M.; Guichard, E. Effect of fat nature and aroma compound hydrophobicity on

868

flavor release from complex food emulsions. J. Agric. Food Chem. 2004, 52, 6257-6263.

869

(40) Kopjar, M.; Andriot, I.; Saint-Eve, A.; Souchon, I.; Guichard, E. Retention of aroma compounds:

870

An interlaboratory study on the effect of the composition of food matrices on thermodynamic

871

parameters in comparison with water. J. Sci. Food Agr. 2010, 90, 1285-1292.

872

(41) Van Ruth, S.M.; King, C.; Giannouli, P. Influence of lipid fraction, emulsifier fraction, and mean

873

particle diameter of oil-in-water emulsions on the release of 20 aroma compounds. J. Agric. Food

874

Chem. 2002, 50, 2365-2371.

875

(42) Haahr, A.M.; Bredie, W.L.P.; Stahnke, L.H.; Jensen, B.; Refsgaard, H.H.F. Flavour release of

876

aldehydes and diacetyl in oil/water systems. Food Chem. 2000, 71, 355-362.

877

(43) Weel, K.G.C.; Boelrijk, A.E.M.; Burger, J.J.; Jacobs, M.A.; Gruppen, H.; Vorhagen, A.G.J.; Smit,

878

G. Effect of emulsion properties on release of esters under static headspace, in vivo, and artificial

879

throat conditions in relation to sensory intensity. J. Agric. Food Chem. 2004, 52, 6572−6577.

880

(44) Heilig, A.; Hahn, C.; Erpenbach, K.; Kübler, K.; Hinrichs, J. Determination of aroma volatile

881

diffusion coefficients in set-type acidified dairy matrices of different composition and microstructure by

882

means of the concentration profile technique in combination with headspace gas chromatography. J.

883

Texture Stud., 2003, 44(6), 436-449.

884

(45) Saint-Eve, A.; Juteau, A.; Atlan, S.; Martin, N.; Souchon, I. Complex viscosity induced by protein

885

composition variation influences the aroma release of flavored stirred yogurt. J. Agric. Food Chem.

886

2006, 54, 3997-4004.

887

(46) Deleris, I.; Lauverjat, C.; Trelea, I.C.; Souchon, I. Diffusion of aroma compounds in stirred yogurts

888

with different complex viscosities. J. Agric. Food Chem. 2007, 55, 8681-8687.

889

(47) Savary, G.; Guichard, E.; Doublier, J.L.; Cayot, N. Mixture of aroma compounds: Determination of

890

partition coefficients in complex semi-solid matrices. Food Res. Int. 2006, 39, 372-379.

891

(48) Deleris, I.; Atlan, S.; Souchon, I.; Marin, M.; Trelea, I.C. An experimental device to determine the

892

apparent diffusivities of aroma compounds. J. Food. Eng. 2008, 85, 232-242.

893

(49) Hollowood, T.A.; Linforth, R.S.T.; Taylor, A.J. The effect of viscosity on the perception of flavour.

894

Chem. Senses, 2002, 27, 583-591.


35


Page 36 of 66

895

(50) Hansson, A.; Leufvén, A.; Pehrson, K.; Stenlöf, B. Multivariate analysis of the influence of pectin,

896

white syrup, and citric acid on aroma concentration in the headspace above pectin gels. J. Agric. Food

897

Chem. 2002, 50, 3803- 3809.

898

(51) Philippe, E.; Seuvre, A.M.; Colas, B.; Langendorff, V.; Schippa, C. Behavior of flavor compounds

899

in model food systems: a thermodynamic study. J. Agric. Food Chem. 2003, 51, 1393-1398.

900

(52) Jouquand, C.; Ducruet, V.; Giampaoli, P. Partition coefficients of aroma compounds in

901

polysaccharide solutions by the phase ratio variation method. Food Chem. 2004, 85, 467-474.

902

(53) Jouquand, C.; Aguni, Y.; Malhiac, C.; Grisel, M. Influence of chemical composition of

903

polysaccharides on aroma retention. Food Hydrocolloid, 2008, 22, 1097- 1104.

904

(54) Nongonierma, A.B.; Springett, M.; Le Queré, J.L.; Cayot, P.; Voilley, A. Flavour release at

905

gas/matrix interfaces of stirred yoghurt models. Int. Dairy J. 2006, 16, 102-110.

906

(55) Lubbers, S.; Decourcelle, N.; Martinez, D.; Guichard, E.; Tromelin, A. Effect of thickeners on

907

aroma compound behavior in a model dairy gel. J. Agric. Food Chem. 2007, 55, 4835-4841.

908

(56) González-Tomas, L.; Bayarri, S.; Taylor, A.J.; Costell, E. Flavour release and perception from

909

model dairy custards. Food Res. Int. 2007, 40, 520-528.

910

(57) Covarrubias-Cervantes, M.; Bongard, S.; Champion, D.; Voilley, A. Effects of the nature and

911

concentration of substrates in aqueous solutions on the solubility of aroma compounds. Flavour Fragr.

912

J., 2005, 20, 265-273.

913

(58) Lethuaut, L.; Brossard, C.; Meynier, A.; Rousseau, F.; Llamas, G.; Bousseau, B. Sweetness and

914

aroma perceptions in dairy desserts varying in sucrose and aroma levels and in textural agent. Int.

915

Dairy J., 2005, 15, 485-493.

916

(59) Poll, L. & Flink, J.M. Aroma analysis of apple juice: influence of salt addition on headspace

917

volatile composition as measured by gas chromatography and corresponding sensory evaluations.

918

Food Chem., 1984, 13, 193-207.

919

(60) Andriot, I.; Marin, I.; Feron, G.; Relkin, P.; Guichard, E. Binding of benzaldehyde by β-

920

lactoglobulin, by static headspace and high performance liquid chromatography in different physico-

921

chemical conditions. Lait, 1999, 79, 577-586.

922

(61) Perreault, V.; Britten, M.; Turgeon, S. L.; Seuvre, A.M.; Cayot, P.; Voilley, A. Effects of heat

923

treatment and acid-induced gelation on aroma release from flavoured skim milk. Food Chem., 2010,

924

118, 90-95.


36

Page 37 of 66


925

(62) Keim, S.; Kulozik, U; Hinrichs, J. Texture and stabilizing bonds in pressure-induced milk protein

926

gels. Milchwissenschaft 2006, 61, 363-366.

927

(63) Jouenne, E. & Crouzet, J. Effect of pH on retention of aroma compounds by β-lactoglobulin. J.

928

Agric. Food Chem. 2000, 48, 1273-1277.

929

(64) Van Ruth, S.M. & Villeneuve, E. Influence of β-lactoglobulin, pH and presence of other aroma

930

compounds on the air/liquid partition coefficients of 20 aroma compounds varying in functional group

931

and chain length. Food Chem. 2002, 79, 157-164.

932

(65) Tromelin, A.; Merabtine, Y.; Andriot, I.; Lubbers, S.; Guichard, E. Retention-release equilibrium of

933

aroma

934

relationships approach. Flavour Fragr. J. 2010, 25, 431–442.

935

(66) Tromelin, A. & Guichard, E. Interaction between flavour compounds and β-lactoglobulin:

936

approach by NMR and2D/3D-QSAR studies of ligands. Flavour Fragr. J. 2006, 21, 13-24.

937

(67) Savary, G.; Hucher, N.; Petibon, O.; Grisel, M. Study of interactions between aroma compounds

938

and acacia gum using headspace measurements, Food Hydrocolloid 2014, 37, 1-6.

939

(68) Roberts, D.D.; Pollien, P.; Antille, N.; Lindinger, C.; Yeretzianj, C. Comparison of nosespace,

940

headspace, and sensory intensity ratings for the evaluation of flavor absorption by fat. J. Agric. Food

941

Chem. 2003, 51, 3636-3642.

942

(69) Tehrany, E.A.; Mouawad, C.; Desobry, S. Determination of partition coefficient of migrants in food

943

simulants by the PRV method. Food Chem. 2007, 105, 1571-1577.

compounds

in

polysaccharide

gels:

study

by

quantitative

structure-activity/property

944


37


Page 38 of 66

Figure captions Fig. 1: Magnitude of the (A) 56 aroma compound log P values and (B) 542 matrix/gas partition coefficients KMG that were extracted from the reviewed literature (Table 2). Dashed lines border the upper and lower 2.5 %, 5.0 % and 12.5 % percent of log P and KMG-values, respectively. Fig. 2: KMG observed versus predicted plot obtained by multiple regression of (A) all KMG-values listed in Table 2 (excluding lines 52 and 439) and (B) 95 % of these values, excluding the upper and lower 2.5 %. For Fig. 2 (A) and (B), the following relationship between the fitting parameters and KMG is derived within the boundaries given in Table 5: 2 (A): KMG = 3491 – (393.7*log P) – (0.799*BP) – (19.52*pi0) + (6.861*Water) + (49.57*Protein) + (75.81*Fat) + (2.674*CWR) – (138.4*Thickeners) – (59.55*Disaccharides) – (48.33*Ash) – (1.303*DWPD) + (151.7*pH) – (87.15*ϑ); 2 (B): KMG = 2459 – (168.2*log P) – (3.075*BP) – (11.68*pi0) + (0.100*Water) + (19.18*Protein) + (49.59*Fat) + (2.043*CWR) – (90.59*Thickeners) + (6.191*Disaccharides) + (233.7*Ash) – (0.709*DWPD) + (62.81*pH) – (40.13*ϑ).

Fig. 3: KMG observed versus predicted plot obtained by multiple regression of all KMG-values listed in Table 2 (excluding lines 52 and 439), with the exception of diacetyl and limonene KMG-values, as well as the remaining upper and lower 2.5 %. Within the in Table 5 listed parameter boundaries, KMG can be calculated as follow: KMG = 3199 – (338.2*log P) – (6.404*BP) – (8.357*pi0) + (24.59*Water) + (4.839*Protein) + (44.01*Fat) + (0.545*CWR) – (66.48*Thickeners) – (3.362*Disaccharides) + (141.4*Ash) – (0.490*DWPD) + (24.94*pH) – (26.69*ϑ).

Fig. 4: KMG observed versus predicted plot obtained by multiple regression of (A) all KMG-values determined in protein- and fat-free matrices (excluding lines 52 and 439) and (B) with the exception of diacetyl and limonene KMG-values, as well as the remaining upper and lower 2.5 %. Within the in Table 5 listed parameter boundaries, KMG can be calculated as follow: KMG = 28019 – (151.4*log P) + (3.415*BP) – (0.037*pi0) - (278.0*Water) - (233.4*Thickeners) – (279.0*Disaccharides) – (273.3*Ash) – (30.24*pH) – (2.346*ϑ).

Fig. 5: KMG observed versus predicted plot obtained by multiple regression of (A) all KMG-values determined in protein-containing, fat-free matrices and (B) with the exception of diacetyl and limonene KMG-values, as well as the remaining upper and lower 2.5 %. Within the in Table 5 listed parameter boundaries, KMG in protein-containing, fat-free matrices (Fig. 5B) can be calculated as follow: KMG = 688.2 – (241.8*log P) + (4.275*BP) – (2.811*pi0) – (1.953*Water) + (1.108*Protein) + (0.033*CWR) – (3.987*Thickeners) – (5.948*Disaccharides) – (19.47*Ash) – (0.121*DWPD) – (17.88*pH) – (8.516*ϑ).


38

Page 39 of 66


Fig. 6: KMG observed versus predicted plot obtained by multiple regression of (A) all KMG-values determined in protein- and fat-containing matrices and (B) with the exception of diacetyl and limonene KMG-values, as well as the remaining upper and lower 2.5 %. Within the in Table 5 listed parameter boundaries, KMG in protein- and fat-containing matrices (Fig. 6 (B)) can be calculated as: KMG = 186867 – (1972*log P) + (73.55*BP) + (7.355*pi0) – (1677*Water) – (5654*Protein) – (1621*Fat) + (166.0*CWR) – (4432*Thickeners) – (540.2*Disaccharides) – (14153*Ash) – (0.641*DWPD) – (178.2*pH) – (133.4*ϑ).

Fig. 7: KMG observed versus predicted plot obtained by multiple regression of all diacetyl KMG-values. Within the in Table 5 listed parameter boundaries, KMG of diacetyl is calculated as: KMG = – 472801 + (4768*Water) + (4692*Protein) + (4607*Fat) – (7.672*CWR) – (6192*Thickeners) + (4085*Disaccharides) + (9597*Ash) + (0.410*DWPD) + (550.3*pH) – (162.4*ϑ).

Fig. 8: KMG observed versus predicted plot obtained by multiple regression of all limonene KMG-values. Within the in Table 5 listed parameter boundaries, KMG of limonene can be calculated as: KMG = 38281 – (411.6*Water) – (369.8*Protein) – (311.8*Fat) + (0.098*CWR) + (38.91*Thickeners) + (78.64*Disaccharides) – (1745*Ash) + (0.253*DWPD) – (14.39*pH) + (35.03*).

Fig. 9: KMG observed versus predicted plot obtained by multiple regression of all ethyl hexanoate KMGvalues. Within the in Table 5 listed parameter boundaries, KMG of ethyl hexanoate can be calculated as: KMG = 8156 – (80.89*Water) – (70.08*Protein) + (30.11*Fat) + (0.070*CWR) – (175.1*Thickeners) + (29.13*Disaccharides) – (215.1*Ash) – (0.569*DWPD) – (7.536*pH) – (12.80*ϑ).

945


39


946 947

Table 1: Concentration and supplier specification of the strawberry aroma-based composition of volatile compounds used in this study. Compound

% (w/w) in aroma

b

ppm (w/w)

log P

in final product

octanol/water

CAS-No. a

Limonene

1.20

120

+ 4,5

138-86-3

Ethyl hexanoate

0.60

60

+ 2,8

123-66-0

(Z)-3-hexenyl acetate

0.60

60

+ 2,4

3681-71-8

γ-decalactone

0.30

30

+ 2,4

706-14-9

Methyl cinnamate

0.30

30

+ 2,2

1754-62-7

Ethyl-2-methylbutanoate

1.00

100

+ 2,1

7452-79-1

Hexanoic acid

1.80

180

+ 1,8

142-62-1

Ethyl butanoate

0.80

80

+ 1,8

105-54-4

(Z)-3-hexenol

1.00

100

+ 1,6

928-96-1

2-methyl butyric acid

1.80

180

+ 1,1

116-53-0

Furaneol

0.27

27

+ 0,3

3658-77-3

b

1.20

120

- 1,3

431-03-8

89.13

-

Diacetyl

Propylene glycol

948 949 950 951 952

Page 40 of 66

-

57-55-6

The CAS-No. is a unique numerical identifier assigned by Chemical Abstracts Service to every chemical substance. a

log P (hydrophobicity) calculated by (ACD/Labs) Software V8.14 (Advanced Chemistry Development

Inc., Toronto, Canada). b

Compounds were added to commercial strawberry aroma.


40

Page 41 of 66


Table 2: Literature review of matrix/gas partition coefficients KMG of various aroma compounds, determined by the phase ratio variation (PRV) method, in aqueous, polysaccharide and dairy matrices. Aroma compound a denomination & specification Trivial name CAS-No. D.L-Limonene 138-86-3

Molecular structure

Aroma compound physico-chemical propertiesb log P range M (-) (mean value) BP (°C) pi0 (hPa) 4.45-4.57 136 (4.51) 178 2.05

(Dairy) matrix Compositionc ACC (ppm w/w) 120 120

Water (% w/w)

f Protein (% w/w)

g Milk fat (% w/w)

95.2 95.2

0.0 0.0

120 120 120 120 120 120 120 200 120 200 200 200 200 120 120 120 120 120 120 120 120 120 120 120 120 120 120 120

91.2 91.0 90.7 90.4 90.1 90.1 90.1 90.1 90.1 90.1 90.1 90.1 90.1 89.9 88.5 87.6 85.1 85.1 85.1 85.1 82.6 82.6 81.8 81.8 80.1 80.1 80.1 80.1

4.0 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 8.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0

200 200 120 200 120 120 200 200 200 120

89.7 89.2 88.2 88.1 86.3 86.3 86.3 86.3 86.3 78.7

6 6

6

4.0 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6

h

(Dairy) matrix Processingd

CWR (-)

i Thick. (% w/w)

j Disacc. (% w/w)

0.0 0.0

n.a. n.a.

0.00 0.00

1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.3 0.7 1.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 100.0 0.7 4.0 4.0 4.0 4.0 4.0 0.3 0.3 0.7 0.7 4.0 4.0 4.0 4.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 0.05 2 0.10 2 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

0.5 1.0 2.0 2.0 4.0 4.0 4.0 4.0 4.0 12.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

0.00 0.00 0.00 2 0.10 0.00 0.00 0.00 0.00 0.00 0.00

4.4 4.4

k Ash (% w/w)

l

4.07 9.68 13.75 18.04 22.70 30.48 43.43 27.71 25.12 18.56 30.28 31.22 25.78 24.21 49.83 29.27 44.25 39.67 40.33 80.40 28.47 40.47 38.15 70.20 61.69 76.33 75.25 80.64

40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40

3 3 3 3 3 92 57 92 99 3

6.75 6.75 6.75 6.75 6.75 1 4.23 6.75 6.75 6.75 6.75

83.22 148.80 273.04 301.33 392.97 610.67 508.37 374.26 375.89 918.22

40 40 40 40 40 40 40 40 40 40

1

0.79 0.78 0.78 0.78 0.77 0.77 0.77 0.77 0.77 0.74

5.0 5.0 5.0 1 5.0 1 4.9 1 4.9 1 4.9 1 4.9 1 4.9 1 4.5

Temp. First author (°C)

6.75 6.75 6.75 6.75 6.75 1 4.23 1 4.23 6.75 6.75 6.75 6.75 6.75 6.75 6.75 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23

0.49 0.57 0.64 0.72 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.86 0.75 0.97 1.15 1.15 1.15 1.15 0.85 0.85 1.07 1.07 1.51 1.51 1.51 1.51

1

KMG (-)

3 3 3 3 3 3 92 57 92 99 3 3 57 3 92 3 3 3 92 92 3 3 3 3 3 3 92 92

4.3 4.5 1 4.7 1 4.9 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.3 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 5.7 1 4.6 1 4.6 1 5.2 1 5.2 1 6.4 1 6.4 1 6.4 1 6.4 1

1

n

2.67 2.69

n.a. n.a.

1

pH (-)

4.23 6.75

0.43 0.43

1

m

DWPD (%)

Reported temperature-specific matrix/gas partition coefficiente

40 Heilig 40 Heilig

Line

Year

* *

1 2

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

201115 201115 201115 201115 201115 201115 * * * * * * * 15 2011 * * 15 2011 15 2011 * * * * * * 201115 15 2011 * *

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

* * * * * * * * * *

31 32 33 34 35 36 37 38 39 40



D-Limonene 5989-27-5

Decanoic acid 334-48-5

Ethyl octanoate 106-32-1

4.45-4.50 (4.48)

4.09 (4.09)

3.83-3.90 (3.87)

136 178 2.05

172 269 0.00

15 50 15 15 15 15 15 15 15 15

100.0 100.0 100.0 63.0 63.4 99.2 64.8 99.7 63.1 62.6

2

77.5

50 1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3

100.0 77.5

5.4 0.0

3

5.4

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1

4.0

0.0 1

4.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0.00 0.00 3 0.05 0.00 0.00 3 0.80 0.00 3 0.33 0.00 0.00

2.1

0.00

n.a. 2.1

172 207 0.30

8 50 8 8 8

100.0 100.0 63.1 63.1 63.1

0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a.

2-Decanone 693-54-9

3.73 (3.73)

156 210 0.36

33

100.0

0.0

0.0

1.0

Nonanal 204-688-5

3.36-3.46 (3.41)

142 192 0.71

20 20 20 20

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

1-Nonanol 143-08-8

3.30-3.39 (3.35)

144 214 0.05

12 12 12

100.0 99.6 98.8

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

12 12 12

86.4 86.3 86.2

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

13 50 13 13 1000 13 13 13 13 13 13 13

100.0 100.0 100.0 99.6 99.0 98.8 98.6 64.8 63.4 63.1 63.0 62.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

13 13 13

86.4 86.3 86.2

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

Linalool 78-70-6

2.91-3.40 (3.14)

154 195 0.12

2 2

2 2

0.0 0.0 0.0 2 35.0 2 35.0 0.0 2 35.0 0.0 2 35.0 2 35.0

0.00 0.00 0.00 0.19 0.19 0.00 0.19 0.00 0.19 0.19

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

3

1.20

n.a.

11.8

0.00 0.00 0.00 0.00 1.73 5 1.73 5 1.73 5

0.0 3

11.8

0.00 0.40 2 0.40 2 0.40

0.00 0.05 2 0.10

7.00

1

2

4.60

2061.86 33112.6

1

8771.93

4 Saint-Eve** 25 Atlan 4 Saint-Eve**

200647 14 2006 200647 200647 47 2006 200647 200647 200647 200647 200647

41 42 43 44 45 46 47 48 49 50

200645

51

2006

14

52

2006

45

53

47

2006 200614 200647 200647 47 2006

54 55 56 57 58

7.00 7.00 7.00 7.00 7.00

29.07 49.75 28.99 1 30.77 1 32.43

30 25 30 20 10

0.0

0.00

n.a.

7.00

1

40 Benjamin

201137

59

0.0 10.0 2 10.0 2 10.0

0.00 0.00 0.02 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

37 37 37 37

Bylaite Bylaite Bylaite Bylaite

200325 200325 25 2003 200325

60 61 62 63

0.00 0.62 3 0.62

n.a. n.a. n.a.

6.50 3.50 3.50

83.33 82.64 84.03

30 Merabtine 30 Merabtine 30 Merabtine

201029 201029 29 2010

64 65 66

5.7 5.8 3 5.8

0.86 0.86 0.86

85 85 85

4.00 4.00 1 4.00

400.00 250.00 166.67


201029 201029 29 2010

67 68 69

0.0 0.0 0.0 0.0 0.0 2 0.2 0.0 2 35.0 2 35.0 2 35.0 2 35.0 2 35.0

0.00 0.00 0.00 3 0.62 0.00 3 0.62 0.00 0.19 0.19 0.19 0.19 0.19


6.50 7.00 7.00 3.50 7.00 3.50 7.00 7.00 7.00 7.00 7.00 7.00

333.33 313.48 1 258.40 285.71 1 1265.82 256.41 1 280.90 1 254.45 1 310.08 1 313.73 1 310.08 1 296.30

30 25 30 30 7 30 30 30 30 30 30 30

Merabtine Atlan Savary Merabtine Deleris** Merabtine Savary Savary Savary Savary Savary Savary

201029 200614 200647 201029 200746 29 2010 47 2006 47 2006 47 2006 47 2006 47 2006 47 2006

70 71 72 73 74 75 76 77 78 79 80 81

0.86 0.86 0.86

85 85 85


2010 29 2010 29 2010

29

82 83 84

2

2

2

1

Savary Atlan Savary Savary Savary Savary Savary Savary Savary Savary


0.00 0.05 2 0.10 0.00 0.00 0.00 2 0.10 1 1.00 2 0.80 4 1.40 0.00 5 1.45 5 1.73 6 1.80 5 2.20

80

4.60

2

30 25 30 30 30 30 30 30 30 30

0.00 0.00 0.19 0.19 0.19

0.0 0.0 2 0.2

2

1.20

n.a.

1

0.0 0.0 35.0 2 35.0 2 35.0 2

0.00 0.10 2 0.80 2

0.00

1 3.98 96.15 1 390.24 1 400.00 1 410.26 1 411.52 1 411.52 1 416.67 1 450.70 1 457.14

7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00

1

0.00

2

Page 42 of 66

3

1

5.7 5.8 3 5.8 3

3

1 1

1

4.00 4.00 1 4.00 1

1 1

19.66

10.53 1 7.42 1 13.79 1 10.06

1

285.71 263.16 250.00

Savary Atlan Savary Savary Savary


Page 43 of 66


1000 1000 1000 1000 1000 1000 1000 1000 1000

81.8 89.6 79.6 77.5 77.5 77.5 77.5 77.5 77.5

2

5.4 4.4 2 5.4 2 5.4 2 5.4 4 5.4 4 5.4 3 5.4 2 5.4

0.0 0.1 1 2.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0

4.0 4.0 4.0 4.0 4.0 5.2 5.2 2.0 4.0

1

E-2-nonenal 18829-56-6

2.96-3.17 (3.07)

140 189 0.34

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

Nonan-2-one 821-55-6

2.90-3.03

142

3

100.0

0.0

0.0

n.a.

(2.97)

195 0.86

3 3 3 3

85.1 84.6 84.3 83.6

6

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.40 2 0.40 2 0.40 2

0.0 0.0 0.0 0.0

3.0 3.0 3.0 3.0

0.00 0.00 0.00 0.00

6

2

1

2

1

7.00

1

1

17.7 17.7 17.7 1 17.7

2.14 3.14 3.14 2 3.14

65 65 65 65

1

2

1

2

100.00 150.15 200.00 1 150.15

30 30 30 30

1

176.99

40 Benjamin

201137

103

27.78 14.81 22.22 22.73 1 17.64 1 19.16 1 20.70

30 37 30 30 37 37 37

Merabtine Bylaite Merabtine Merabtine Bylaite Bylaite Bylaite

201029 200325 29 2010 201029 200325 200325 200325

104 105 106 107 108 109 110


201029 201029 201029

111 112 113

30 25 30 7 25 10 40 40 25 10 20 30

Gierczynski Atlan Savary Deleris** Deleris** Lauverjat Heilig Heilig Deleris** Savary Savary Savary

2007 200614 200647 46 2007 48 2008 5 2009 * * 48 2008 47 2006 200647 200647

30

114 115 116 117 118 119 120 121 122 123 124 125

30 40 40 40 40

Martuscelli Heilig Heilig Heilig Heilig

200824 201115 201115 201115 201115

126 127 128 129 130

1

4

1

Octanal 124-13-0

2.80-2.95 (2.87)

128 172 2.75

11 20 11 11 20 20 20

100.0 100.0 99.6 98.8 89.6 89.6 89.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0.00 0.00 2 0.10 2 0.80 2 0.40 2 0.40 2 0.40

0.0 0.0 0.0 2 0.2 2 10.0 2 10.0 2 10.0

0.00 0.00 3 0.62 3 0.62 0.00 1 0.02 1 0.04


6.50 7.00 3.50 3.50 7.00 7.00 7.00

11 11 11

86.4 86.3 86.2

4.0 4.0 4.0

0.0 0.0 0.0

4.0 4.0 4.0

5.7 5.8 5.8

0.86 0.86 0.86

85 85 85

1 50 155 1000

155 155 155

100.0 100.0 100.0 99.0 99.0 99.0 95.2 95.2 64.0 63.1 63.1 63.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0


0.0 0.0 0.0 0.0 0.0 0.0 1 4.4 1 4.4 2 35.0 2 35.0 2 35.0 2 35.0

0.00 0.00 0.00 0.00 0.00 0.00 0.43 0.43 0.00 0.19 0.19 0.19


7.00 7.00 7.00 7.00 7.00 7.00 1 4.23 6.75 7.00 7.00 7.00 7.00

120 60 60 60 60

82.8 91.2 91.0 90.7 90.4

3.2 4.0 6 4.0 6 4.0 6 4.0

0.0 0.0 0.0 0.0 0.0

4.0 0.0 0.3 0.7 1.5

0.68 0.49 0.57 0.64 0.72

99 3 3 3 3

7.00 6.75 6.75 6.75 6.75

1 3

2

3

4.01 0.00 0.00 0.00 0.00

3

9.4 4.3 1 4.5 1 4.7 1 4.9 1

50.00

6.75 4.60 4.60 4 4.60 4

7.00

2

1

8 7 8 7 7 7 7 7 8

1

n.a.

5

99 100 101 102

n.a.

0.00

6

2007 30 2007 200730 200730

0.00

0.0

1

98

30

0.0

0.00

9 60 60

200730

37 37 37 37

n.a.

0.00 0.00 0.00 1 1.00 1 1.00 1 1.00 0.00 0.00 1 1.00 5 1.73 5 1.73 5 1.73

30 Gierczynski

49.75 36.90 1 50.25 1 40.32

0.0

144 167 2.21

94 95 96 97

1

0.0

2.80-2.84 (2.82)

25

7.00 7.00 7.00 7.00

100.0

Ethyl hexanoate 123-66-0

2003 200325 200325 200325

n.a. n.a. n.a. n.a.

33

0.00 0.05 0.10


0.00 0.00 1 0.02 1 0.04

130 195 0.20

2

85 86 87 88 89 90 91 92 93

0.0 10.0 2 10.0 2 10.0

2.88-3.00 (2.94)

2

200936 200746 200936 200746 200746 200746 200746 200746 200936

80 90 80 80 80 80 80 80 80

Octanol 111-87-5

2

Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris**

1.16 0.94 1.18 1.20 1.20 1.20 1.20 1.20 1.20

2

4.60 4.00 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60

3571.43 2564.10 1 4166.67 1 1724.14 1 1123.60 1 4761.90 1 3846.15 1 2439.02 1 9090.91

11.6 1 5.0 3 11.8 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 11.9

0.00

10.0 10.0 10.0 6 10.0 6

3

1

1

66.67 71.43 68.97

4.00 4.00 4.00

1 1

1

20.83 30.40 1 33.11 1 117.10 1 21.65 1 133.69 9.50 12.59 1 61.35 1 63.16 1 38.71 1 33.33 1

1

57.47 31.31 23.70 35.00 19.62

Gierczynski Gierczynski Gierczynski Gierczynski



60 60 60 100 60 100 100 100 100 60 1000 60 60 60 60 60 60 1 1 1 1 60 60 60 60 60 60 60 60

90.1 90.1 90.1 90.1 90.1 90.1 90.1 90.1 90.1 89.9 81.8 88.5 87.6 85.1 85.1 85.1 85.1 85.1 84.6 84.3 83.6 82.6 82.6 81.8 81.8 80.1 80.1 80.1 80.1

1000 100 100 60 100 1000 120 60 60 100 100 100 22 22 22 1000 1000 1000 1000 1000 1000 1000 60

89.6 89.7 89.2 88.2 88.1 79.6 80.2 86.3 86.3 86.3 86.3 86.3 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 78.7

6

4.0 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 2 5.4 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 8.0 6 10.0 6 10.0 6 10.0 6 10.0 6 10.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6

1

4.4 4.0 6 4.0 6 4.0 6 4.0 2 5.4 1 3.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 4 5.4 2 5.4 3 5.4 2 5.4 2 5.4 4 5.4 4 5.4 3 5.4 3 5.4 2 5.4 6 4.0 6

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 100.0 4.0 0.7 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 0.3 0.3 0.7 0.7 4.0 4.0 4.0 4.0

0.00 0.00 0.00 0.00 0.00 0.00 2 0.05 2 0.10 2 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.1 0.5 1.0 2.0 2.0 2.0 1 2.7 4.0 4.0 4.0 4.0 4.0 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 12.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.0 2.1 4.0 4.0 5.2 5.2 2.0 2.0 4.0 4.0

0.00 0.00 0.00 0.00 2 0.10 0.00 5 4.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

5.1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.3 3 11.6 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 5.7 1 17.7 1 17.7 1 17.7 1 17.7 1 4.6 1 4.6 1 5.2 1 5.2 1 6.4 1 6.4 1 6.4 1 6.4 1

1

5.0 5.0 1 5.0 1 5.0 1 5.0 3 11.8 3 9.3 1 4.9 1 4.9 1 4.9 1 4.9 1 4.9 3 11.8 3 11.8 3 11.8 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 11.9 1 4.5 1

Page 44 of 66

0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.86 1.16 0.75 0.97 1.15 1.15 1.15 1.15 2.14 2 3.14 2 3.14 2 3.14 0.85 0.85 1.07 1.07 1.51 1.51 1.51 1.51

3 3 92 57 92 99 3 3 57 3 80 92 3 3 3 92 92 65 65 65 65 3 3 3 3 3 3 92 92

0.94 0.79 0.78 0.78 0.78 1.18 0.67 0.77 0.77 0.77 0.77 0.77 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 0.74

90 3 3 3 3 80 99 3 92 57 92 99 80 80 80 80 80 80 80 80 80 80 3

6.75 4.23 1 4.23 6.75 6.75 6.75 6.75 6.75 6.75 6.75 2 4.60 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 4 4.60 4 4.60 4 4.60 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23

27.01 36.03 33.85 31.63 28.52 15.50 28.59 25.24 24.74 25.18 1 261.78 56.25 39.38 59.75 64.20 44.67 34.47 1 36.36 1 66.67 1 71.43 1 71.43 86.92 94.37 79.45 63.73 73.04 77.33 76.99 85.02

40 40 40 40 40 40 40 40 40 40 8 40 40 40 40 40 40 30 30 30 30 40 40 40 40 40 40 40 40

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Deleris** Heilig Heilig Heilig Heilig Heilig Heilig Gierczynski Gierczynski Gierczynski Gierczynski Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

201115 201115 * * * * * * * 15 2011 36 2009 * * 15 2011 15 2011 * * 30 2007 30 2007 30 2007 200730 * * * * 201115 201115 * *

131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159

2

1

7 40 40 40 40 8 30 40 40 40 40 40 4 4 4 7 7 7 7 7 7 8 40

Deleris** Heilig Heilig Heilig Heilig Deleris** Martuscelli Heilig Heilig Heilig Heilig Heilig Saint-Eve** Saint-Eve** Saint-Eve** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Heilig

200736 * * * * 200936 200824 * * * * * 45 2006 45 2006 200645 200746 200746 200746 200746 46 2007 46 2007 36 2009 *

160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182

1

4.00 6.75 6.75 6.75 6.75 2 4.60 7.00 6.75 1 4.23 6.75 6.75 6.75 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 6.75

258.40 43.18 96.78 182.67 189.67 1 869.57 1 578.03 343.91 410.64 322.16 229.85 260.61 1 2331.00 1 1845.02 1 1499.25 1 1369.86 1 1562.50 1 1562.50 1 1818.18 1 1612.90 1 1538.46 1 1785.71 1056.88


Page 45 of 66

3-Octanol 589-98-0

Isopropyl tiglate 1733-25-1


2.70-2.82 (2.76)

2.60-2.75 (2.68)

130 174 0.68

142 n.a. 2.50

11 11 11

100.0 99.6 98.8

11 11 11

86.4 86.3 86.2

13 13 13

100.0 99.6 98.8

13 13 13

86.4 86.3 86.2

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

2 2

2 2

E,E-2,4-nonadienal 5910-87-2

2.55-2.65 (2.60)

138 n.a. 0.14

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

E,E-2,6-nonadienal 17587-33-6

2.55-2.60 (2.58)

138 203 0.37

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

γ-deca-lactone 706-14-9

2.39-2.72 (2.56)

170 267 0.01

50

100.0

0.0

0.0

n.a.

E-2-octenal 2548-87-0

2.44-2.64 (2.54)

126 n.a. 0.73

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

(Z)-3-hexenyl acetate 3681-71-8

2.40-2.63 (2.48)

142 166 1.62

60 60

95.2 95.2

0.0 0.0

0.0 0.0

n.a. n.a.

30 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60

82.8 90.1 90.1 90.1 90.1 88.5 87.6 85.1 85.1 85.1 85.1 82.6 82.6 81.8 81.8 80.1

3.2 4.0 6 4.0 6 4.0 6 4.0 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 8.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 4.0 4.0 0.7 4.0 4.0 4.0 4.0 4.0 0.3 0.3 0.7 0.7 4.0

1 6

0.00 0.10 2 0.80

0.0 0.0 2 0.2

186 187 188

6.50 3.50 3.50

30.77 26.67 26.74


201029 29 2010 201029

189 190 191

37.04 36.36 35.71


2010 201029 201029

29

192 193 194

192.31 196.08 1 416.67 1 217.39

37 37 37 37


200325 25 2003 200325 200325

195 196 197 198

7.00 7.00 7.00 7.00

1

188.68 222.22 1 256.41 1 250.00

37 37 37 37


200325 200325 200325 25 2003

199 200 201 202

n.a.

7.00

1

25 Atlan

200614

203

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

37 37 37 37

200325 25 2003 200325 200325

204 205 206 207

0.43 0.43

n.a. n.a.

* *

208 209

0.68 0.79 0.79 0.79 0.79 0.75 0.97 1.15 1.15 1.15 1.15 0.85 0.85 1.07 1.07 1.51

99 92 92 3 3 92 3 92 92 3 3 3 3 3 3 92

24

210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

0.0

0.00

0.0 10.0 2 10.0 2 10.0

3

2

2

0.00

4.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

29

85 85 85

1

5

2010 201029 201029

0.86 0.86 0.86

0.00 0.05 2 0.10 2

0.00 0.00


5.7 5.8 3 5.8

0.0 0.0 2 0.2

0.00 0.40 2 0.40 2 0.40

250.00 222.22 200.00

n.a. n.a. n.a.

0.00 0.10 2 0.80

5.7 5.8 3 5.8

2

2

4.00 4.00 1 4.00

0.00 0.62 3 0.62

3

0.00 0.40 2 0.40 2 0.40

183 184 185

85 85 85

1

2

201029 29 2010 201029

0.86 0.86 0.86

0.00 0.05 2 0.10

0.00 0.40 2 0.40 2 0.40


n.a. n.a. n.a.

2

2

222.22 181.82 178.57

0.00 0.62 3 0.62

2

2

1

4.4 4.4

1

3

9.4 5.1 1 5.1 1 5.1 1 5.1 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 5.7 1 4.6 1 4.6 1 5.2 1 5.2 1 6.4 1

3

3

6.50 3.50 3.50 1 1

1

4.00 4.00 1 4.00 1

1

1

296.74

1

73.53 62.50 1 59.17 1 70.92 1

1

40.00 41.88

4.23 6.75

7.00 6.75 1 4.23 6.75 1 4.23 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75

1

107.53 72.00 67.33 66.47 58.89 105.20 82.00 78.00 70.77 107.75 98.20 109.32 101.80 119.67 76.60 117.33


40 Heilig 40 Heilig 30 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40

Martuscelli Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

2008

* * * * * * * * * * * * * * *



60 60 60 60 30 60 60 60

80.1 80.1 80.1 88.2 80.2 86.3 86.3 78.7

6

12.0 12.0 6 12.0 6 4.0 1 3.0 6 4.0 6 4.0 6 4.0

0.0 0.0 0.0 2.0 2.7 4.0 4.0 12.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

0.00 0.00 0.00 0.00 5 4.01 0.00 0.00 0.00

6

1

Page 46 of 66

6.4 6.4 1 6.4 1 5.0 3 9.3 1 4.9 1 4.9 1 4.5

1.51 1.51 1.51 0.78 0.67 0.77 0.77 0.74

92 3 3 3 99 3 92 3

1

1

4.23 6.75 4.23 6.75 7.00 6.75 1 4.23 6.75 1

2-Octanone 111-13-7

2.37-2.50 (2.44)

128 174 1.80

20 20 20 20

100.0 100.0 100.0 100.0

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

0.00 0.00 0.00 0.00

0.0 0.0 0.0 0.0

0.00 0.00 0.00 0.00

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

Heptanal 111-71-7

2.29-2.50 (2.37)

114 153 5.12

20 33 20 20 20

100.0 100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0


0.00 0.00 2 0.40 2 0.40 2 0.40

0.0 0.0 2 10.0 2 10.0 2 10.0

0.00 0.00 0.00 1 0.02 1 0.04


7.00 7.00 7.00 7.00 7.00

Methyl cinnamate 103-26-4

2.18 (2.18)

162 261 0.01

50

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

Ethyl-3Methylbutanoate 108-64-5

2.12-2.19 (2.16)

130 132 10.44

60

82.8

1

3.2

0.0

4.0

5

0.68

99

7.00

80.2

1

4.0

5

Ethyl-2-methylbutanoate 7452-79-1

2.10-2.12 (2.11)

130 133 10.44

60 100 100

95.2 95.2

100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

90.1 90.1 90.1 90.1 88.5 87.6 85.1 85.1 85.1 85.1 82.6 82.6 81.8 81.8 80.1 80.1 80.1 80.1

100 100 100 100

88.2 86.3 86.3 78.7

3.0

2.7

4.01

3

4.01

3

9.4 9.3

0.0 0.0

0.0 0.0

n.a. n.a.

0.00 0.00

1

4.0 4.0 6 4.0 6 4.0 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 8.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 4.0 0.7 4.0 4.0 4.0 4.0 4.0 0.3 0.3 0.7 0.7 4.0 4.0 4.0 4.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

2.0 4.0 4.0 12.0

4.0 4.0 4.0 4.0

0.00 0.00 0.00 0.00

6 6

6

4.0 4.0 6 4.0 6 4.0 6

4.4 4.4

0.67

99

0.43 0.43

n.a. n.a.

5.1 5.1 5.1 1 5.1 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 5.7 1 4.6 1 4.6 1 5.2 1 5.2 1 6.4 1 6.4 1 6.4 1 6.4

0.79 0.79 0.79 0.79 0.75 0.97 1.15 1.15 1.15 1.15 0.85 0.85 1.07 1.07 1.51 1.51 1.51 1.51

92 3 3 92 92 3 92 92 3 3 3 3 3 3 92 92 3 3

1

0.78 0.77 0.77 0.74

3 3 92 3

1

1 1

5.0 4.9 4.9 1 4.5 1 1

7.00

125.95 121.73 103.00 291.50 1 781.25 569.80 479.50 1137.57

40 40 40 40 30 40 40 40

Heilig Heilig Heilig Heilig Martuscelli Heilig Heilig Heilig

200824 * * *

25 60 70 80

Jouquand Jouquand Jouquand Jouquand

25.38 34.13 1 22.99 1 22.47 1 27.86

37 40 37 37 37

Bylaite Benjamin Bylaite Bylaite Bylaite

409.84

1

161.29 1 13.40 1 8.33 1 5.41 1 1

1

1

30.21

1

144.93

* * * *

226 227 228 229 230 231 232 233

2004 200452 200452 200452

52

234 235 236 237

200325 201137 200325 25 2003 25 2003

238 239 240 241 242

25 Atlan

200614

243

30 Martuscelli

200824

244

30 Martuscelli

24

245

2008

1

4.23 6.75

15.75 12.43

40 Heilig 40 Heilig

* *

246 247

6.75 6.75 4.23 1 4.23 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23

22.00 14.45 17.24 25.07 32.34 18.95 27.33 29.93 22.33 15.40 23.35 33.23 30.89 30.00 38.82 60.22 26.62 25.67

40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

* * * * * * * * * * * * * * * * * *

248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265

6.75 6.75 4.23 6.75

58.00 114.98 139.37 293.63

40 40 40 40

Heilig Heilig Heilig Heilig

* * * *

266 267 268 269

1

1


Page 47 of 66


E,E-2,4-octadienal 30361-28-5

2.03-2.12 (2.08)

124 199 0.48

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

E-2-heptenal 18829-55-5

1.92-2.11 (2.02)

112 166 2.42

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

2-Heptanone 110-43-0

1.70-2.20 (1.96)

114 150 6.29

3 9 20 20 20 20 9 6 9

100.0 100.0 100.0 100.0 100.0 100.0 99.6 99.0 98.8

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

9 9 9 3 3 3 3

86.4 86.3 86.2 85.1 84.6 84.3 83.6

4.0 4.0 2 4.0 6 10.0 6 10.0 6 10.0 6 10.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 3.0 3.0 3.0 3.0

6 6

63.0 63.0

5

1 7.4 14.8

100.0 100.0

3.2

0.0

4.0

2 2

5

24.4 18.3 1

1

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

270.27 526.32 1 833.33 1 312.50

37 37 37 37


200325 25 2003 200325 200325

270 271 272 273

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

116.28 153.85 1 106.38 1 104.17

37 37 37 37


200325 25 2003 200325 200325

274 275 276 277

0.00 0.00 0.00 0.00 0.00 0.00 2 0.10 1 1.00 2 0.80

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2 0.2

0.00 0.00 0.00 0.00 0.00 0.00 3 0.62 0.00 3 0.62


7.00 6.50 7.00 7.00 7.00 7.00 3.50 7.00 3.50

1 83.33 105.26 1 175.44 1 25.64 1 14.01 1 9.71 100.00 1 609.76 83.33

30 30 25 60 70 80 30 10 30

Gierczynski Merabtine Jouquand Jouquand Jouquand Jouquand Merabtine Lauverjat Merabtine

200730 201029 200452 200452 52 2004 52 2004 29 2010 5 2009 29 2010

278 279 280 281 282 283 284 285 286

0.00 0.05 2 0.10 0.00 0.00 0.00 0.00

1

5.7 5.8 3 5.8 1 17.7 1 17.7 1 17.7 1 17.7

0.86 0.86 0.86 2.14 2 3.14 2 3.14 2 3.14

85 85 85 65 65 65 65

1

105.26 100.00 90.91 1 66.67 1 90.91 1 100.00 1 71.43

30 30 30 30 30 30 30

Merabtine Merabtine Merabtine Gierczynski Gierczynski Gierczynski Gierczynski

201029 201029 201029 200730 200730 200730 200730

287 288 289 290 291 292 293

1

2

n.a. n.a.

1

2

4.11 3.46

3

1

3

1

1020.41 1666.67

13 Lauverjat 13 Lauverjat

20095 20095

294 295

9.4

0.68

99

7.00

1

30 Martuscelli

200824

296

1

60 Jouquand 70 Jouquand 80 Jouquand

200452 200452 200452

297 298 299

30 25 60 70 80 37 30 37 37 37 30 30 30 30 30

200647 52 2004 200452 200452 200452 200325 200647 200325 200325 200325 200647 200647 200647 47 2006 47 2006

300 301 302 303 304 305 306 307 308 309 310 311 312 313 314

0.00 0.40 2 0.40 2 0.40 2

0.00 0.40 2 0.40 2 0.40 2

2

0.00 0.00 5

4.01

2

2

3

33.4 25.1 3

1

1

4.00 4.00 1 4.00 6.75 4 4.60 4 4.60 4 4.60 1

6.20 6.20

Benzyl acetate 140-11-4

1.96-1.97 (1.97)

150 214 0.24

24

82.8

1-Hexanol 111-27-3

1.86-2.03 (1.95)

102 157 1.23

20 20 20

100.0 100.0 100.0

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

0.00 0.00 0.00

0.0 0.0 0.0

0.00 0.00 0.00

n.a. n.a. n.a.

7.00 7.00 7.00

Hexanal 66-25-1

1.78-1.97 (1.85)

100 131 14.50

7 20 20 20 20 20 7 20 20 20 7 7 7 7 7

100.0 100.0 100.0 100.0 100.0 100.0 98.6 89.6 89.6 89.6 64.8 63.4 63.1 63.0 62.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0.00 0.00 0.00 0.00 0.00 0.00 4 1.40 2 0.40 2 0.40 2 0.40 0.00 5 1.45 5 1.73 6 1.80 5 2.20

0.0 0.0 0.0 0.0 0.0 0.0 0.0 2 10.0 2 10.0 2 10.0 2 35.0 2 35.0 2 35.0 2 35.0 2 35.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1 0.02 1 0.04 0.19 0.19 0.19 0.19 0.19

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00

719.42

117.65 1 75.19 1 49.50 1

86.21 90.91 1 12.00 1 7.87 1 5.29 1 38.91 1 95.24 1 37.88 1 36.50 1 40.16 1 84.66 1 102.56 1 102.56 1 102.56 1 104.58 1

Savary Jouquand Jouquand Jouquand Jouquand Bylaite Savary Bylaite Bylaite Bylaite Savary Savary Savary Savary Savary



82.8

1

50 1 1 1

80.3 77.5 77.5 77.5

1

1 50 188 22 22 22 22 35 80 80 188 188 188

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 95.2 95.2 63.1 63.1 63.1

540 80 80 80 80 80 80 80 80 80 80 1 1 1 1 80 80 80 80 80 80 80 80

82.8 90.1 90.1 90.1 90.1 88.5 87.6 85.1 85.1 85.1 85.1 85.1 84.6 84.3 83.6 82.6 82.6 81.8 81.8 80.1 80.1 80.1 80.1

80 540 80 80 27 27 27 80

88.2 80.2 86.3 86.3 77.5 77.5 77.5 78.7

10 10

100.0 99.6

12

Ethyl butanoate 105-54-4

Ethyl crotonate 623-70-1

1.70-1.85 (1.78)

1.60-1.85 (1.73)

116 121 17.02

114 143

4.0

5

2.7 4.0 4.0 1 4.0

4.0 4.5 4.0 2.1

5

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

3.2 4.0 6 4.0 6 4.0 6 4.0 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 8.0 6 10.0 6 10.0 6 10.0 6 10.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 4.0 4.0 0.7 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 0.3 0.3 0.7 0.7 4.0 4.0 4.0 4.0

4.0 3.0 6 4.0 6 4.0 4 5.4 2 5.4 3 5.4 6 4.0

2.0 2.7 4.0 4.0 1 4.0 1 4.0 1 4.0 12.0

4.0 4.0 4.0 4.0 4.5 4.0 2.1 4.0

0.0 0.0

0.0 0.0

n.a. n.a.

3.2

3.0 5.4 5.4 3 5.4

0.0

4

1

2

1

1 6

6 1

4.01

3

4.01 0.00 0.00 0.00

3

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5 1.73 5 1.73 5 1.73 5

4.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

9.4

99

1

7.00

167.79 2336.45 1077.59 1 1137.66

0.67 1.20 1.20 1.20

99 80 80 80

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 4.4 1 4.4 2 35.0 2 35.0 2 35.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.43 0.43 0.19 0.19 0.19

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 1 4.23 6.75 7.00 7.00 7.00

1

0.68 0.79 0.79 0.79 0.79 0.75 0.97 1.15 1.15 1.15 1.15 2.14 2 3.14 2 3.14 2 3.14 0.85 0.85 1.07 1.07 1.51 1.51 1.51 1.51

99 92 92 3 3 92 3 92 92 3 3 65 65 65 65 3 3 3 3 92 92 3 3

7.00 6.75 1 4.23 6.75 1 4.23 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 4 4.60 4 4.60 4 4.60 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23 6.75 1 4.23

0.78 0.67 0.77 0.77 1.20 1.20 1.20 0.74

3 99 3 92 80 80 80 3

6.75 7.00 6.75 1 4.23 2 4.60 2 4.60 2 4.60 6.75

0.00 0.62

n.a. n.a.

6.50 3.50

3

9.4 5.1 1 5.1 1 5.1 1 5.1 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 5.7 1 17.7 1 17.7 1 17.7 1 17.7 1 4.6 1 4.6 1 5.2 1 5.2 1 6.4 1 6.4 1 6.4 1 6.4 1

1

0.00 0.10

0.0 0.0

3 1

3

7.00 4.60 4.60 2 4.60

40.65

1

9.3 11.8 11.8 3 11.8

5.0 9.3 4.9 1 4.9 3 11.8 3 11.8 3 11.8 1 4.5

2

0.68

3

3

0.00 4.01 0.00 0.00 0.00 0.00 0.00 0.00

5

Page 48 of 66

2

1

2

1

30 Martuscelli

200824

315

24

30 4 4 4

Martuscelli Saint-Eve** Saint-Eve** Saint-Eve**

2008 200645 200645 200645

316 317 318 319

41.67 43.29 1 54.64 1 55.56 1 12.50 1 8.06 1 5.99 1 56.37 28.75 22.09 1 89.69 1 63.16 1 53.48

30 25 30 25 60 70 80 40 40 40 10 20 30

Gierczynski Atlan Savary Jouquand Jouquand Jouquand Jouquand Benjamin Heilig Heilig Savary Savary Savary

2007 200614 200647 200452 200452 200452 52 2004 37 2011 * * 47 2006 47 2006 47 2006

30

320 321 322 323 324 325 326 327 328 329 330 331 332

1

43.86 34.67 36.67 30.46 27.68 46.19 29.50 36.67 37.70 36.25 30.40 1 40.00 1 43.48 1 42.55 1 35.71 43.89 56.00 47.49 47.13 44.94 66.92 35.47 35.00

30 40 40 40 40 40 40 40 40 40 40 30 30 30 30 40 40 40 40 40 40 40 40

Martuscelli Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Gierczynski Gierczynski Gierczynski Gierczynski Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

200824 * * * * * * * * * * 30 2007 30 2007 200730 200730 * * * * * * * *

333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355

53.00 107.76 97.40 106.35 1 483.09 1 458.72 1 389.11 206.00

40 30 40 40 4 4 4 40

Heilig Martuscelli Heilig Heilig Saint-Eve** Saint-Eve** Saint-Eve** Heilig

*

2006 45 2006 45 2006 *

45

356 357 358 359 360 361 362 363

201029 201029

364 365

1

1

117.65 133.33

30 Merabtine 30 Merabtine

2008

24

* *


Page 49 of 66

Ethylbutanal 97-96-1


1.70-1.73 (1.72)

9.14

10

98.8

0.0

0.0

n.a.

86.4 86.3 86.2 100.0 99.6 98.8

2

100 117 22.48

10 10 10 8 8 8

4.0 4.0 2 4.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 n.a. n.a. n.a.

8 8 8

86.4 86.3 86.2

2

4.0 4.0 4.0

0.0 0.0 0.0

4.0 4.0 4.0

2

2 2

t-2-hexenal 85761-70-2

1.58-1.79 (1.69)

98 142 8.78

n.a. n.a. n.a.

100.0 100.0 100.0

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

2-methyl-pentanal 123-15-9

1.79 (1.79)

100 120 22.48

20 20 20 20

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

Hexenal 6728-26-3

1.40-1.79 (1.60)

98 147 6.15

8 40 8 8 40 40 40

100.0 100.0 99.6 98.8 89.6 89.6 89.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0


8 8 8

86.4 86.3 86.2

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

50 163 100 100

100.0 100.0 95.2 95.2

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

100 100 100 100 100 100 100 100 100 100

90.1 90.1 90.1 90.1 85.1 85.1 85.1 81.8 80.1 80.1

4.0 4.0 6 4.0 6 4.0 6 8.0 6 8.0 6 8.0 6 12.0 6 12.0 6 12.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 0.7 4.0 4.0

100 750 100 24 24

88.2 80.3 86.3 77.5 77.5

2.0 2.7 4.0 1 4.0 1 4.0

4.0 4.0 4.0 4.5 4.0

(Z)-3-hexenol 928-96-1

1.56-1.61 (1.59)

100 157 1.38

2 2

6 6

6

4.0 3.0 6 4.0 4 5.4 2 5.4 1

2

0.80

2

3

0.62

n.a.

0.00 0.05 2 0.10 0.00 2 0.10 2 0.80

1

0.86 0.86 0.86 0.00 3 0.62 3 0.62

85 85 85 n.a. n.a. n.a.

1

0.00 0.05 0.10

1

5.7 5.8 5.8

0.86 0.86 0.86

85 85 85

1

0.0 0.0 0.0

0.00 0.00 0.00

n.a. n.a. n.a.

7.00 7.00 7.00

1

0.2

5.7 5.8 3 5.8 0.0 0.0 2 0.2

2

3

2

3

2

3

0.00 0.00 0.00 0.00 0.40 2 0.40 2 0.40

7.00 7.00 7.00 7.00

0.00 0.00 2 0.10 2 0.80 2 0.40 2 0.40 2 0.40

0.0 0.0 0.0 2 0.2 2 10.0 2 10.0 2 10.0

0.00 0.00 3 0.62 3 0.62 0.00 1 0.02 1 0.04


6.50 7.00 3.50 3.50 7.00 7.00 7.00

5.7 5.8 3 5.8

0.86 0.86 0.86

85 85 85

0.00 0.00 0.00 0.00

0.0 0.0 1 4.4 1 4.4

0.00 0.00 0.43 0.43

n.a. n.a. n.a. n.a.

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

5.1 5.1 5.1 1 5.1 1 5.7 1 5.7 1 5.7 1 5.2 1 6.4 1 6.4

0.79 0.79 0.79 0.79 1.15 1.15 1.15 1.07 1.51 1.51

92 92 3 3 92 3 3 3 3 3

0.00 4.01 0.00 0.00 0.00

1

0.78 0.67 0.77 1.20 1.20

3 99 3 80 80

5

1

5.0 9.3 4.9 3 11.8 3 11.8 3 1

30 30 30 30 30 30

Merabtine Merabtine Merabtine Merabtine Merabtine Merabtine

201029 29 2010 201029 201029 201029 29 2010

367 368 369 370 371 372

25.64 22.86 23.53


201029 201029 29 2010

373 374 375

46.95 36.23 1 29.94


200452 200452 200452

376 377 378

1

22.78 21.79 1 20.70 1 22.52

37 37 37 37


2003 200325 200325 25 2003

25

379 380 381 382

222.22 178.57 105.26 105.26 1 161.29 1 163.93 1 156.25

30 37 30 30 37 37 37

Merabtine Bylaite Merabtine Merabtine Bylaite Bylaite Bylaite

201029 200325 29 2010 201029 200325 200325 200325

383 384 385 386 387 388 389


201029 201029 201029

390 391 392

1841.62 1865.67 611.50 432.21

25 30 40 40

Atlan Savary Heilig Heilig

200614 47 2006 * *

393 394 395 396

797.67 708.67 523.75 520.33 765.67 1231.25 679.80 777.00 1040.21 554.67

40 40 40 40 40 40 40 40 40 40

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

* * * * * * * * * *

397 398 399 400 401 402 403 404 405 406

922.00 1754.39 891.50 1 5494.51 1 6622.52

40 30 40 4 4

Heilig Martuscelli Heilig Saint-Eve** Saint-Eve**

* 200824 * 200645 45 2006

407 408 409 410 411

4.00 4.00 4.00

n.a. n.a. n.a. n.a.

1

111.11 105.26 100.00 25.00 21.05 21.98

1

0.00 0.00 1 0.02 1 0.04

3

366

1

0.0 10.0 2 10.0 2 10.0

1

201029

4.00 4.00 1 4.00 6.50 3.50 3.50

2

0.00 0.05 2 0.10

30 Merabtine

1

2

2

142.86

3.50

1

1

1

1

500.00 454.55 408.16

4.00 4.00 1 4.00 1

7.00 7.00 1 4.23 6.75 6.75 4.23 6.75 1 4.23 1 4.23 6.75 1 4.23 1 4.23 6.75 1 4.23 1

6.75 7.00 6.75 2 4.60 2 4.60

1 1

1



24 100

77.5 78.7

3 6

5.4 4.0

1 4.0 12.0

2.1 4.0

E,E-2,4-heptadienal 4313-03-5

1.51-1.59 (1.55)

110 n.a. 1.38

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

2-Hexanone 591-78-6

1.38 (1.38)

100 128 15.43

n.a. n.a. n.a.

100.0 100.0 100.0

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

Pentanal 110-62-3

1.29-1.44 (1.37)

86 103 42.29

20 20 20 20

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

2-methyl butanal 96-17-3

1.25-1.34 (1.30)

86 92 65.57

20 20 20 20

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

3-methyl butanal 590-86-3

1.25-1.34 (1.30)

86 92 65.57

20 20 20 20

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

Methylpentenone 141-79-7

1.12-1.30 (1.21)

98 130 11.65

8 8 8

100.0 99.6 98.8

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

8 8 8

86.4 86.3 86.2

4.0 4.0 2 4.0

0.0 0.0 0.0

4.0 4.0 4.0

2 2

0.00 0.00 0.00 0.40 2 0.40 2 0.40 2

3

0.00 0.40 2 0.40 2 0.40 0.00 0.40 2 0.40 2 0.40 2

0.00 0.40 2 0.40 2 0.40 2

2

1

4 Saint-Eve** 40 Heilig

200645 *

412 413

37 37 37 37


200325 25 2003 200325 200325

414 415 416 417

34.48 22.99 1 16.69


200452 200452 200452

418 419 420

7.00 7.00 7.00 7.00

1

59.17 62.89 1 68.49 1 62.11

37 37 37 37


2003 200325 200325 200325

25

421 422 423 424

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

31.65 31.25 1 30.40 1 32.57

37 37 37 37


2003 200325 200325 200325

25

425 426 427 428

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

38.91 37.88 1 36.90 1 39.37

37 37 37 37


200325 200325 200325 25 2003

429 430 431 432

0.00 0.62 3 0.62

n.a. n.a. n.a.

6.50 3.50 3.50

266.67 250.00 243.90


201029 201029 29 2010

433 434 435

5.7 5.8 3 5.8

0.86 0.86 0.86

85 85 85

222.22 200.00 181.82


201029 201029 201029

436 437 438

25 Atlan

200614

439

20 Tehrany

200769

440

1.20 0.74

80 3

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

0.0 0.0 0.0

0.0 0.0 0.0

n.a. n.a. n.a.

7.00 7.00 7.00

1

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

0.0 10.0 2 10.0 2 10.0

2

2

2

2

0.00 0.10 2 0.80

0.0 0.0 2 0.2

0.00 0.05 2 0.10

1

2

2

3

3

4.60 6.75

9803.92 862.25

11.8 1 4.5

0.00 0.00 0.00 2

Page 50 of 66

1

434.78 400.00 1 666.67 1 312.50 1

1

1

1

1

1

4.00 4.00 1 4.00 1

1

3194.89

Vanillin 121-33-5

1.19-1.21 (1.20)

152 286 0.00

50

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

Isopropyl acetate 108-21-4

1.06-1.20 (1.13)

102 89 80.29

87

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

E-2-pentanal 1576-87-0

0.88-1.28 (1.08)

84 n.a. 15.23

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

263.16 238.10 1 238.10 1 232.56

37 37 37 37


200325 200325 200325 25 2003

441 442 443 444

E,E-2,4-hexadienal 142-83-6

0.99-1.06 (1.03)

96 174 3.95

40 40 40 40

100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

0.0 10.0 2 10.0 2 10.0

0.00 0.00 1 0.02 1 0.04

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1

37 37 37 37


200325 25 2003 200325 200325

445 446 447 448

Butanal

0.81-0.88

72

80

100.0

0.0

0.0

n.a.

0.0

0.00

n.a.

7.00

200769

449

0.00 0.40 2 0.40 2 0.40 2

0.00 0.40 2 0.40 2 0.40 2

0.00

2

2

41.10

1

555.56 625.00 1 625.00 1 526.32 1

40.90

20 Tehrany


Page 51 of 66

123-72-8


(0.84)

75 n.a.

2-methyl propanal 78-84-2

0.74-0.82 (0.78)

72 63 230.09

Ethyl acetate 141-78-6

0.71-0.73 (0.72)

88 77 88.05

20 20 20 20 20 20 20 20

100.0 89.6 89.6 89.6 100.0 89.6 89.6 89.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

50 123 90 1000

123 123 123

100.0 100.0 100.0 99.0 99.0 64.0 63.1 63.1 63.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1000

81.8

2

5.4

0.0

1000 1000 18 18 18 1000 1000 1000 1000 1000 1000 1000

89.6 79.6 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5

1

4.4 5.4 5.4 2 5.4 3 5.4 2 5.4 2 5.4 4 5.4 4 5.4 3 5.4 3 5.4 2 5.4

0.00 0.40 2 0.40 2 0.40 0.00 2 0.40 2 0.40 2 0.40

450 451 452 453 454 455 456 457

103.84 1 61.73 37.70 1 361.01 1 81.97 1 86.21 1 160.00 1 75.02 1 61.54

25 30 20 7 25 25 10 20 30

Atlan Savary Tehrany Deleris** Deleris** Deleris** Savary Savary Savary

200614 200647 69 2007 46 2007 200848 200848 200647 200647 200647

458 459 460 461 462 463 464 465 466

8 Deleris**

200936

467

46

7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00


0.00 0.00 0.00 1 1.00 1 1.00 1 1.00 5 1.73 5 1.73 5 1.73

0.0 0.0 0.0 0.0 0.0 2 35.0 2 35.0 2 35.0 2 35.0

0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.19 0.19


7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00

4.0

0.00

3

1.16

80

2

1

2

1

2

1

2

1

11.6 1

5.0 11.8 11.8 3 11.8 3 11.8 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 11.9

0.94 1.18 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20

90 80 80 80 80 80 80 80 80 80 80 80

3 3

1

1

354.61

4.60

4.00 4.60 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60

0.26-0.47 (0.34)

72 79.3 120.50

100 250 250 250

100.0 100.0 100.0 100.0

0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0

n.a. n.a. n.a. n.a.

0.00 0.00 0.00 0.00

0.0 0.0 0.0 0.0

0.00 0.00 0.00 0.00

n.a. n.a. n.a. n.a.

7.00 7.00 7.00 7.00

1-propanol 71-23-8

0.25 (0.25)

60 98 27.93

32

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

Acetaldehyde 75-07-0

(-0.22)-(-0.16) 44 (-0.19) 20 1199.7

78

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

Acetonitrile 75-05-8

(-0.39)-(-0.34) 41 (-0.37) 82 118.10

79

100.0

0.0

0.0

n.a.

0.00

0.0

0.00

n.a.

7.00

Diacetyl 431-03-8

(-1.80)-(1.30) (-1.48)

50 30 1000

100.0 100.0 99.0 99.0 98.6

0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0


0.00 0.00 1 1.00 1 1.00 4 1.40

0.0 0.0 0.0 0.0 0.0

0.00 0.00 0.00 0.00 0.00


7.00 7.00 7.00 7.00 7.00

30

200325 25 2003 25 2003 25 2003 200325 200325 25 2003 200325

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

2-Butanone 78-93-3

86 88 75.54

Bylaite Bylaite Bylaite Bylaite Bylaite Bylaite Bylaite Bylaite

0.00 0.00 1 0.02 1 0.04 0.00 0.00 1 0.02 1 0.04

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

37 37 37 37 37 37 37 37

0.0 10.0 2 10.0 2 10.0 0.0 2 10.0 2 10.0 2 10.0

4.0 4.0 4.5 4.0 2.1 4.0 4.0 5.2 5.2 2.0 2.0 4.0

1

4

78.74 60.61 1 57.14 1 60.98 1 44.84 1 35.09 1 30.86 1 32.47

2

0.1 2.0 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0

2

1

2

403.23 312.50 483.09 1 483.09 1 436.68 1 257.07 1 273.22 1 268.10 1 258.40 1 253.81 1 274.73 1 347.22

7 8 4 4 4 7 7 7 7 7 7 8

34.80 100.00 1 61.35 1 42.37

20 60 70 80

1

1

1408.45

1

Deleris** Deleris** Saint-Eve** Saint-Eve** Saint-Eve** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris**

2007 200936 200645 200645 200645 200746 200746 200746 200746 200746 200746 200936

468 469 470 471 472 473 474 475 476 477 478 479

Tehrany Jouquand Jouquand Jouquand

2007 200452 200452 200452

69

480 481 482 483 483 484

37

40 Benjamin

2011

39.90

20 Tehrany

200769

485

42.40

20 Tehrany

200769

486

25 30 7 25 30

200614 200647 46 2007 200848 200647

487 488 489 490 491

1501.50 1 79.37 1 4166.67 1 1136.36 1 888.89

Atlan Savary Deleris** Deleris** Savary



a

120 120 30 30 30 30 30

95.2 95.2 64.8 63.4 63.1 63.0 62.6

120 120 120 120 120 120 120 120 200 200 200 200 120 1000 120 120 120 120 120 120 120 120 120 120 120

91.2 91.0 90.7 90.4 90.1 90.1 90.1 90.1 90.1 90.1 90.1 90.1 89.9 81.8 88.5 87.6 85.1 85.1 85.1 82.6 82.6 81.8 80.1 80.1 80.1

1000 200 200 120 1000 120 200 200 200 4 4 4 1000 1000 1000 1000 1000 1000 1000

89.6 89.7 89.2 88.2 79.6 86.3 86.3 86.3 86.3 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5 77.5

0.0 0.0 0.0 0.0 0.0 0.0 0.0 6

4.0 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 6 4.0 2 5.4 6 6.0 6 6.0 6 8.0 6 8.0 6 8.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6 12.0 6

1

4.4 4.0 4.0 6 4.0 2 5.4 6 4.0 6 4.0 6 4.0 6 4.0 4 5.4 2 5.4 3 5.4 2 5.4 2 5.4 4 5.4 4 5.4 3 5.4 3 5.4 2 5.4 6 6

0.0 0.0 0.0 0.0 0.0 0.0 0.0


0.00 0.00 0.00 5 1.45 5 1.73 6 1.80 5 2.20

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.3 0.7 1.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 100.0 4.0 0.7 4.0 4.0 4.0 4.0 0.3 0.3 0.7 4.0 4.0 4.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 0.05 2 0.10 2 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.1 0.5 1.0 2.0 1 2.0 4.0 4.0 4.0 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0 1 4.0

4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.0 2.1 4.0 4.0 5.2 5.2 2.0 2.0 4.0

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1

4.4 4.4 2 35.0 2 35.0 2 35.0 2 35.0 2 35.0 1

1

4.3 4.5 1 4.7 1 4.9 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.1 1 5.3 3 11.6 1 4.8 1 5.4 1 5.7 1 5.7 1 5.7 1 4.6 1 4.6 1 5.2 1 6.4 1 6.4 1 6.4 1

1

5.0 5.0 5.0 1 5.0 3 11.8 1 4.9 1 4.9 1 4.9 1 4.9 3 11.8 3 11.8 3 11.8 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 12.5 3 11.9 1 1

Page 52 of 66

1

4.23 6.75 7.00 7.00 7.00 7.00 7.00

512.00 515.74 761.90 1 1000.00 1 1000.00 1 888.89 1 888.89

40 40 30 30 30 30 30

Heilig Heilig Savary Savary Savary Savary Savary

2006 200647 200647 200647 200647

492 493 494 495 496 497 498

3 3 3 3 3 3 92 92 99 3 3 57 3 80 92 3 3 3 92 3 3 3 3 3 92

6.75 6.75 6.75 6.75 6.75 1 4.23 6.75 1 4.23 6.75 6.75 6.75 6.75 6.75 4.60 6.75 6.75 6.75 1 4.23 1 4.23 6.75 1 4.23 1 4.23 6.75 1 4.23 1 4.23

647.33 563.86 1468.50 756.33 696.27 445.88 668.00 476.33 892.67 662.40 533.25 702.28 973.33 1 3225.81 1452.25 1281.00 2091.33 524.00 583.50 1310.00 466.83 416.73 6337.00 638.67 446.00

40 40 40 40 40 40 40 40 40 40 40 40 40 8 40 40 40 40 40 40 40 40 40 40 40

Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Deleris** Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig Heilig

201115 201115 15 2011 15 2011 15 2011 15 2011 * * * * * * 15 2011 36 2009 * * 15 2011 201115 * * * * 15 2011 201115 *

499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523

90 3 3 3 80 92 57 92 99 80 80 80 80 80 80 80 80 80 80

1

1

7 40 40 40 8 40 40 40 40 4 4 4 7 7 7 7 7 7 8

Deleris** Heilig Heilig Heilig Deleris** Heilig Heilig Heilig Heilig Saint-Eve** Saint-Eve** Saint-Eve** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris** Deleris**

200746 * * * 36 2009 * * * * 45 2006 200645 200645 200746 200746 200746 46 2007 46 2007 46 2007 36 2009

524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542

0.43 0.43 0.19 0.19 0.19 0.19 0.19


0.49 0.57 0.64 0.72 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.79 0.86 1.16 0.75 0.97 1.15 1.15 1.15 0.85 0.85 1.07 1.51 1.51 1.51 0.94 0.79 0.78 0.78 1.18 0.77 0.77 0.77 0.77 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20 1.20

4.00 6.75 6.75 6.75 2 4.60 1 4.23 6.75 6.75 6.75 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60 2 4.60

1

6250.00 581.97 583.80 505.74 1 2380.95 515.67 433.13 502.04 548.20 1 2392.34 1 1003.01 1 841.75 5555.56 3846.15 4545.45 3125.00 6666.67 2857.14 2941.18

* *

47

Trivial name and CAS-No. as given by the respective study’s authors; most likely CAS-No. was assigned if not given in the literature; molecular structure from http://www.sigmaaldrich.com/.


Page 53 of 66

b


range and mean of log P-values given in the reviewed studies, including log P-values from http://www.thegoodscentscompany.com/; M: molecular mass, BP: boiling point at 1013 hPa, pi0: saturated vapor pressure at 25 ° C, from

http://www.thegoodscentscompany.com/. c

(Dairy) matrix composition listing the ACC: aroma compound concentration, water content, protein content, milk fat content, CWR: casein to whey protein ratio, Thick.: thickener content, Disacc.: disaccharide content in the matrix.

d

(Dairy) matrix processing listing the DWPD: degree of whey protein denaturation, and pH.

e

Matrix/gas partition coefficient KMG, determined at the respective equilibration temperature to the right; KMG was reported in studies identified by the respective first author and the year of publication.

f

Protein originates from 1: fresh milk, 2: reconstituted skim milk powder, 3: reconstituted skim milk and whey protein concentrate powder, 4: reconstituted skim milk and sodium caseinate powder, 5: reconstituted from skim milk ultrafiltration

retentate powder, 6: reconstituted micellar casein and whey protein isolate powder g

Milk fat originates from fresh cream or 1: anhydrous milk fat.

h

If not specified in the literature, a casein to whey protein ratio CWR of 4 was assumed for dairy matrices made of fresh milk or skim milk powder, and 100 for skim milk ultrafiltration retentate powder.

i

Thickener content originates from 1: agar, 2: pectin, 3: carrageenan, 4: starch, 5: starch + carrageenan, 6: starch + pectin.

j

Disaccharide content originates from 1: lactose, 2: sucrose, 3: lactose + sucrose; if not specified in the literature, a protein to lactose ratio of 0.73 and 0.70 was assumed for (reconstituted) skim and whole milk, respectively .

k

Ash content includes added 1: CaCl2, 2: NaCl, 3: Na-citrate + Ca-citrate + K-sorbate; if not specified in the literature, a protein to ash ratio of 4.67 and 4.50 was assumed for (reconstituted) skim and whole milk, respectively .

l

19

19

If not specified in the literature, the degree of whey protein denaturation DWPD was estimated from whey protein denaturation kinetics and the heat treatment denoted in the literature .

m n

19

pH / gel set by 1: addition of glucono-δ-lactone, 2: microbial fermentation, 3: glucono-δ-lactone + rennet, 4: microbial fermentation + rennet. For studies that reported the 1: gas/matrix partition coefficient KGM, it was converted to the matrix/gas partition coefficient KMG via KMG = 1 / KGM.

* determined according to Heilig et al.15. ** KMG-values tabulated in the literature were corrected according to the respective authors’ manuscript specifications.



Page 54 of 66

Table 3: Compilation of aroma compounds reported as being non-detectable in studies using the PRV-method to determine matrix/gas partition coefficients. Trivial name

log P7

CAS-no.

BP (°C)7

pi0 (hPa)7

Decanoic acid*

6

334-48-5

4.09

269

0.00

Ethyl octanoate*

106-32-16

3.90

207

6

3.28

196

Linalool*

78-70-6

6

Octanal*

124-13-0

2.95

1,2

γ-decalactone*

706-14-9

172

2.72

267

ACC (ppm)9 3

at °C

4

10, 21, 303; 44

0.30

14

44

0.12

2

8 ;1

4

4

4

30

5

30 ; 40 ; 10, 21, 30

3

5

0.04

2.75 1

0.01

2

12-100 ; 30 ; 17

3

1

2

3

5

305

3-25

1

301

1-5

1

301

3391-86-4

6

24851-98-7

1

93-92-5

1

2.28

214

0.27

Methyl cinnamate*

103-26-41; 1754-62-72

2.18

2611; 2552

0.01

14-1201; 302; 153; 24

301; 402; 10, 21, 303; 44

Methyl anthranilate

134-20-31

2.04

240

0.02

1-51

301

0.24

1-10

1

301

10

5

180 ; 8 ; 1 ; 25

5

1

5

305 301; 10, 21, 303; 44

Oct-1-en-3-ol Methyl dihydrojasmonate Methyl benzyl acetate

2.64 2.50

1

Benzyl acetate*

140-11-4

Phenylacetaldehyde

308

1.96

6

122-78-1

214

1.78

2

Hexanoic acid

175

142-62-1

194

1.72

203

0.71 0.00

0.49 2

0.21

3

4

3-methylbutanal*

6

590-86-3

1.25

92

65.57

Vanillin*

121-33-51

1.19

286

0.00

3-251; 1083; 16

2-methyl butyric acid

116-53-02

1.13

177

0.74

1802

6

Butanoic acid

107-92-6

Furaneol

3658-77-3

118-71-8

Diacetyl* 24

209

0.07

431-03-8

Martuscelli et al.

163

0.34

6

Maltol

1

0.79

1,2

285

-1.34 2

88 15

(custards with 0 to 2.7 % milk fat); Heilig et al.

aqueous solution with 0.05 to 1.4 % of added thickeners);

4

3

3

40 ; 10, 21, 30 ; 4 ; 305

1

2

3

10, 21, 30 ; 44

3

4

30 ; 40 ; 10, 21, 303; 44

3

224 ; 33

4

10, 21, 303; 44

24

5

3-25 ; 27 ; 127 ; 19

n.a. 75.54

3

1

2

30 47

(milk protein solutions with 0 to 4 % milk fat); Savary et al. 45

Saint-Eve et al.

(stirred yoghurts with 4 % milk fat);

6

5

(water and 30

Gierczynski et al.

(water

7

and model cheese with 10 % protein and 0 % milk fat); estimated as not specified in the literature; log P, BP: boiling point at 1013 hPa, pi0: saturated vapor pressure at 25 °C, from http://www.thegoodscentscompany.com/; 8 rounded values; ACC = aroma compound concentration in the analyzed matrix; n.a. = not available; * reported to be detectable by some authors (see Table 1).

54


4

402

4

15 ; 2

2.19 0.04

305 2

5

Page 55 of 66


Table 4: Aroma compounds that were reported to be either not / less or more retained by higher fat contents. Trivial name

log Pa

CAS-no.

Less retained / no change at higher fat contents Diacetyl -1,34 431-03-8 1-propanol +0,25 Furaneol +0,34 Ethyl acetate +0,71 Butyric acid +0,79 Pyridine +0,84 Z-3-hexenol +1,61 More retained at higher fat contents (E,E)-2,4-hexadienal +1,06 Guaiacol +1,34 Benzaldehyde +1,48 Ethyl isobutanoate +1,77 t-2-hexenal +1,79 (E)-2-hexenal +1,79 Ethyl butanoate +1,85 Hexanal +1,97 Ethyl-2-methylbutanoate +2,12 2,3-diethyl-5-methylpyrazine +2,16 Ethylguaiacol +2,18 Isoamyl acetate +2,26 Amyl acetate +2,30 Ethyl pentanoate +2,30 +2,42 δ-decalactone (Z)-3-hexenyl acetate +2,42 Heptanal +2,50 (E,E)-2,6-nonadienal +2,60 (E,Z)-2,6-nonadienal +2,60 2-isobutyl-3-methoxypyrazine +2,62 1-octen-3-ol +2,64 (E,E)-2,4-nonadienal +2,65 Ethyl hexanoate +2,83 Octanol +2,88 (Z)-6-Nonenal +3,11 (E)-2-nonenal +3,17 Linalool +3,28 Nonanal +3,46 2-decanone +3,73 Ethyl octanoate +3,90 2-pentylfuran +3,97 +4,04 β-damascenone Geranyl acetate +4,10 Limonene +4,57 a

First author

71-23-8 3658-77-3 141-78-6 107-92-6 110-86-1 928-96-1

Guyot1*; Miettinen2*; Haahr42*; Deleris36*; Leksrisompong3; Roberts38*; Roberts68*; Saint-Eve45* Benjamin37* 3 Leksrisompong Weel43*; Saint-Eve45* 1 54 36 Guyot *; Nongonierma *; Deleris * Roberts68* 15 Heilig

142-83-6 90-05-1 100-52-7 97-62-1 6728-26-3 6728-26-3 105-54-4 66-25-1 7452-79-1 18138-04-0 2785-89-9 123-92-2 628-63-7 539-82-2 705-86-2 3681-71-8 111-71-7 557-48-2 557-48-2 24683-00-9 3391-86-4 5910-87-2 123-66-0 111-87-5 2277-19-2 18829-56-6 78-70-6 124-19-6 693-54-9 106-32-1 3777-69-3 23696-85-7 105-87-3 138-86-3

Haahr42* Roberts68* Roberts38* Nongonierma54* Meynier31* Haahr36* Weel43*; Nongonierma54*; Benjamin37*; Heilig15; Roberts38* Haahr42*; Nongonierma54*; Roberts38*; Meynier31* Heilig15 Roberts68* Roberts68* Meynier31* Meynier31* Meynier31* Guyot1*; Leksrisompong3 Heilig15 Benjamin37* Haahr42* Haahr42* Roberts68* Roberts68* Haahr42* Weel43*; Nongonierma54*; Deleris36*; Heilig15 Benjamin37* Haahr42* Haahr42* Miettinen2*; Deleris36* Haahr42* Benjamin37* Nongonierma54* Roberts68* Roberts38*; Roberts68* Weel43* Heilig15; Roberts68*

from http://www.thegoodscentscompany.com/; * most likely CAS-no was assigned if not given in the literature.

55



Page 56 of 66

Table 5: Boundaries for the relationship shown in Fig. 2 – 9 Parameter

Const.

log P

BP

pi0

(-)

(°C)

(hPa)

Water

Protein

Fat

CWR

Thick.

Disacc.

pH

υ

(% w/w)

(% w/w)

(% w/w)

(-)

(% w/w)

(% w/w)

(% w/w)

(%)

(-)

(°C)

80

Ash DWPD

Fig. 2 (A) Upper limit

n.a.

+4.45

269

1199.7

100.0

24.4

14.8

100.0

4.01

35.0

4.11

99

7.00

Lower limit

n.a.

-1.34

-2

0.00

62.2

0.0

0.0

0.0

0.00

0.0

0.00

3

3.50

4

P-Value

0.454

0.000

0.805

0.000

0.900

0.480

0.232

0.686

0.290

0.358

0.905

0.510

0.027

0.000

Upper limit

n.a.

+4.45

267

1199.7

100.0

24.4

14.8

100.0

4.01

35.0

4.11

99

7.00

80

Lower limit

n.a.

-1.34

-2

0.01

62.6

0.0

0.0

0.0

0.00

0.0

0.00

3

3.50

4

P-Value

0.251

0.000

0.035

0.000

0.997

0.544

0.084

0.476

0.134

0.835

0.201

0.409

0.035

0.000

Upper limit

n.a.

+3.90

267

1199.7

100.0

24.4

14.8

100.0

4.01

35.0

4.11

99

7.00

80

Lower limit

n.a.

-0.34

20

0.01

62.6

0.0

0.0

0.0

0.00

0.0

0.00

3

3.50

4

P-Value

0.024

0.000

0.000

0.000

0.136

0.816

0.021

0.843

0.084

0.858

0.213

0.418

0.211

0.000

Upper limit

n.a.

+3.90

267

1199.7

100.0

n.a.

n.a.

n.a.

2.20

35.0

0.62

n.a.

7.00

80

Lower limit

n.a.

-0.34

20

0.01

62.6

n.a.

n.a.

n.a.

0.00

0.0

0.00

n.a.

3.50

7

P-Value

0.094

0.000

0.000

0.669

0.095

n.a.

n.a.

n.a.

0.144

0.095

0.117

n.a.

0.161

0.000

Upper limit

n.a.

+3.39

214

121.1

91.2

12.0

n.a.

100.0

4.01

17.7

3.14

99

7.00

40

Lower limit

n.a.

+0.71

73

0.05

80.1

3.2

n.a.

0.0

0.00

4.3

0.49

3

4.00

8

P-Value

0.626

0.000

0.000

0.036

0.914

0.954

n.a.

0.979

0.920

0.743

0.811

0.709

0.091

0.253

Upper limit

n.a.

+4.09

269

150.0

89.6

24.4

14.8

100.0

4.01

33.4

4.11

99

7.00

40

Lower limit

n.a.

+0.71

77

0.00

63.0

3.0

0.1

2.0

0.00

4.5

0.67

3

4.00

4

P-Value

0.149

0.000

0.000

0.147

0.093

0.476

0.108

0.201

0.321

0.476

0.674

0.925

0.530

0.414

Upper limit

n.a.

n.a.

n.a.

n.a.

100.0

12.0

4.0

100.0

2.20

35.0

1.51

99

7.00

40

Lower limit

n.a.

n.a.

n.a.

n.a.

62.6

0.0

0.0

0.0

0.00

0.0

0.00

3

4.00

4

P-Value

0.000

n.a.

n.a.

n.a.

0.000

0.000

0.000

0.499

0.417

0.000

0.000

0.936

0.007

0.000

Upper limit

n.a.

n.a.

n.a.

n.a.

100.0

12.0

12.0

100.0

2.20

35.0

1,51

99

7.00

40

Lower limit

n.a.

n.a.

n.a.

n.a.

62.6

0.0

0.0

0.0

0.00

0.0

0.00

3

4.23

4

P-Value

0.307

n.a.

n.a.

n.a.

0.292

0.321

0.418

0.885

0.921

0.877

0.269

0.302

0.137

0.669

Upper limit

n.a.

n.a.

n.a.

n.a.

100.0

12.0

12.0

100.0

4.01

35.0

3.14

99

7.00

40

Lower limit

n.a.

n.a.

n.a.

n.a.

63.1

0.0

0.0

0.0

0.00

0.0

0.00

3

4.00

4

P-Value

0.000

n.a.

n.a.

n.a.

0.002

0.041

0.317

0.974

0.003

0.269

0.206

0.496

0.821

0.044

Fig. 2 (B)

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

n.a. = not applicable.

56


Page 57 of 66


Fig. 1 100000

5

BB

A 4

10000

1000

2

KMG (-)

log P (-)

3

1

100

0

10 -1 -2

1

1

Investigated aroma compounds

56

1

57

Experimentally determined KMG-values


535


Page 58 of 66

Fig. 2

12500

5000

Observed KMG (-)

A

B

7500

3000

2500

1000

-1000

-2500 -2500

2500

7500

12500

-1000

Predicted KMG (-)

58


1000

3000

5000

Page 59 of 66


Fig. 3

Observed KMG (-)

2500

1500

500

-500 -500

500

1500

2500

Predicted KMG (-)

59



Page 60 of 66

Fig. 4

1000

5000

B

Observed KMG (-)

A 750 3000 500

250 1000 0

-1000

-250 -1000

1000

3000

5000

-250

Predicted KMG (-)

60


0

250

500

750

1000

Page 61 of 66


Fig. 5

7500

1000

B

A Observed KMG (-)

750 5000 500 2500 250 0

0

-2500 -2500

-250 0

2500

5000

7500

-250

Predicted KMG (-)

61


0

250

500

750

1000


Page 62 of 66

Fig. 6

10000

10000

Observed KMG (-)

AA

B B

6000

6000

2000

2000

-2000

-2000 -2000

2000

6000

10000

-2000

Predicted KMG (-)

62


2000

6000

10000

Page 63 of 66


Fig. 7

7500

Observed KMG (-)

5000

2500

0

-2500 -2500

0

2500

5000

7500

Predicted KMG (-)

63



Fig. 8

Observed KMG (-)

2500

1500

500

-500 -500

500

1500 Predicted KMG (-)

64


2500

Page 64 of 66

Page 65 of 66


Fig. 9

Observed KMG (-)

2500

1500

500

-500 -500

500

1500

2500

Predicted KMG (-)

65



TOC

66


Page 66 of 66

Determination of Aroma Compound Partition Coefficients in Aqueous

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