Sensory evaluation of the synergism among ester odorants in light aroma-type liquor by odor threshold, aroma intensity and flash GC electronic nose

Accepted Manuscript Sensory evaluation of the synergism among ester odorants in light aroma-type liquor by odor threshold, aroma intensity and flash GC electronic nose

Yunwei Niu, Zhengmin Yao, Zuobing Xiao, Guangyong Zhu, Jiancai Zhu, Jiaying Chen PII: DOI: Reference:

S0963-9969(18)30018-8 https://doi.org/10.1016/j.foodres.2018.01.018 FRIN 7306

To appear in:

Food Research International

Received date: Revised date: Accepted date:

28 August 2017 21 November 2017 9 January 2018

Please cite this article as: Yunwei Niu, Zhengmin Yao, Zuobing Xiao, Guangyong Zhu, Jiancai Zhu, Jiaying Chen , Sensory evaluation of the synergism among ester odorants in light aroma-type liquor by odor threshold, aroma intensity and flash GC electronic nose. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Frin(2017), https://doi.org/10.1016/j.foodres.2018.01.018

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ACCEPTED MANUSCRIPT Sensory evaluation of the synergism among ester odorants in light aroma-type liquor by odor threshold, aroma intensity and flash GC electronic nose Yunwei Niua, Zhengmin Yaoa, Zuobing Xiaoa*, Guangyong Zhua, Jiancai

School of Perfume and Aroma Technology, Shanghai Institute of Technology,

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a

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Zhua, and Jiaying Chena

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Shanghai 201418, PR China * Corresponding author. E-mail: [email protected]

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Abbreviations: 3-AFC, three-alternative forced-choice; PA, phenylethyl acetate; EP,

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ethyl phenylacetate; FR, fruit recombination; BET, best-estimate threshold; FID, flame ionization detector; PCA, principal component analysis; GC-O, gas

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chromatograph-olfactometry; GC-MS, gas chromatograph-mass spectrometry; FD,

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factor dilution; OAV, odor activity value;

ACCEPTED MANUSCRIPT Abstract: Although esters were important odorants in light aroma-type liquor, it was still puzzling that sensory interaction between esters made the odor quality of light aroma-type liquor outstanding. The aim of the paper was to investigate perceptual interaction among esters. The odor thresholds of eighteen esters and 35 binary

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mixture were determined by a three-alternative forced-choice procedure. The

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relationship between odor threshold and carbon chain length of homologous ethyl

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esters was investigated. Moreover, 31 binary mixtures present either a synergistic effect or additive action. Furthermore, odor quality and odor intensity were

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determined by p/τ plot and σ/τ plot, respectively. From the p/τ plot, an ideal

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sigmoidal function for odor quality was obtained. From the σ/τ plot, for all 120 binary mixtures, just 9 mixtures were in the hyper-additivity area (σ＞1.05), and two

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were in the so-called perfect additivity area (0.95 < σ < 1.05). Almost one half (48%)

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showed compromise level. Finally, a significantly difference was observed by flash gas chromatography electronic nose (p＜0.05). Sensory analysis revealed that a

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mask effect of fruity note was occurred by adding ethyl phenylacetate at various

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levels (100, 2500, 58000ppb) to the fruit recombination and an enhancement effect of floral note was reported by adding phenylethyl acetate at low (1400ppb) or high level (11500ppb). It was noticed that sweet note was significantly enhanced by adding phenylethyl acetate at peri-threshold (3200 ppb). Keywords: perceptual interaction, three-alternative forced-choice, σ-τ plot, flash GC electronic nose, ester aroma compounds

ACCEPTED MANUSCRIPT 1 Introduction Esters were important aroma components in Chinese liquors. Generally in various aroma-type liquors, the content of esters had significantly difference and almost accounted for 35% to 70%. In the literature, esters were responsible for the

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fruity note, such as banana-fruit, pineapple-fruit. Moreover, fruity note had

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positively contributed to the overall aroma of light aroma-type liquor. For instance,

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many authors had investigated the aroma compounds in Chinese liquors by advanced analytical methods (Fan et al., 2006; Fan et al., 2011; Gao et al., 2014; Niu et al.,

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2017; ). Furthermore, Gao et al., revealed the significance of the entire group of

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esters in light aroma type liquor by omission test (Gao et al., 2014). However, was there perceptual interaction among esters? It was still a puzzle for uncovering the

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formation mechanism of aroma in liquors. To answer the question, some researchers

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investigated the interaction in wine, beer and other food filed by different sensory analysis methods in recent years.

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By using one of these sensory analysis methods to investigate perceptual

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interaction, many researchers found some basic rules in binary mixtures or more complex mixtures. These basic rules had quite impact on flavor chemistry. For instance, the determination of the odor threshold of an individual component was one way of estimating its contribution to the overall aroma of food. Several flavor threshold determinations had been made on beverage, tea, wines and common food fields. By mixing the compounds in a 1:1 ratio according to their individual thresholds, researchers had classified the interaction among aroma compounds into

ACCEPTED MANUSCRIPT four types: no-effect, masking effect, additive action and synergistic effect (Guadagni et al., 1963). Adhikari et al., determined the olfactory threshold of diacetyl, hexanal and decalactone in various matrices (Adhikari et al., 2006). The result showed that diacetyl in water was suppressed by the presence of hexanal, but

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the presence of decalactone with hexanal reversed the trend. The perception of

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diacetyl was enhanced in the binary skim milk solutions, but the trend was reversed

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in the ternary solution. The perception of hexanal was enhanced in water (binary and ternary solutions), and it was suppressed in skim milk (binary and ternary solutions).

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Decalactone showed similar trends as hexanal, except that it was suppressed in the

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presence of diacetyl in water. Zhu et al., focused on the interactions between 24 representative aroma compounds in Oolong tea infusion (Zhu et al., 2017). Results

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showed that the mixed compounds with similar structure and aroma mainly

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presented synergistic effect and additive action. Moreover, mask effect was found among compounds with different structures and aroma. Saison et al., investigated the

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contribution of staling compounds to the aged flavor of lager beer by studying their

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flavor thresholds (Saison et al., 2009). Result demonstrated that thresholds were regularly found to be substantially lower than those previously reported, and it appeared important to consider threshold values as indicative rather than absolute because of very large variations in sensitivity of individuals. Besides, as one of the most important evaluation criteria, aroma intensity (AI) judged the perceptual interaction degree of aroma compounds and their binary mixture in a more quantitative way (Kim et al., 2014; Gebicki et al., 2014; Curren et al., 2014). In order

ACCEPTED MANUSCRIPT to promote the application of AI evaluation, human assessors were supposed to be replaced and predictive AI methods had been widely explored. According to the literature, many AI prediction models had been proposed, such as Vector Model, U Model, Additivity Model, the Strongest Component Model (Cain et al., 1995;

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Rodrigues et al., 2010; Teixeira et al., 2013). Berglund et al., found that data fitted to

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the vector model with α=99 and small amounts of DMDS (dimethyl disulfide)

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suppressed the intensity of mixtures by studying the binary mixture of pyridine and DMDS (Berglund et al., 1993). Cain et al., investigated the aroma intensity of linalyl

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acetate and hexyl salicylate. Result showed that the intensity of the mixture was well

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represented by the strongest component (SC) model (Cain et al., 1995). Furthermore, Yan et al., established a modified Vector model for odor intensity prediction based on

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a detected linear relation between the odor intensity and the logarithm of odor

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activity value of individual odorant (Yan et al., 2015). Result showed that the modified vector model was applicable for odor mixtures consisted of odorants with

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the same chemical functional groups or similar molecular structures.

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However, for Chinese light aroma type liquors, the study on perceptual interactions between esters had not been reported by a careful literature inspection. Therefore, the aims of this study were (i) to determine the selected odor thresholds in liquor, and (ii) to investigate the possible interactions among ester aroma compounds in binary mixtures by determining the threshold of mixture, ( ⅲ ) to further investigate the aroma quality and aroma intensity in binary mixtures, (ⅳ) to study the possible perceptual interactions between sensory attributes by E-nose and

ACCEPTED MANUSCRIPT sensory analysis. Accordingly, the present study would provide a theoretical basis for understanding the aroma quality characteristic of light aroma type liquor and give interesting clues to liquor-makers when they would take decisions along elaboration (yeast selection, fermentation conditions, liquor blending).

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2. Materials and methods

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2.1. Chemicals

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Authentic standards were obtained from the following sources. Ethyl acetate (analytical grade, ≥97%), ethyl propionate (analytical grade, ≥97%), ethyl butyrate

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(analytical grade, ≥97%), ethyl valerate (analytical grade, ≥97%), ethyl hexanoate

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(analytical grade, ≥97%), ethyl heptanoate (analytical grade, ≥97%), ethyl octanoate (analytical grade, ≥97%), ethyl nonanoate (analytical grade, ≥97%), ethyl decanoate

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(analytical grade, ≥97%), ethyl benzoate (analytical grade, ≥97%), ethyl

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phenylacetate (analytical grade, ≥97%), ethyl 3-phenylpropionate (analytical grade, ≥97%), ethyl lactate (analytical grade, ≥97%), phenylethyl acetate (analytical grade,

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≥97%), isoamyl acetate (analytical grade, ≥97%), ethyl isobutyrate (analytical grade,

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≥97%), ethyl isovalerate (analytical grade, ≥97%), diethyl succinate (analytical grade, ≥97%) were purchased from Sigma-Aldrich (Shanghhai, China). Absolute ethanol (analytical grade, 99.97%, Sigma-Aldrich, Shanghhai) was diluted to 53% v/v with Milli-Q water (Millipore, Bedford, MA) before use. 2.2. Measurement of odor threshold The measurement of odor threshold was based on ASTM (E679-04) (2011) (ASTM standard, 2011) and previous research with minor modification (Saison et al.,

ACCEPTED MANUSCRIPT 2009). Thirteen panelists participated in this study. The panelists were informed of the nature of the additive and a standard solution was presented at the entrance to the test room. A series of test samples were prepared in 53% diluted alcohol solution by dispersing the substance whose threshold was determined in the brown glass bottle.

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Panelists were presented with six 3-AFC tests spaced by a factor of 2.0. The panel

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members started at the highest concentration step, which should be two

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concentration steps above the estimated threshold. If the panelist could recognize aroma in both trials on the same sample, the sample at the next lower concentration

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(step 2) was similarly tested, and the same test procedure was repeated for steps 3-6.

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The best-estimate threshold (BET) was calculated as the geometric mean of the last missed concentration and the next (adjacent) higher concentration. The group

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threshold was calculated as the geometric mean of the BETs. The threshold of

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mixture was usually determined by mixing the compounds in a 1:1 ratio according to their individual thresholds (Guadagni et al., 1963). All the experiments were

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performed in triplicate.

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2.3. Sensory Analyses

2.3.1. General Conditions Sensory analyses were performed as described by Martin and de Revel (Martin et al., 1999). Samples were evaluated at controlled room temperature (20℃), in individual booths, using brown glasses, containing about 10ml liquid, coded with three-digit random numbers. 2.4.2 Sensory Panels.

ACCEPTED MANUSCRIPT The thirteen volunteers (6 women and 7 men, between 18 and 30 years old) participated in the sensory experiments. They were selected from 38 candidates on the basis of their performance on several olfactory tests and absence of anosmia to the odorants used in the study. They did not declare any allergy or problem in their

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sense of smell. All subjects had previous experience in olfactory tests but they were

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not informed about the aim of the experiment. All panelists belonged to School of

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Perfume and Aroma Technology, Shanghai Institute of Technology. They attended 5 sessions per week, for 8 weeks.

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2.4.3. Stimuli

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2.4.3.1. Stimuli 1

The Stimuli 1 were 4 concentrations of ester aroma compounds, their 16

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possible combinations (mixtures), for a total of 24 unique stimuli. The set of 4

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concentrations of each substance was selected to be approximately equal in perceived intensity as determined in a pilot experiment with subjects (Atanasova, B

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et al., 2004b).

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2.4.3.2. Stimuli 2

The Stimuli 2 were 3 concentrations of phenylethyl acetate (PA) and ethyl phenylacetate (EP), the fruit reconstitution (FR) prepared with 9 ethyl esters and acetates in dilute alcohol solution at the average concentrations found in Chinese light aroma type liquors (the 9 esters out of 18 with OAV≥1) (Gao et al., 2014; Niu et al., 2017), their six possible combinations (mixtures), for a total of 13 unique stimuli.

ACCEPTED MANUSCRIPT 2.4.4. Procedure 2.4.4.1. Experiment 1 The 13 subjects were paid to take part in the experiment. The duration of each visit was 5 h. The task for the subjects was two-fold because perceived odor intensity

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and identification of perceived quality were studied simultaneously. In terms of the

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quantitative aspect, subjects had to evaluate the overall perceived odor intensity of

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the binary mixtures and the perceived odor intensity of each unmixed odorant. Intensity ratings were made using a modified 1-butanol reference scale procedure

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(Atanasova et al., 2004a). During the experiment, the subjects rated their intensity by

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using a 0−13 point structured scale, where 0 indicated that no odor was perceived and 13 indicated high intensity. At the same time, the task for the subjects during the

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experimental sessions was to judge the quality of the odor (unmixed odorant or

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mixture) by using one of four response categories (A, B, AB, or the hood). They were to say "AB" if they perceived both A and B to be present simultaneously, "A"

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or "B" if they thought that only one of them was present, and "the hood" if neither

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was there. The 24 stimuli were presented twice each session. Each stimuli sample lasted physically 20-25 seconds (depending on the subject's speed of responding). A 5-10 seconds break separated these stimuli. 2.4.4.2 Experiment 2 Various reconstitution models of Stimuli 2 in 53% v/v dilute alcohol solution were presented to subjects to evaluate sensory profiles for overall aroma, fruity, floral and sweet notes. The first glass consisted of dilute alcohol solution

ACCEPTED MANUSCRIPT supplemented with the 9 ethyl esters and acetates at the concentrations indicated in Table 3a. The second contained dilute alcohol solution supplemented with the EP or PA (individually) at the concentrations indicated in Table 3b. The third consisted of dilute alcohol solution supplemented with both the 9 ethyl esters and acetates and the

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EP or PA (individually). Each sample was presented twice during each session. For

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each sample, the subject rated the intensity of four descriptors (overall aroma, fruity,

the left and “very intense” on the right.

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2.5 Heracles flash GC electronic nose detection

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floral, and sweet) on a 13 cm scale printed on paper, labeled “no odor perceived” on

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The HERACLES electronic nose (Alpha M.O.S., Toulouse, France) was applied to monitor the aroma change between different reconstitutions. This instrument,

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which had the ability to perform complete data treatment, was integrated with

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classical GC functionalities and E-Nose olfactive fingerprint software. It consisted of a sampling system, a detector system containing two short columns of different

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polarity coupled to two flame ionization detectors (FID) for a global fingerprint and

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a data acquisition and processing system (Alpha MOS proprietary software (Alpha Soft)) which used multivariate statistical analysis and chemo-metrics to acquire, compute and interpret electronic nose measurements. 1 g reconstitution solution was placed in 20 ml headspace vials and capped with a Teflon faced silicon rubber cap. Each vial was incubated at 50℃ for 20 min. The accumulated gas in the headspace was then injected into GC with 2 m × 0.18 mm MXT-5/MXT-1701 (Tenax trap) for C7–C30. The carrier gas, hydrogen, was

ACCEPTED MANUSCRIPT circulated at 1 ml/min in the constant flow mode. The injected volume was 5000μL and the injector temperature 200℃. The oven temperature program was as follows: 50℃ for 2 s, 1℃/s ramp to 80℃and then 3℃/s ramp to 250℃, holding for 15s. The two flame ionization detectors temperature was 260℃. The parameters were

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optimized in details and each analysis was repeated four times.

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2.6 Data analysis

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The scores obtained for each attribute was submitted to two-way analysis of variance (judges as random and models as fix factors). Further Principal Component

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Analysis (PCA) was calculated with the mean intensity scores over the panelist for

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the three attributes. All statistical analyses were performed using XLSTAT (Addinsoft, version 2015). All descriptors are mean-centered per panelist and scaled

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to unit variance. Origin data from electronic nose and sensory data were analyzed by

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one-way analysis of variance (ANOVA) by use of SPSS v20.0 (SPSS Inc., Chicago, IL). The statistically significant level was 5% (p < 0.05).

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Experimental data were also reported on a graph based on two parameters [σ = f

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(τ)] for binary mixtures, as proposed by Patte and Laffort (Patte et al., 1979). τ refers to the ratio of perceived intensity of unmixed B (or of A) in the mixture, τ A = IA/(IA+IB) or τB = IB/(IA+IB). σ reflects the ratio between the perceived intensity of the mixture and the sum of the perceived intensities of its components, prior to mixing, and reflects the level of interaction: σ = Imix/(IA+IB). The mean experimental results for the panel were presented using the synthetic representation σ = f (τ). The graph was divided into several parts, according to the interaction level. The position

ACCEPTED MANUSCRIPT of experimental points reflected the interaction level. Cain and Drexler referred to mixture interactions in terms of the overall perceived intensity of a mixture compared to the intensity of each separate component. These authors specified several cases of perceived strength of a mixture (Cain et al., 1974). First, the

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intensity might be as strong as the sum of the perceived intensities of the unmixed

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components, exemplifying complete addition (σ = 1). The intensity might be also

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more intense than the sum of its components, exemplifying hyper-addition (σ > 1), or less intense than the sum of its components, exemplifying hypo-addition (σ < 1).

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In addition, Frijters differentiated three cases of hypo-addition: the terms “partial

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addition”, “compromise”, and “subtraction” were used if the quality intensity of the mixture was greater than, intermediate to, or smaller than that of the individual

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compounds (Frijters et al., 1987). For each sample, the significance of the observed

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perceptual interaction was statistically tested by calculating the 95% confidence interval on the mean intensity of the 13 subjects for both σ and τ.

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3 Result and discussion

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3.1 Selection of eighteen ester aroma compounds According to previous studies on light aroma type liquors conducted by the aroma reconstitution and omission tests (Gao et al., 2014), the result revealed the significance of the entire group of esters. Further study on five light aroma type liquors (Niu et al., 2017), a total of 80 odorants were identified by GC-O (gas chromatograph-olfactometry) coupled with GC-MS (gas chromatograph-mass spectrometry). In addition, aroma-active compounds (FD≥16) were further screened

ACCEPTED MANUSCRIPT out as the key aroma compounds according to quantitative study and odor activity values (OAV). Finally eighteen important esters in liquors were selected to evaluate the perceptual interactions among them by combining OAV with the partial least squares analysis. Based on the differences in sensory attribute, these compounds

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could be separated into three categories: fruity, floral, sweet notes.

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3.2 Threshold determinations and perception interaction between aroma compounds

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As shown in Table 1, there were significant differences between the referenced and determined threshold values. None of the ratios of these two values was

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consistent. Overall, it is obviously observed that the detection threshold of each ester

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compounds in 53% v/v dilute alcohol solution was higher than that in 46% v/v dilute alcohol solution. It was concluded that there was a significantly mask effect as the

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increase of alcohol content. The possible cause was that the aroma of alcohol would

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mask fruity and floral attributes in esters. Berre et al., assessed the impact of alcohol on the perception of mixtures of woody (whiskey lactone) and fruity (isoamyl

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acetate) odorants in wines (Berre et al., 2007). They found that a reduction in alcohol

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content in wine could affect the aromatic bouquet, especially by reinforcing perceptual interactions between woody and fruity wine odorants. Moreover, it was reported that ethanol had a significantly low odor threshold and mean olfactory thresholds were approximately 0.01% v/v (Cometto-Muniz et al., 1990). Therefore, it was supposed that the olfactory thresholds in alcohol solution of odorants would be increased as the concentration of alcohol increased. In addition, the relationship between odor threshold and carbon chain length of

ACCEPTED MANUSCRIPT homologous ethyl esters was investigated. The result showed that the odor threshold of homologous ethyl esters gradually decreased as the carbon chain length increased. Some cases could be found from Table 1, such as ethyl acetate (423285.35μg/L), ethyl propionate (41976μg/L), ethyl butyrate (1574μg/L), ethyl pentanoate

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(723.85μg/L), ethyl benzoate (40104μg/L), ethyl phenylacetate (2538.62μg/L), ethyl

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phenylpropionate (1875μg/L). Cometto-Muniz et al., studied the characteristics that

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threshold of four linear alcohols (Ethanol, n-butanol, n-hexanol and n-octanol) as the carbon chain length changed, it was pointed that concentration-detection functions

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for the odor of homologous n-alcohols shifted towards lower concentrations with

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increasing carbon chain length (Cometto-Muniz J.E et al., 2008). Yi et al., measured the odor threshold of 5 series of organic compounds including alcohols, aldehydes,

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ketones, acids and mercaptans by 3-AFC, and the good linear relations between

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logarithmic values of odor threshold and carbon chain length were concluded by mathematical formula (Qin Y et al., 2013).

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Although the threshold of a compound gives a good indication of its olfactory

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impact, it would be insufficient and oversimplified to consider the overall liquor flavor as the sum of contributions made by each individual compound, since several interactions affecting odor perception could be neglected. Therefore, the impact of binary mixtures was evaluated by determining their thresholds. Compounds were added in the ratio of their individual thresholds in order to evaluate the interactions at the same level of sensory activity. The ratio (%) of the determined threshold value of a compound in the mixture to the original threshold of the compound was used to

ACCEPTED MANUSCRIPT represent the degree of perceptual interaction. Four possible interactions might occur (Saison et al., 2009). Firstly, the compounds could exhibit their flavor independently, which meant that each compound had to be present at 100% of its individual threshold. “No-effect” was occurred between compounds. Secondly, mask effect was

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occurred that they could counteract each other (antagonism), which meant that the

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threshold of the mixture of compounds was greater than 100% of the threshold of the

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single compound. Thirdly, they could exhibit addition effect, which suggested that the threshold of the mixture was 50% of that of the single compound. Finally,

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synergistic effect would be appeared that the threshold of the mixture was less than

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50% of the individual compound thresholds (Guadagni et al., 1963). In this experiment, thirty-five binary mixtures were investigated as shown in Table 2.

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There were nineteen binary mixtures which showed synergistic effect. It was

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obviously noted that nine pairs with similar structure and similar aroma had a strong synergistic effect. In addition, five pairs with similar aroma and dissimilar structure

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also showed strong synergistic effect. Similar conclusion had been reported by other

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authors (Saison et al., 2009; Zhu et al., 2017). Therefore, compounds with similar structures or aroma seemed to present either a synergistic effect or additive action; however, this did not mean that all homologues could present a synergistic effect after mixing. For instance, although ethyl octanoate and ethyl decanoate, ethyl propionate and ethyl heptanoate, phenylethyl acetate and ethyl phenylacetate had similar aroma, they produced a masking effect after being mixed. The reason for this remained unclear and was deemed to warrant further research.

ACCEPTED MANUSCRIPT Moreover, weak additive action was found among compounds with different structures. For instance, the ratios of ethyl hexanoate and phenylethyl acetate, phenylethyl acetate and ethyl 3-phenylpropionate were 74.80% and 72.28%, respectively. However, it was not observed that a mask effect occurred when two

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components with different aroma or structure mixed. It was not agreement with the

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conclusion that the compounds with different structures usually demonstrated

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masking action (Zhu et al., 2017). The possible cause for the phenomenon was that these 18 compounds investigated in the study had the same functional groups. In the

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literature (Zhu et al., 2017), the odorants of most binary mixtures with mask effect

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generally were of different functional groups, such as (E)-2-hexenal and ethyl acetate (169%), 2-methylbutanal and butyl acetate (149%), 2,5-dimethylpyrazine and

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(E)-2-hexenal (138%).

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3.3 Perceptual interaction of the binary mixture at various concentrations 3.3.1 Odor quality interaction

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In order to monitor the qualitative change of the perception of the mixture as its

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components were changed in intensity, the probabilities of identifying the mixtures as A, B, and AB were determined. For this purpose, the p/τ approach would be applied to experiments that measured the probabilities of the individual components within the mixture. According to an interaction model for odor quality by Olsson (Olsson et al., 1994), a direct and simple way to estimate the size of these probabilities was the following: P(a)=Ia2 / (Ia2+Ib2) and P(b)=Ib2 / (Ia2+Ib2). In Figure 1, there were five

ACCEPTED MANUSCRIPT odor pairs it was first of all noteworthy that the concordance between the P (a) and P (b) predicted by the interaction model and the empirical P (a) and P (b) was obvious. Second, when the binary mixtures contained two odorants at different intensity levels (quite τ different to 0.5), the high intensity level compound (in isolation)

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would dominate the odor characteristics of the mixture or even would be the only

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odorant perceived in the mixture. The smell of the low level odorant would be

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partially or even completely masked (or suppressed) by the high level. Therefore, it was accordance with the literature (Vicente Ferrieira, 2012b). The author confirmed

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the intensity ratio of the mixture constituents was the main driver of quality, so that

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the most intense compound tends to dominate the overall odor of the mixture. Third, as shown in Figures 1a, 1b, 1c, 1d and 1e, the relationship between p and τ was one

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of sigmoidal type, and it was not lineal. It was meant that the change in the odor

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quality of a mixture was relatively sharp as noted by Latin (D. G. Laing et al., 1984). Furthermore, it was reported that those functions were known as concentration

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detection functions or psychometric functions and had been obtained for a limited

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number of odorants and a yet more limited number of mixtures (Cometto-Muniz et al., 2009; Miyazawa et al., 2009; Cometto-Muniz et al., 2010). An ideal sigmoidal function for odor quality was obtained from our experimental data. In the arithmetic form:

P

1 1  exp[(   0) / D]

Where P is the probability of detecting A or B in binary mixture, τ is the intensity ration of one of the components in the mixture. τ0 is the intensity ration of components at equal intensity level. D

ACCEPTED MANUSCRIPT is a parameter that defines the steepness of the function.

In all tested cases the model had fitted experimental data satisfactorily without any evidence of lack of fit. In addition, according to the literature (Vicente Ferrieira, 2012b), the steepness (D) of these functions was similar for all binary mixtures.

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3.3.2 Odor intensity

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Four principles of odor-intensity interaction had received special attention in

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previous work (Berglund et al., 1993). First principle is level independence. Second principle is hypo-additivity. Third principle is symmetry. A fourth principle of

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odor-intensity interaction is the possibility that a mixture may be weaker than the

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strongest of its components (Cain et al., 1974; Berglund et al., 1993). This is referred to as compromise.

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The mean experimental data from the panel were presented using the synthetic

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representation σ = f (τ). Data concerning mixtures of: (a) ethyl acetate and ethyl hexanoate; (b) ethyl acetate and phenylethyl acetate; (c) ethyl propionate and ethyl

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phenylacetate; (d) ethyl hexanoate and phenylethyl acetate and (e) phenylethyl

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acetate and ethyl phenylacetate are shown in Figures 2A, 2B, 2C, 2D and 2E, respectively.

Hypo-addition was most commonly observed, i.e. mixtures intensity was perceived to be weaker than the sum of the components intensities. Hypo-addition was a quite systematic phenomenon in binary mixtures (Atanasova et al., 2004b). It was pointed that a tendency to hyper-addition was observed in iso-intense mixtures only at the lowest intensity level. Moreover, for all 120 binary mixtures, just nine

ACCEPTED MANUSCRIPT mixtures were in the hyper-additivity area (σ＞1.05), and two were in the so-called perfect additivity area (0.95 < σ < 1.05). Furthermore, most mixtures in the hyper-additivity area were observed when mixing low iso-intensities of the two components (τ = 0.34 for the ethyl acetate/ethyl hexanoate mixture, τ = 0.47 for the acetate/phenylethyl

acetate

mixture,

τ

=

0.46

for

the

ethyl

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ethyl

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hexanoate/phenylethyl acetate mixture, τ = 0.39 for the phenylethyl acetate/ ethyl

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phenylacetate; Figures 2A-2E). Perfect addition and synergy were restricted to some

by Laing (D. G. Laing et al., 1984).

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very exceptional cases. For instance, cases of hyper-addition were noticed previously

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According to Berglund and Olsson the level independence principle was usually observed in perceptual quantitative interactions between odorants in a mixture. This

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principle was supported that the degree of additivity (σ) would be the same for

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combinations of two strong odors as for two weak odors (Berglund et al., 1993). And it had been measured for mixtures of equally strong components (IA=IB) in previous

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studies. However, other authors (Laing et al., 1984; Atanasova et al., 2004b) agreed

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that the principle was not supported when σ is the same for close values of τ. They found that their experimental data was in contradiction with the level independence principle. Thus, for the five types of mixtures in this study, when mixing two approximately iso-intensity odorants, the mixtures led to statistically different σ. For example, for ethyl acetate/ethyl hexanoate mixtures, there was an overlap of the 95% confidence intervals on τ four approximately iso-intense mixtures [A1B1 (τ = 0.34, σ = 1.80); A2B2 (τ = 0.38, σ = 0.92); A3B3 (τ = 0.43, σ = 0.55); A4B4 (τ = 0.48, σ =

ACCEPTED MANUSCRIPT 0.49); Figure 2A] but there was an overlap of the 95% confidence intervals on σ (A3B3 [σ = 0.55] and A4B4 [σ = 0.49]). In addition, as can be seen in Figure 2A-2E, the existence of asymmetry was relatively frequent. The conclusion was accordance with previous literature (V.

PT

Ferreira., 2012a). V. Ferreira agreed that some odor pairs in which differences in

of heptyl

acetate/ethyl

salicylate

(Thomas-Danguin

et

al., 2002),

SC

cases

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hedonic tones were not clear and asymmetry was yet present. This happens in the

pyridine/DMDS (Berglund et al., 1993). Moreover, the hypothesis was supported by

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these five odor pairs in our study. According to Berglund et al., result demonstrated

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that compromise was a quite characteristic phenomenon for binary mixtures (Berglund et al., 1976). However, for the 80 binary mixtures tested in this study,

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almost one half (48%) showed compromise level. It was obvious that the

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characteristic phenomenon commonly happened at low τ or at high τ level. The conclusion was accordance with other authors (Cain et al., 1995; Atanasova et al.,

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2004b). When the components of binary mixtures mixed at different intensity level,

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compromise was usually occurred, which was in contradiction with the conclusion as noted by Berglund and Olsson (Berglund et al., 1993). The act of physical addition hereby gave rise to a perceptual reduction. Meanwhile, these binary mixtures fitted the definition of compromise were the ones that most frequently were confused with the background-air stimulus and might therefore be disregarded. The conclusion was accordance with the previous report (Olsson M. J., 1994). More importantly, from the five odor pairs perception point of view, the

ACCEPTED MANUSCRIPT hyper-additivity was usually observed when these odor pairs were at peri-threshold or threshold level. This was consistent with the result of the threshold determination for mixed mixture and individual component. J. A. Gottfried agreed that the enhancement would take place when the odor nuances introduced by the

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sub-threshold or peri-threshold odorants help in making the overall odor of the

RI

mixture to become closer to a well-defined odor object (J. A. Gottfried et al., 2009).

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V. Ferreria explained four main red wine aroma nuances by investigating sensory interactions between six common aroma vectors at low level and high level

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concentrations (V. Ferrieira et al., 2016). In addition, as the increase of τA, degree of

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additivity (σ) of these esters with fruity note (such as ethyl acetate, ethyl hexanoate) was enhancement in binary mixture. On the contrary, degree of additivity (σ) of

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these esters with floral note (such as phenylethyl acetate and ethyl phenylacetate)

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seemed to be suppressed. However, to investigate these effects, further experiment was conducted by adding phenylethyl acetate and ethyl phenylacetate at three

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different concentrations to the fruity esters pool.

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3.4 Modulation of the fruit reconstitution (FR) solution by floral-note and sweet-note ester compounds addition. As shown in Figure 3a and 3b, the comparison of chromatograms showed significant differences in volatile compounds profile between these different mixture models. Adding EP or PA at different concentration levels to the FR solution, the FR with high level EP or PA clearly showed higher odor intensity than the FR solution. It could be demonstrated that there was a significant difference on odor intensity

ACCEPTED MANUSCRIPT between FR and six mixed models. And to verify this conclusion, descriptive sensory analysis was conducted by sensory panel. The specific sensory effects of PA and EP (floral and sweet notes) on the aroma properties of six mixed models were further studied by descriptive analysis. Six

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different mixed models were characterized by using three different sensory

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descriptors. The results were summarized in Fig. 4, which showed the

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two-dimensional PCA biplot with the projection of the three descriptors and these models. Moreover, the first PC explained 96.40% of the original variance and

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showed a clear opposition between fruity note and floral/sweet note.

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As shown in Fig. 4, the increase of EP and PA caused in all cases displacements of these models toward the left of the biplot (lower values of PC1). The plots shown

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in Fig. 5 and Fig. 6 could help to understand these effects. When increasing the

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concentration of EP at the low level (100ppb), it could bring about significant increases in the overall aroma (P＜0.05) and floral attribute (P＜0.01) as shown in

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Fig. 5a. Differently, in the Fig. 5c, a non-significant increase (P > 0.05) in the

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intensity of the overall aroma and floral note was observed upon addition of EP at high level (58000ppb). The observation was in agreement with results showing the effect of sub-threshold or peri-threshold levels of some odorants on the intensity or even quality of odorants at supra-threshold levels. Zhu et al., indicated that the grassy aroma of the tea infusion with adding (E)-2-hexenal at sub-threshold level (0.03ppm) had significantly increased (Zhu et al., 2017). Similar effects were noted upon addition of sub-threshold levels of γ-hexalactone to a jasmine tea infusion,

ACCEPTED MANUSCRIPT whose aroma sweet and astringent notes were enhanced (Y. Ito et al., 2005). It was remarkable that the PA seemed to affect in a similar way to the overall aroma perceptions. It was interesting behavior that there was a significantly increase on the intensity when adding PA with low level (1400ppb) or medium level (3200ppb) to

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the FR solution. In addition, the significantly decrease in the fruity note was found

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when adding EP or PA at medium level (2500ppb, 3200ppb respectively).

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The second factor of the PCA (31.41 % of original variance) was mainly driven by the floral attribute (Fig. 4). A clear shift upwards of all models was observed,

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which could be attributed to increases in the floral note in the presence of EP or PA.

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It was confirmed that increases in floral note were significant (P < 0.05) for the FR_low EP (Fig. 6a), FR_medium EP, FR_medium PA and FR_high PA (Fig. 6c)

D

models, but not for the FR_high EP or FR_low PA model.

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As reported previously, fruity and floral aroma had been identified as dominated quality and liking drivers for typical light aroma type liquor by some authors (Gao et

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al., 2014; Niu et al., 2017). Accordingly, the results observed in the present paper

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further demonstrate that EP or PA was essentially beneficial to liquor quality. These results revealed that when EP or PA was added to a mixture with ethyl esters and acetates, they contributed to increasing floral note and overall aroma in all models. In some cases, when EP or PA at sub-threshold level (100ppb, 1400ppb) was added to the FR solution, it was observed that perception of fruity note attenuated. It would contribute to improvement of aroma quality and further explained the mechanism between the formation of aroma characteristics and ester aroma compounds.

ACCEPTED MANUSCRIPT 4 Conclusions The present work confirmed the odor threshold of eighteen esters on 53% v/v diluted alcohol solution, and further demonstrated the perceptual interaction in nineteen binary mixtures by the method of 3-AFC. Most binary mixture (about 90%)

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with similar structures or aroma present either synergistic effect or additive action.

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Odor quality and intensity experiment was shown that perception of

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components in binary mixtures was primarily determined by their perceived (unmixed) intensities. From the p/τ plot, the observation confirmed that the odor

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quality of five binary mixtures was most similar to the strongest (unmixed)

MA

component. And an ideal sigmoidal function for odor quality was obtained according to the experimental data and previous experience. Besides, odor intensity

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interactions in five odor pairs were studied in laboratory conditions by sensory

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analysis. From the σ/τ plot, hypo-addition action was frequent in binary mixture and hyper-addition action would be occurred at low level intensity (generally τ＜0.5).

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Level independence was not observed in studied five binary mixtures. All odor pairs

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exhibited asymmetry in our study and almost one half (48%) showed compromise level. Moreover, when these odor pairs were at peri-threshold level, the hyper-additivity was usually observed. Finally, the olfactory impact was observed by descriptive sensory analysis and flash GC E-nose when adding EP (100 ppb, 2500 ppb, 58000 ppb) or PA (1400 ppb, 3200 ppb, 11500ppb) to the FR solution models. The result showed that both compounds could enhance the overall aroma intensity in models and modified the qualitative perception of FR. It was interesting behavior

ACCEPTED MANUSCRIPT that the perception tended to floral note when adding EP (100 ppb) or PA (1400 ppb) at sub-threshold level to FR solution. In addition, a radar graph was automatically generated by the built-in software of the E-nose system. As could be seen, there were obvious differences before and after the addition of EP or PA. And it was approved

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that the sub-threshold or peri-threshold concentration of EP and PA in Chinese light

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aroma type played an essential role on significantly change of the aroma quality.

SC

Acknowledgement

This work was supported by the National Natural Science Foundation of China

NU

[grant numbers 2147614090]; National Key Research and Development Program

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Nanotechnology Specific Project [grant numbers 2016YFA0200304]; and Shanghai Engineering Technology Research Center of Fragrance and Flavor [grant numbers

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15DZ2280100].

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ACCEPTED MANUSCRIPT Figure 1. The p/τ representations of two pairs of binary mixtures. (a) Ethyl acetate/ethyl hexanoate pair. (b) Ethyl acetate/phenylethyl acetate pair. (c) ethyl hexanoate/phenylethyl acetate pair. (d) Ethyl propionate/ethyl phenylacetate pair. (e) ethyl phenylacetate/phenylethyl acetate pair. Prep pa, the predicted probability of compound A; Prep pb, the predicted probability

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of compound B; pa, the experimental probability of compound A; pb, the experimental probability of compound B

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Figure 2. The σ/τ representations of two pairs of binary mixtures. (A) Ethyl

SC

acetate/ethyl hexanoate pair. (B) Ethyl acetate/phenylethyl acetate pair. (C) ethyl

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hexanoate/phenylethyl acetate pair. (D) Ethyl propionate/ethyl phenylacetate pair. (E) ethyl phenylacetate/phenylethyl acetate pair. Error bars indicate the 95% confidence

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interval on the mean for both τ and σ. A1-A4, stands for four concentrations of compound A from low to high. B1-B4, stands for four concentrations of compound

D

B from low to high.

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Figure 3a. Aroma profile of FR solution adding PA from low concentration to high concentration by E-nose. FR, fruity recombination; low PA, low concentration of

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phenylethyl acetate; medium PA, medium concentration of phenylethyl acetate; high PA, high concentration of phenylethyl acetate

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b. Aroma profile of FR solution adding EP from low concentration to high concentration by E-nose. FR, fruity recombination; low EP, low concentration of ethyl phenylacetate; medium EP, medium concentration of ethyl phenylacetate; high EP, high concentration of ethyl phenylacetate Figure 4. Biplot showing the projection of the aroma descriptors and FR models on the first two principal components of the PCA space. Six FR models containing PA or EP from low level to high level were projected. FR, fruity recombination; FR_low EP, fruity recombination with low concentration of ethyl phenylacetate; FR_medium EP, fruity recombination with medium concentration of ethyl phenylacetate;

ACCEPTED MANUSCRIPT FR_high EP, fruity recombination with high concentration of ethyl phenylacetate. FR_low PA, fruity recombination with low concentration of phenylethyl acetate; FR_medium PA, fruity recombination with medium concentration of phenylethyl acetate; FR_high PA, fruity recombination with high concentration of phenylethyl

PT

acetate.

Figure 5. Aromatic impact of EP added to FR in dilute alcohol solution from low

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level to high level. *, p < 0.05 on the centered and scaled values. **, p < 0.01 on the

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centered and scaled values. Error bars indicate standard error deviation. FR, fruity recombination. FR_low EP, fruity recombination with low concentration of ethyl

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phenylacetate. FR_medium EP, fruity recombination with medium concentration of ethyl phenylacetate. FR_high EP, fruity recombination with high concentration of

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ethyl phenylacetate.

Figure 6. Aromatic impact of PA added to FR in dilute alcohol solution from low

D

level to high level. *, p < 0.05 on the centered and scaled values. **, p < 0.01 on the

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centered and scaled values. Error bars indicate standard error deviation. FR, fruity recombination. FR_low PA, fruity recombination with low concentration of

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phenylethyl acetate. FR_medium PA, fruity recombination with medium concentration of phenylethyl acetate. FR_high PA, fruity recombination with high

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concentration of phenylethyl acetate.

ACCEPTED MANUSCRIPT Table 1 Odor thresholds of eighteen selected compounds from experiment and literature with aroma description Table 2 Threshold values of binary mixtures of compounds in the ratio of their individual thresholds (TH) with aroma description. Table 3a Nine ethyl esters and acetates concentrations used for sensory analyses

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Table 3b Amount of phenylethyl acetate and ethyl phenylacetate added to FR for

AC

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D

MA

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SC

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sensory profiles

ACCEPTED MANUSCRIPT Table 1 Odor thresholds of eighteen selected compounds from experiment and literature with aroma description Threshold

Threshold Descriptor

(Literature,

Determined,

μg/L)

μg/L

a

1

ethyl octanate

fruity

13

2

ethyl hexanoate

pineapple

55

3

ethyl isovalerate

fruity

7

4

ethyl acetate

fruity

32600

5

ethyl decanoate

coconut

1122

6

ethyl butyrate

pineapple

7

isoamyl acetate

banana

8

ethyl isobutyrate

fruity

9

phenylpropionate

5208

PT

Compound

SD b 198

3017

196

96

8

423285

21164

13516

541

81

1574

126

94

1212

24

57

354

25

125

1875

94

27

724

17

sweet, floral

908

3201

288

SC NU

MA

fruity, honey,

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No

floral ethyl pentanoate

acetate

PT E

phenylethyl 11

fruity

D

10

ethyl nonanoate

fruity

3150

33142

2320

13

ethyl heptanoate

fruity

13153

16730

1004

14

ethyl lactate

fruity

128083

1409590

84575

15

ethyl propionate

pineapple

19019

41976

3358

ethyl benzoate

fruity

1433

40104

2406

ethyl

sweet, honey, 406

2539

178

phenylacetate

floral

diethyl succinate

fruity

353193

510850

40868

AC

16

CE

12

17 18 a

The thresholds of compounds referred to literature (Niu Y. et al ,2017).

b

The standard deviation of thresholds of compounds investigated in experiment.

ACCEPTED MANUSCRIPT Table 2 Threshold values of binary mixtures of compounds in the ratio of their individual thresholds (TH) with aroma description. No

Binary mixture

Aroma description

Ratio a

SD b

pineapple, alcoholic, fruity

27.10%

2.50

Similar aroma and structure ethyl butyrate 1

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3.60

148.20%

13.70

fermentation, fruity

40.90%

2.50

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ethyl isovalerate

48.59%

4.50

21.84%

2.00

whisky, fruity

22.22%

1.70

pineapple, coconut

22.16%

2.10

pineapple

142.47%

10.30

caramel, fruity

21.29%

1.50

pineapple, alcoholic

32.38%

2.70

fermentation

30.57%

1.90

fermentation, pineapple

27.59%

2.20

ethyl octanoate 2

alcoholic, pineapple

37.68%

ethyl octanoate 3

coconut, alcoholic

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ethyl decanoate ethyl acetate 4 ethyl butanoate ethyl acetate 5

fermentation, alcoholic

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ethyl nonanoate ethyl heptanoate 6

fruity, coconut

ethyl heptanoate

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D

ethyl decanoate 7

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ethyl hexanoate

ethyl octanoate

ethyl propionate 8

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ethyl decanoate

ethyl propionate 9

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ethyl heptanoate ethyl propionate

10

ethyl nonanoate

ethyl heptanoate 11 ethyl nonanoate ethyl propionate 12 ethyl acetate 13

ethyl acetate

ACCEPTED MANUSCRIPT ethyl hexanoate Similar aroma but different structure ethyl phenylacetate 14

floral, rose, sweet

192.94%

16.40

pineapple, alcoholic

43.04%

4.20

phenylethyl acetate ethyl hexanoate 15

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phenylpropionate diethyl succinate 16

fermentation, fruity

34.36%

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ethyl acetate

61.21%

5.80

30.32%

3.10

banana

51.98%

4.90

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ethyl lactate 17

fruity

banana

58.45%

5.60

pineapple, banana

53.74%

5.10

apple, banana

37.42%

3.20

alcoholic

84.47%

8.10

alcoholic

27.07%

2.10

fruity

9.14%

0.40

sweet, floral

57.63%

3.90

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ethyl acetate ethyl nonanoate 18

banana, fruity

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isoamyl acetate ethyl propionate 19 isoamyl acetate ethyl octanoate 20 ethyl hexanoate

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D

isoamyl acetate 21

3.50

isoamyl acetate

ethyl isovalerate 22

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isoamyl acetate

ethyl nonanoate 23

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ethyl lactate

ethyl benzoate

24

ethyl lactate

ethyl benzoate 25 ethyl propionate Different aroma and structure ethyl acetate 26 phenylethyl acetate

ACCEPTED MANUSCRIPT ethyl hexanoate 27

fruity, sweet

74.80%

6.70

honey, alcoholic

68.77%

6.40

sweet, fruity

54.62%

5.30

phenylethyl acetate ethyl nonanoate 28 ethyl phenylacetate ethyl propionate 29

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phenylethyl acetate ethyl benzoate 30

sweet, fruity

50.00%

81.19%

7.70

honey, sweet, fruity

13.67%

0.60

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sweet, alcoholic

alcoholic, sweet

30.08%

2.90

72.28%

7.10

106.03%

9.70

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ethyl phenylacetate ethyl propionate 32

4.90

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diethyl succinate 31

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phenylethyl acetate

ethyl phenylacetate ethyl lactate 33 ethyl phenylacetate phenylethyl acetate 34

fruity, sweet

D

phenylpropionate

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Similar structure but different aroma ethyl phenylacetate 35

honey, fruity

phenylpropionate

Threshold values of mixtures of compounds in the ratio of their individual

thresholds.

The standard deviation of thresholds of mixtures compounds

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b

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a

ACCEPTED MANUSCRIPT Table 3a Nine ethyl esters and acetates concentrations used for sensory analyses Compounds

concentration (mg/L)

1

ethyl octanoate

30

2

ethyl hexanoate

50

3

ethyl isopentanoate

2

4

ethyl acetate

1000

5

ethyl decanoate

6

ethyl butanoate

7

isopentyl acetate

8

ethyl isobutanoate

9

ethyl pentanoate

PT

No.

30

RI

2

AC

CE

PT E

D

MA

NU

SC

1.5 0.3 1

ACCEPTED MANUSCRIPT Table 3b Amount of phenylethyl acetate and ethyl phenylacetate added to FR a for sensory profiles PA c

amount added to FR to produce a low concentration (μg/L)

100

1400

amount added to FR to produce a medium concentration (μg/L)

2500

3200

amount added to FR to produce a high concentration (μg/L)

58000

11500

CE

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D

MA

NU

SC

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FR, fruity reconstitution; b EP, ethyl phenylacetate; c PA, phenylethyl acetate.

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a

PT

EP b

ACCEPTED MANUSCRIPT Highlights:

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  

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

The relationship between odor threshold and carbon chain length of homologous ethyl esters was investigated. The perceptual interaction was related with the structure or aroma of compounds. An ideal function of odor quality was obtained from experimental data. Four principle basic rules were verified by five odor pairs Sub-threshold level compounds had a significantly impact on the overall aroma of the FR solution.

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

Graphics Abstract

Figure 1

Figure 2r1

Figure 2r2

Figure 3r1

Figure 3r2

Figure 4

Figure 5

Figure 6