研究将智能感官分析技术与传统感官评价相结合,采用回归分析、相关性分析的数据分析方法,探究在不同餐酒搭配过程中白酒消费者喜好度,喜好度与脑电波和面部表情情绪的相关性,以及消费者在餐酒搭配前后对菜品味觉感受的变化,与各搭配喜好度、香气喜好度、口感喜好度、综合喜好度、购买意愿及推荐度之间相关性。研究结果表明,不同的餐酒搭配后,味觉强度变化呈现异质性,清雅型与豉香型白酒和酸味、苦味、辣味菜品搭配后味觉强度均有所提升,且鲜味强度变化越大,消费者越倾向于向别人推荐豉香型白酒。甜味强度变化越大,消费者越喜欢甜味菜品和豉香型白酒的搭配。清雅型白酒与甜味菜品搭配时消费者喜好度最高,豉香型白酒与咸味菜品搭配时消费者喜好度最高。线性回归模型相关R值在0.49~0.76之间,且P值均小于0.05,拟合度良好,说明智能感官分析技术与传统感官评价相结合的方法能够有效地分析不同餐酒搭配时的白酒消费者喜好度。该研究为提高餐酒搭配喜好度奠定了科学理论基础。
The study combined intelligent sensory analysis technology with traditional sensory evaluation and used regression analysis and correlation analysis methods to explore consumer preference of Baijiu during different meal and wine pairings.It investigated the correlation between preference and brain waves and facial expressions emotions.It also examined changes in taste perceptions of consumers on dishes before and after meal and wine pairing, correlating with preferences for pairing, aroma, taste, overall liking, purchase intent, and level of recommendation.Results showed heterogeneous changes in taste intensity after different meal and wine pairings, and both elegant-flavor Baijiu and Chi-flavor Baijiu enhance taste intensity with sour, bitter, and spicy dishes.Greater umami intensity change leaded consumers to prefer recommending the Chi-flavor Baijiu.Higher sweetness intensity change correlated with a preference on sweet dishes paired with the Chi-flavor Baijiu.Highest consumer preference appeared when elegant-flavor Baijiu paired with sweet dishes and Chi-flavor Baijiu with salty dishes.Linear regression models yielded correlation coefficients (R) between 0.49 and 0.76, all with P-values below 0.05, indicating a good fit and demonstrating that combining intelligent sensory analysis with traditional sensory evaluation could effectively analyze consumer preference during different meal and wine pairings.This study establishes a scientific basis for enhancing meal and wine pairing preferences.
[1] 杨颂平. 我国白酒消费者市场细分研究[J].中国市场, 2023(30):126-129.
YANG S P.China liquor consumer market segmentation research[J].China Market, 2023(30):126-129.
[2] 赵艳. 国内白酒市场现状及质量研究存在问题探讨[J].食品安全导刊, 2020(33):33-34.
ZHAO Y.Discussion on the current situation of domestic liquor market and problems in quality research[J].China Food Safety Magazine, 2020(33):33-34.
[3] VERDONK N, RISTIC R, CULBERT J A, et al.Investigating Australian consumers’ perceptions of and preferences for different styles of sparkling wine using the fine wine instrument[J].Foods, 2021, 10(3):488.
[4] ZHU Y X, SU Q Y, JIAO J F, et al.Exploring the sensory properties and preferences of fruit wines based on an online survey and partial projective mapping[J].Foods, 2023, 12(9):1844.
[5] ALVINO L, CONSTANTINIDES E, VAN DER LUBBE R H J.Consumer neuroscience:Attentional preferences for wine labeling reflected in the posterior contralateral negativity[J].Frontiers in Psychology, 2021, 12:688713.
[6] MENA B, TORRICO D D, HUTCHINGS S, et al.Understanding consumer liking of beef patties with different firmness among younger and older adults using FaceReaderTM and biometrics[J].Meat Science, 2023, 199:109124.
[7] LAGAST S, GELLYNCK X, SCHOUTETEN J J, et al.Consumers’ emotions elicited by food:A systematic review of explicit and implicit methods[J].Trends in Food Science & Technology, 2017, 69:172-189.
[8] 支瑞聪, 赵镭, 张璐璐.情感型感官测试技术动态分析[J].食品研究与开发, 2016, 37(13):200-206.
ZHI R C, ZHAO L, ZHANG L L.Overview of affective sensory evaluation techniques for food sensory quality[J].Food Research and Development, 2016, 37(13):200-206.
[9] LAWLESS H T, MALONE G J.Comparison of rating scales:Sensitivity, replicates and relative measurement[J].Journal of Sensory Studies, 1986, 1(2):155-174.
[10] ZHI R C, HU X, WANG C Y, et al.Development of a direct mapping model between hedonic rating and facial responses by dynamic facial expression representation[J].Food Research International, 2020, 137:109411.
[11] CLARK E A, KESSINGER J, DUNCAN S E, et al.The facial action coding system for characterization of human affective response to consumer product-based stimuli:A systematic review[J].Frontiers in Psychology, 2020, 11:920.
[12] MATSUFUJI Y, UEJI K, YAMAMOTO T.Predicting perceived hedonic ratings through facial expressions of different drinks[J].Foods, 2023, 12(18):3490.
[13] SHEPELENKO A, SHEPELENKO P, OBUKHOVA A, et al.The relationship between charitable giving and emotional facial expressions:Results from affective computing[J].Heliyon, 2024, 10(2):e23728.
[14] VAN BOMMEL R, STIEGER M, VISALLI M, et al.Does the face show what the mind tells? A comparison between dynamic emotions obtained from facial expressions and Temporal Dominance of Emotions (TDE)[J].Food Quality and Preference, 2020, 85:103976.
[15] WU M, LI H L, QI H Z.Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments[J].Indoor Air, 2020, 30(3):534-543.
