IDEAS home Printed from https://ideas.repec.org/a/rfa/setjnl/v6y2019i1p6-15.html
   My bibliography  Save this article

Evaluation and Analysis Model of Wine Quality Based on Mathematical Model

Author

Listed:
  • Yunhui Zeng
  • Yingxia Liu
  • Lubin Wu
  • Hanjiang Dong
  • Yuanbiao Zhang
  • Hongfei Guo
  • Zisheng Guo
  • Shuyang Wang
  • Yao Lan

Abstract

This paper takes wine quality evaluation as the research object, establishes the analysis and evaluation model of wine quality, and explores the influence of physical with chemical indicators of wine grapes and wine on the wine quality. Firstly, the Mann-Whitney U test is used to analyze the wine evaluation results of the two wine tasters, and it is found that the significant difference between the two is small. Then this paper uses the Cronbach Alpha coefficient method to analyze the credibility of the two groups of data. It is found that the credibility of the first group of wine scores is significantly greater than that of the second group and the white wine scores are more reliable than the red wine. Therefore, the first set of data and white wine can be applied for follow-up studies. Next, the principal component analysis is used to extract the main indicators and calculate the factor coefficients as the Ward method in cluster analysis is used to classify the wine into four grades according to the quality score of the wine. Then, based on the extracted principal components that is physical with chemical indicators, this paper does the multiple linear regression analysis of wine quality, and takes the influence of aromatic substances on the aroma of wine in physical with chemical indicators as an example. Regression analysis shows that there is a positive correlation linear relationship between the scores of the aroma of wine and C2H6O, C6H12O2, C3H8O, C11H24, C7H12O2, C5H10O2 and C10H16. It can be judged that the aromatic substances in the wine such as C2H6O have a regular influence on the odor of the wine, and it is inferred that other physical and chemical properties have a similar regular relationship with the wine quality. This provides an effective reference for the analysis and evaluation of wine quality by using physical with chemical indicators such as aromatic substances in wine in the future.

Suggested Citation

  • Yunhui Zeng & Yingxia Liu & Lubin Wu & Hanjiang Dong & Yuanbiao Zhang & Hongfei Guo & Zisheng Guo & Shuyang Wang & Yao Lan, 2019. "Evaluation and Analysis Model of Wine Quality Based on Mathematical Model," Studies in Engineering and Technology, Redfame publishing, vol. 6(1), pages 6-15, December.
  • Handle: RePEc:rfa:setjnl:v:6:y:2019:i:1:p:6-15
    as

    Download full text from publisher

    File URL: https://redfame.com/journal/index.php/set/article/download/3626/3916
    Download Restriction: no

    File URL: https://redfame.com/journal/index.php/set/article/view/3626
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peterson, Robert A, 1994. "A Meta-analysis of Cronbach's Coefficient Alpha," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 381-391, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joseph A. Cazier & Benjamin B. M. Shao & Robert D. St. Louis, 2007. "Sharing information and building trust through value congruence," Information Systems Frontiers, Springer, vol. 9(5), pages 515-529, November.
    2. Haase, Janina & Wiedmann, Klaus-Peter & Labenz, Franziska, 2022. "Brand hate, rage, anger & co.: Exploring the relevance and characteristics of negative consumer emotions toward brands," Journal of Business Research, Elsevier, vol. 152(C), pages 1-16.
    3. Sirén, Charlotta & Kohtamäki, Marko, 2016. "Stretching strategic learning to the limit: The interaction between strategic planning and learning," Journal of Business Research, Elsevier, vol. 69(2), pages 653-663.
    4. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang & Lee, Cheng fang, 2022. "Adoption model of healthcare wearable devices," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    5. Yoonsun Oh & Jungsuk Oh, 2017. "A critical incident approach to consumer response in the smartphone market: product, service and contents," Information Systems and e-Business Management, Springer, vol. 15(3), pages 577-597, August.
    6. Maria Naether & Janine Stratmann & Christina Bendfeldt & Ludwig Theuvsen, 2015. "Wodurch wird die Arbeitszufriedenheit landwirtschaftlicher Arbeitnehmer beeinflusst?," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 8(1), pages 85-96.
    7. S. Rajeswari & Yarlagadda Srinivasulu & S. Thiyagarajan, 2017. "Relationship among Service Quality, Customer Satisfaction and Customer Loyalty: With Special Reference to Wireline Telecom Sector (DSL Service)," Global Business Review, International Management Institute, vol. 18(4), pages 1041-1058, August.
    8. Su Jin Kang & Wonseok Seo, 2020. "The Effects of Multilayered Disorder Characteristics on Fear of Crime in Korea," IJERPH, MDPI, vol. 17(24), pages 1-22, December.
    9. Mark Heitmann & Andreas Herrmann, 2007. "Die Zufriedenheit mit dem Entscheidungsprozess als Determinante der Kundenbindung," Schmalenbach Journal of Business Research, Springer, vol. 59(5), pages 530-566, August.
    10. Catherine Viot & André Le Roux & Florence Kremer, 2014. "Attitude towards the purchase of counterfeits: Antecedents and effect on intention to purchase," Post-Print halshs-02530136, HAL.
    11. Le Thanh Tiep & Ngo Quang Huan & Tran Thi Thuy Hong, 2020. "The Impact of Renewable Energy on Sustainable Economic Growth in Vietnam," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 359-369.
    12. Herjanto, Halimin & Amin, Muslim & Purington, Elizabeth F., 2021. "Panic buying: The effect of thinking style and situational ambiguity," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    13. Tor Guimaraes & Ketan Paranjape & Mike Cornick & Curtis P. Armstrong, 2018. "Empirically Testing Factors Increasing Manufacturing Product Innovation Success," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 1-26, April.
    14. Patrick Kunle Adeosun LADIPO & Ismail Tubosun AREBI & Olushola Solomon AKEKE & Babatunde BISIRIYU, 2021. "Effect Of Customer Service On Corporate Competitive Advantage In The Nigerian Telecoms Service Industry," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 212-229, November.
    15. Céline Desmoulins, 2021. "Reputation measurement: a tool for ski station applied to Isère Mountain," Post-Print hal-03149407, HAL.
    16. Pelet, Jean-Éric & Durrieu, François & Lick, Erhard, 2020. "Label design of wines sold online: Effects of perceived authenticity on purchase intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    17. Hsu, Chia-Jui & Yen, Jin-Ru & Chang, Yu-Chun & Woon, Hui Kee, 2016. "How do the services of low cost carriers affect passengers' behavioral intentions to revisit a destination?," Journal of Air Transport Management, Elsevier, vol. 52(C), pages 111-116.
    18. Andor, Mark A. & Lange, Andreas & Sommer, Stephan, 2022. "Fairness and the support of redistributive environmental policies," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).
    19. Naruemon Choochinprakarn, 2015. "Strategic Uses of Electronic Commerce for Thai Travel Small and Medium Enterprises (SMEs)," Proceedings of Business and Management Conferences 2303915, International Institute of Social and Economic Sciences.
    20. Dan Zhao & Shengrui Zhang & Bei Zhou & Shuaiyang Jiao & Ling Yang, 2020. "Risk Perception Sensitivity of Cyclists Based on the Cox Risk Perception Model," Sustainability, MDPI, vol. 12(7), pages 1-23, March.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rfa:setjnl:v:6:y:2019:i:1:p:6-15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.