Korean Journal of Food Science and Technology (한국식품과학회지)

Korean Society of Food Science and Technology (한국식품과학회)
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Exploratory Study on the Quality Grade of Korea Black Raspberry Wines by Using Consumer Preference Data

시판 복분자주의 기호도 분석을 통한 탐색적 등급 분류

  • Lee, Seung-Joo (Department of Culinary and Food Service Management, Sejong University)
  • 이승주 (세종대학교 조리외식경영학과)
  • Received : 2014.02.03
  • Accepted : 2014.02.18
  • Published : 2014.06.30
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Abstract

In this study, 100 consumers (men, 50; women, 50; age group, 20-50 years) rated their overall preferences for 24 Korean raspberry wines by using a 9-point hedonic scale. The analysis of variance was constructed to evaluate the effect of gender, age, and samples on the preference scores of the wine products. Significant differences were observed in overall preferences for the 24 samples; however, no interactions based on preferences by age and gender groups were noted. Cluster analysis was performed to determine sample clustering based on the frequencies from the preference data. Three clusters were obtained; these three clusters were well separated based on the mean overall preference scores for the samples. Discriminant analysis based on the three clusters also confirmed the same grouping of samples with 100% accuracy.

수도권 거주 소비자 100명을 대상으로 전국에서 시판되는 24종의 복분자주의 소비자 기호도 조사를 실시하였다. 24개 복분자주 시료의 전반적인 기호도 평가의 분산분석을 통해 기호도 평가에 연령 및 성별간의 차이보다는 개인 간의 차이가 더 크게 작용한 것으로 나타났다. 전체 소비자 기호도 평가 결과를 바탕으로 군집분석을 실시하여 시료 간 유사한 기호도 평가를 보인 세 개의 군집으로 분류하였다. 세 개의 군집은 기호척도의 빈도수 분포와 실제 기호도 평균 점수에서 군집 간의 차이가 확인되었다. 이러한 군집 분류를 바탕으로 판별분석을 활용하여 군집의 분류가 적절한지 또한 판별함수의 예측력은 적정한지 파악하였다. 판별분석결과 분류율이 100%로 적절한 예측력을 보였고, 세 군집간의 마할라노비스거리와 추출된 요인 내에서의 분포도도 적정한 것으로 나타났다. 향후 다양한 우리술의 품질평가시스템 개발에 소비자 기호도 조사를 활용한 평가방법이 활용 가능하리라 여겨진다.

Keywords

References

  1. Drake MA. Invited review: Sensory analysis of dairy foods. J. Dairy Sci. 90: 4925-4937 (2007) https://doi.org/10.3168/jds.2007-0332
  2. Kraggerud H, Solem S, Abrahamsen RK. Quality scoring - A tool for sensory evaluation of cheese? Food Qual. Prefer. 26: 221-230 (2012) https://doi.org/10.1016/j.foodqual.2012.04.006
  3. Cho SY, Seo G, Kim DH, Kim JH. Palatability grading analysis of Hanwoo beef using sensory properties and discriminant analysis. Korean J. Food Sci. Ani. Resour. 29: 132-139 (2009) https://doi.org/10.5851/kosfa.2009.29.1.132
  4. Bodyfelt FW, Drake MA, Rankin SA. Developments in dairy foods sensory science and education: From student contests to impact on product quality. Int. Dairy J. 18: 729-734 (2008) https://doi.org/10.1016/j.idairyj.2008.03.011
  5. Hopfer H, Heymann H. Judging wine quality: Do we need experts, consumers or trained panelists? Food Qual. Prefer. 32: 221-233 (2014) https://doi.org/10.1016/j.foodqual.2013.10.004
  6. Delgado C, Guinard JX. How do consumer hedonic ratings for extra virgin olive oil relate to quality ratings by experts and descriptive analysis ratings? Food Qual. Prefer. 22: 213-225 (2011) https://doi.org/10.1016/j.foodqual.2010.10.004
  7. Guinard JX, Yip D, Cubero E, Mazzucchelli R. Quality ratings by experts, and relation with descriptive analysis ratings: a case study with beer. Food Qual. Prefer. 10: 59-67 (1998) https://doi.org/10.1016/S0950-3293(98)00038-X
  8. Ismail B, Haffar I, Baalbaki R, Henry J. Development of a total quality scoring system based on consumer preference weightings and sensory profiles: application to fruit dates (Tamr). Food Qual. Prefer. 12: 499-506 (2001) https://doi.org/10.1016/S0950-3293(01)00043-X
  9. Logue AW, Smith ME. Prediction of food preferences in adult humans. Appetite 7: 109-125 (1986) https://doi.org/10.1016/S0195-6663(86)80012-5
  10. Lyon DH. Factors affecting the sensory quality of vegetables. Food Sci. Technol. Today 4: 40-44 (1990)
  11. Watson R, Gee A, Polkinghorne R, Porter M. Consumer assessment of eating quality - development of protocols for meat standards Australia (MSA) testing. Aust. J. Exp. Agr. 48: 1360-1367 (2008) https://doi.org/10.1071/EA07176
  12. Perry D, Thomson JM, Hwang IH, Butchers A, Egan AF. Relationship between objective measurements and taste panel assessment of beef quality. Aust. J. Exp. Agr. 41: 981-989 (2001) https://doi.org/10.1071/EA00023
  13. Poste LM, Butler G, Mackie D, Agar VE, Thompson BK, Cliplef RL, Mckay RM. Correlations of sensory and instrumental meat tenderness values as affected by sampling techniques. Food Qual. Prefer. 4: 207-214 (1993) https://doi.org/10.1016/0950-3293(93)90164-2
  14. Thompson JM. Polkinghorne R, Hwang IH, Gee AM, Cho SH, Park BY, Lee JM. Beef quality grades as determined by Korean and Australian consumers. Aust. J. Exp. Agr. 48: 1380-1386 (2008) https://doi.org/10.1071/EA05111
  15. Polkinghorne RJ, Nishimura T, Neath KE, Watson R. Japanese consumer categorisation of beef into quality grades, based on meat standards Australia methodology. Anim. Sci J. 82: 325-333 (2011) https://doi.org/10.1111/j.1740-0929.2010.00825.x
  16. Korea alcohol liquor industry association. Currents in domestic alcoholic beverage market. Alcohol Beverage News 3: 11 (2011)
  17. Jung JW, Son MY, Jung SW, Nam PW, Sung JS, Lee SJ, Lee KG. Antioxidant properties of Korean black raspberry wines and their apoptotic effectson cancer cells. J. Sci. Food Agr. 89: 970-977 (2009) https://doi.org/10.1002/jsfa.3540
  18. Macfie HJ, Bratchell N, Greenhoff K, Vallis LV. Designs to balance the effect of order of presentation and first-order carry-over effect in hall tests. J. Sens. Stud. 4:129-148 (1989) https://doi.org/10.1111/j.1745-459X.1989.tb00463.x
  19. Lee SJ, Lee KG. Understanding consumer preferences for rice wines using sensory data. J. Sci. Food Agr. 88: 690-698 (2008) https://doi.org/10.1002/jsfa.3137
  20. Martnez C, Santa-Cruz MJ, Hough G, Vega MJ. Preference mapping of cracker type biscuits. Food Qual. Prefer.13:535-544 (2002) https://doi.org/10.1016/S0950-3293(02)00087-3
  21. Monteleone E, Frewer L, Wakeling I, Mela DJ. Individual differences in starchy food consumption: The application of preference mapping. Food Qual. Prefer. 9:211-219 (1998) https://doi.org/10.1016/S0950-3293(97)00070-0
  22. Lee SJ, Noh WA, Choi YC. Sensory Evaluation of cooked rice with fuzzy reasoning. Korean J. Food Sci. Technol. 26: 776-780 (1994)
  23. Kim JH, Kim JA. Statistical discriminant analysis on the driving ability of the brain-injured. J. Korean Data Info. Sci. Soc. 16: 19-31 (2005)

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