Preferences for Commercial Strawberry Drinkable Yogurts Among African American, Caucasian, and Hispanic Consumers in the United States

References 

1. Anonymous. 2006. Subject: Yogurt Drinks in the United States. http://www.researchandmarkets.com/reports/339088 Accessed Jan. 30, 2007.
2. Anonymous. 2007a. Drinkable yogurt is fastest-growing food and beverage category, ACNielsen finds. Cheese Marketing News, Feb. 9, 2007.
3. Anonymous. 2007b. Subject: Yogurt drinks fastest growing in the world—Study. http://www.reuters.com/article/companynewsandPR/idUSN2440974620070124 Accessed Jan. 31, 2007.
4. Arnott N. La Yogurt goes Latino. Sales and Marketing Management. 1994;146:16
5. Banfield JD, Raftery AE. Model-based Gaussian and non-Gaussian clustering. Biometrics. 1993;49:803–821
   • CrossRef
6. Barnes DL, Harper SJ, Bodyfelt FW, McDaniel MR. Correlation of descriptive and consumer panel flavor ratings for commercial prestirred strawberry and lemon yogurts. J. Dairy Sci. 1991;74:2089–2099
   • Abstract
   • Full-Text PDF (772 KB)
   • CrossRef
7. Barnes DL, Harper SJ, Bodyfelt FW, McDaniel MR. Prediction of consumer acceptability of yogurt by sensory and analytical measures of sweetness and sourness. J. Dairy Sci. 1991;74:3746–3754
   • Abstract
   • Full-Text PDF (750 KB)
   • CrossRef
8. Berry D. Growth Continues. Dairy Foods Magazine. 2003;104:24–29
9. Biasioli F, Gasperi F, Aprea E, Endrizzi I, Framondino V, Marini F, et al. A robust and scalable clustering algorithm for mixed type attributes in large database environment. In: 7th Assoc. Comput. Machin. (ACM) Special Interest Group on Knowledge Discovery and Data Mining, San Francisco. CA. ACM, New York, NY. 2001;
10. Bogue J, Ritson C. Integrating consumer information with new product development process: the development of lighter dairy products. Int. J. Consum. Stud. 2005;30:44–54
11. Brewster E. Hispanic flavors heat up. Beverage Industry. 2002;93:41–42
12. Chiu T, Fang D, Cheng J, Wang Y, Jeris C. A robust and scalables clustering algorithm for mixed type attributes in large database environment. In: 7th Assoc. Comput. Machin. (ACM) Special Interest Group on Knowledge Discovery and Data Mining, San Francisco. CA. ACM New York, NY. 2001;
13. Decker, K. J. 2004. Crossing Borders: Designing for the Hispanic Demographic. Food Product Design. Available http://www.food product design.com/articles/0904CS.html. Accessed Mar. 30,2007.
14. Eder R. Drinkable yogurt beats the bagel. Drug Store News. 2003;25:42
15. Johanningsmeier S, McFeeters R, Drake MA. A hypothesis for the chemical basis for perception of sourness. J. Food Sci. 2005;70:R44–R48
    • CrossRef
16. Kalvianinen N, Roininen K, Tuilora H. The relative importance of texture, taste and aroma on a yogurt-type snack food preference in the young and elderly. Food Qual. Pref. 2003;14:177–186
17. Martens H, Martens M. Multivariate Analysis of Quality: An Introduction. West Sussex, UK: John Wiley & Sons; 2001;
18. Meilgaard MM, Civille GV, Carr T. Sensory Evaluation Techniques. 3rd ed. New York, NY: CRC Press; 1999;
19. Pollen NR, Daubert CR, Prabhasankar P, Drake MA, Gumpertz ML. Quantifying fluid food texture. J. Texture Stud. 2004;35:642–657
20. Raymond J. The multicultural report. Am. Demogr. 2001;23:3–6
21. SPSS. 2001. Subject: The SPSS Twostep Cluster Component: A scalable component enabling more efficient customer segmentation. SPSS Inc., Chicago, IL. http://www.spss.ch/upload/1122644952_The%20SPSS%20TwoStep%20Cluster%20Component.pdf Accessed June 22, 2006.
22. Tsuchiya A, Almiron-Roig E, Lluch A, Guyonnet D, Drewnowski A. Higher satiety ratings following yogurt consumption relative to fruit drink or dairy fruit drink. J. Am. Diet. Assoc. 2006;106:550–557
    • Abstract
    • Full Text
    • Full-Text PDF (173 KB)
    • CrossRef
23. Ward CD, Koeferli CS, Schwegler PP, Schaeppi D, Plemmon LE. European strawberry yogurt market analysis with a case study on acceptance drivers for children in Spain using principal component analysis and partial least squares regression. Food Qual. Pref. 1999;10:387–400
24. Zhang T, Ramakrishnon R, Livny M. BIrCH: An efficient data clustering method for very large databases. In: Paper presented at The Assoc. Comput. Machin. (ACM), Special Interest Group on Management of Data Conference on Management of Data. Montreal, Canada. ACM, New York, NY. 1996;