کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8838584 | 1613136 | 2018 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Number of terms to use in temporal check-all-that-apply studies (TCATA and TCATA Fading) for sensory product characterization by consumers
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش تغذیه
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Temporal Check-All-That-Apply (TCATA), and its variant TCATA Fading, are extensions of Check-All-That-Apply (CATA) questions that can deliver detailed descriptions of the dynamics of the sensory characteristics of samples throughout consumption. This research contributes to establishing guidelines for best practice of TCATA methods and focuses on the number of terms to include in the attribute list. In four consumer studies (n = 492), the influence of list length was assessed by comparing lists containing 9 and 15 terms (“short” and “long” lists, respectively). Specifically, results obtained for the 9 sensory attributes common to both lists were compared with respect to: citation proportions, dynamic sensory profiles, sample discrimination, and consumers' task perceptions. The key findings pertaining to list length were that: (i) increasing the number of terms was not detrimental in terms of sample discrimination, (ii) consumers were able to use all the 15 terms to discriminate among samples, and (iii) lists of 15 terms provided good data quality in both TCATA and TCATA Fading. The influence of list length on the results was similar for TCATA and TCATA Fading, although there was some evidence pointing to a slight superiority of TCATA Fading over TCATA when long lists of terms are used.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Quality and Preference - Volume 64, March 2018, Pages 154-159
Journal: Food Quality and Preference - Volume 64, March 2018, Pages 154-159
نویسندگان
Sara R. Jaeger, Florencia Alcaire, Denise C. Hunter, David Jin, John C. Castura, Gastón Ares,