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Technique for order of preference by similarity to ideal solution ( TOPSIS ) method for the generation of external preference mapping using rapid sensometric techniques
Journal of the Science of Food and Agriculture ( IF 4.1 ) Pub Date : 2020-12-09 , DOI: 10.1002/jsfa.10959
Lorena G Ramón-Canul 1, 2 , Diana L Margarito-Carrizal 3 , Rogelio Limón-Rivera 3 , Uriel A Morales-Carrrera 3 , Ingrid M Rodríguez-Buenfil 4 , Manuel O Ramírez-Sucre 4 , Adán Cabal-Prieto 5 , José A Herrera-Corredor 6 , Emmanuel de Jesús Ramírez-Rivera 3, 4
Affiliation  

BACKGROUND External Preference Mapping (PREFMAP) is a powerful tool to explain consumer preference or rejection. Combining the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multicriteria analysis with rapid descriptive techniques can improve PREFMAP results. This study was conducted to compare the PREFMAPs generated with rapid descriptive Flash Profile (FP), Check-All-That-Apply (CATA) and Napping® versus PREFMAPs constructed with FP-TOPSIS, CATA-TOPSIS and Napping®-TOPSIS. RESULTS Only the 38.46, 63.66 and 42% of sensory attributes initially generated by FP, CATA and Napping techniques were considered for the determination of their weight (W) and allocation as positive (+) or negative (-) in the TOPSIS technique. The PREFMAPs constructed with FP-TOPSIS, CATA-TOPSIS and Napping®-TOPSIS presented a better explanation of the preference and rejection compared to the PREFMAPs directly generated with rapid sensory techniques. The results of the Multiple Factor Analysis and coefficient Rv indicated similarities in the sensory vocabularies used after the TOPSIS technique. CONCLUSION The combination of the TOPSIS technique with rapid sensory techniques is a reliable alternative for the construction of PREFMAPs in order to identify the sensory attributes responsible for preference and rejection of food products. This article is protected by copyright. All rights reserved.

中文翻译:

使用快速传感技术生成外部偏好映射的通过与理想解相似的偏好排序技术(TOPSIS)

背景 外部偏好映射 (PREFMAP) 是解释消费者偏好或拒绝的有力工具。将通过与理想解决方案相似度 (TOPSIS) 多标准分析的偏好排序技术与快速描述技术相结合可以改进 PREFMAP 结果。本研究旨在比较使用快速描述性 Flash Profile (FP)、Check-All-That-Apply (CATA) 和 Napping® 生成的 PREFMAP 与使用 FP-TOPSIS、CATA-TOPSIS 和 Napping®-TOPSIS 构建的 PREFMAP。结果 在 TOPSIS 技术中,只有 38.46%、63.66% 和 42% 最初由 FP、CATA 和小睡技术产生的感官属性被考虑用于确定它们的重量 (W) 和分配为正 (+) 或负 (-)。用 FP-TOPSIS 构建的 PREFMAPs,与使用快速感官技术直接生成的 PREFMAP 相比,CATA-TOPSIS 和 Napping®-TOPSIS 对偏好和拒绝提供了更好的解释。多因素分析和系数 Rv 的结果表明 TOPSIS 技术后使用的感官词汇的相似性。结论 TOPSIS 技术与快速感官技术的结合是构建 PREFMAP 的可靠替代方案,以识别导致食品偏好和拒绝的感官属性。本文受版权保护。版权所有。多因素分析和系数 Rv 的结果表明 TOPSIS 技术后使用的感官词汇的相似性。结论 TOPSIS 技术与快速感官技术的结合是构建 PREFMAP 的可靠替代方案,以识别导致食品偏好和拒绝的感官属性。本文受版权保护。版权所有。多因素分析和系数 Rv 的结果表明 TOPSIS 技术后使用的感官词汇的相似性。结论 TOPSIS 技术与快速感官技术的结合是构建 PREFMAP 的可靠替代方案,以识别导致食品偏好和拒绝的感官属性。本文受版权保护。版权所有。
更新日期:2020-12-09
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