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在食品行业环境中,RATA、CATA、排序和 Napping® 作为感官分析的快速替代方法的比较。

Comparison of RATA, CATA, sorting and Napping® as rapid alternatives to sensory profiling in a food industry environment.

机构信息

Société des Produits Nestlé S.A, Route du Jorat 57, CH-1000 Lausanne 26, Switzerland.

Société des Produits Nestlé S.A, Route du Jorat 57, CH-1000 Lausanne 26, Switzerland.

出版信息

Food Res Int. 2022 Aug;158:111467. doi: 10.1016/j.foodres.2022.111467. Epub 2022 Jun 11.

DOI:10.1016/j.foodres.2022.111467
PMID:35840195
Abstract

Today, there is a need to accelerate new product development to deliver faster innovations which are expected by consumers. This requires identifying rapid descriptive methodologies requiring less training than conventional sensory profiling (SP) still providing good quality data allowing to identify food sensory drivers of consumer liking. A set of nine samples covering a large sensory space has been designed systematically combining at three different ratio three commercial almond, rice, and oat-based milks. Ten expert panellists familiar with sensory profiling and naïve with the plant-based milk category performed sorting, Napping®, CATA, RATA tasks and then SP. Overall liking of each sample was rated by 80 plant-based milk consumers. Among the four alternative methodologies, RATA provided both an overall product configuration and description the closest to SP (RV = 0.93) and allowed to identify the sensory drivers of plant-based milk acceptance similarly to SP. CATA is relevant to build a product landscape and to highlight product clusters with major sensory differences whereas Sorting and Napping® are alternatives to CATA, as product mappings were close, when no previous glossary or knowledge exits on product attributes.

摘要

如今,需要加速新产品开发,以满足消费者期望的更快创新。这就需要确定快速描述方法,这些方法比传统的感官分析(SP)需要更少的培训,但仍能提供高质量的数据,以确定消费者喜欢的食品感官驱动因素。设计了一套由 9 个样品组成的系统,这些样品结合了三种不同比例的三种商业杏仁、大米和燕麦基牛奶。10 名熟悉感官分析但对植物基牛奶类别不熟悉的专家品尝员进行了分类、Napping®、CATA、RATA 任务,然后是 SP。80 名植物基牛奶消费者对每个样品的整体喜好进行了评分。在这四种替代方法中,RATA 提供了与 SP 最接近的整体产品配置和描述(RV=0.93),并允许确定植物基牛奶接受度的感官驱动因素,与 SP 类似。CATA 适用于构建产品图谱,并突出具有主要感官差异的产品集群,而排序和 Napping®则是 CATA 的替代方法,因为在没有产品属性的先前词汇表或知识的情况下,产品图谱非常接近。

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