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中国精品科技期刊2020
朱雨萱,问亚琴,许晓青,等. 感官词典建立方法及食品中应用研究进展[J]. 食品工业科技,2022,43(5):396−407. doi: 10.13386/j.issn1002-0306.2021020138.
引用本文: 朱雨萱,问亚琴,许晓青,等. 感官词典建立方法及食品中应用研究进展[J]. 食品工业科技,2022,43(5):396−407. doi: 10.13386/j.issn1002-0306.2021020138.
ZHU Yuxuan, WEN Yaqin, XU Xiaoqing, et al. Research Progress of Sensory Lexicon Building Method and Applications in Food[J]. Science and Technology of Food Industry, 2022, 43(5): 396−407. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021020138.
Citation: ZHU Yuxuan, WEN Yaqin, XU Xiaoqing, et al. Research Progress of Sensory Lexicon Building Method and Applications in Food[J]. Science and Technology of Food Industry, 2022, 43(5): 396−407. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021020138.

感官词典建立方法及食品中应用研究进展

Research Progress of Sensory Lexicon Building Method and Applications in Food

  • 摘要: 感官词典是标准化的词汇表,用于帮助不同人群关于感官问题进行交流。本文综述了建立一个感官词典的流程,主要包括四个步骤:准备样品及培训人员、生成初始词汇、讨论初始词汇并给出定义和参考并验证词汇有效性,分别对四个步骤的具体操作和要求进行阐述,并对近十年来食品与饮品感官词典的开发进行总结。词典的开发促进了感官词汇的标准化,也促进了感官学界、食品制造业与消费者之间的交流。在未来的发展中,感官词典的建立方法可能通过同化学分析、数据挖掘技术如自然语言处理等技术结合起来而得到升级,其应用领域也将趋向多元化。

     

    Abstract: Sensory lexicon is a standardized vocabulary used to help different populations communicate about sensory issues. This paper reviews the process of building a sensory lexicon, which consists of four main steps: preparing samples and training personnel, generating an initial lexicon, discussing the initial lexicon and giving definitions and references, and verifying the validity of the lexicon. The specific operations and requirements of each of the four steps are described, and the development of a sensory lexicon for food and beverages over the past decade is summarized. The development of the lexicon has facilitated the standardization of sensory descriptors and the communication between the sensory community, the food manufacturing industry and consumers. In future developments, sensory lexicon building methods may be upgraded by combining them with chemical analysis, data mining techniques such as natural language processing, etc., and their application areas will tend to diversify.

     

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