da Silva Izabeli Batista Girarducci, Magnani Marciane, Esmerino Erick Almeida, Filho Elson Rogerio Tavares, Cruz Adriano Gomes, Pimentel Tatiana Colombo
State University of Londrina (UEL), Londrina, Brazil.
Laboratory of Microbial Process in Foods, Department of Food Engineering, Federal University of Paraíba, João Pessoa, Brazil.
Compr Rev Food Sci Food Saf. 2025 May;24(3):e70197. doi: 10.1111/1541-4337.70197.
Descriptive analysis (DA) is the gold standard for sensory profiling due to its robustness and reliability. However, its high cost, time demand, and labor intensity limit routine applications in the food industry. Rapid Sensory Profiling Techniques (RSPTs) have emerged as faster, less resource-intensive alternatives to address these challenges. Among them, preferred attribute elicitation (PAE) stands out. This review aims, for the first time, to comprehensively clarify applications of PAE in food products and provide insights into challenges and trends. PAE enables consumers to collaboratively identify, measure, categorize, and prioritize key attributes while providing hedonic insight. By ranking attributes based on their relevance to product acceptance and preference, PAE integrates descriptive and affective dimensions of sensory perception, enhancing the understanding of consumer experience and product appeal. PAE has been applied to fruits, meat, dairy, dairy alternatives, bakery products, and beverages, yielding sensory profiles comparable to those obtained via DA. It has also been used to evaluate processing, resampling, storage, and fermentation effects, distinguish commercial products, and analyze sensory perception differences among consumer groups. Key methodological factors affecting PAE's reliability include the moderator's expertise, panelist profile, and attribute selection. Future research should expand its application to unexplored food categories, validate its relevance compared to traditional acceptance tests, assess its effectiveness in complex food matrices, and integrate it with other sensory methods. This is the first comprehensive review of the PAE application, offering practical insights for researchers and the food industry on correctly using this method.
描述性分析(DA)因其稳健性和可靠性,是感官剖析的黄金标准。然而,其高成本、时间需求和劳动强度限制了在食品工业中的常规应用。快速感官剖析技术(RSPTs)已成为更快、资源消耗更少的替代方法来应对这些挑战。其中,偏好属性引出法(PAE)尤为突出。本综述首次旨在全面阐明PAE在食品中的应用,并深入探讨挑战和趋势。PAE使消费者能够共同识别、测量、分类和优先排列关键属性,同时提供享乐主义见解。通过根据属性与产品接受度和偏好的相关性进行排序,PAE整合了感官感知的描述性和情感维度,增强了对消费者体验和产品吸引力的理解。PAE已应用于水果、肉类、乳制品、替代乳制品、烘焙产品和饮料,产生的感官特征与通过DA获得的特征相当。它还被用于评估加工、重新采样、储存和发酵效果,区分商业产品,以及分析消费者群体之间的感官感知差异。影响PAE可靠性的关键方法因素包括主持人的专业知识、小组成员概况和属性选择。未来的研究应将其应用扩展到未探索的食品类别,验证其与传统接受度测试相比的相关性,评估其在复杂食品基质中的有效性,并将其与其他感官方法相结合。这是对PAE应用的首次全面综述,为研究人员和食品行业正确使用该方法提供了实用见解。