Preferred Attribute Elicitation (PAE) in the Sensory Descriptive Analysis of Foods: A Deep Comprehensive Review of the Method Steps, Application, Challenges, and Trends.
- 2025-05
- Comprehensive reviews in food science and food safety 24(3)
- Izabeli Batista Girarducci da Silva
- Marciane Magnani
- Erick Almeida Esmerino
- Elson Rogerio Tavares Filho
- Adriano Gomes Cruz
- Tatiana Colombo Pimentel
- PubMed: 40371455
- DOI: 10.1111/1541-4337.70197
Study Design
- Type
- Review
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.