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Validation of rapid descriptive sensory methods against conventional descriptive analyses: A systematic review
Lorena Andrade de Aguiar1, Lauro Melo1, Lívia de Lacerda de Oliveira2
1College of Health Sciences, University of Brasilia , Campus Darcy Ribeiro, Asa Norte, Brasilia , Brazil.
Rapid descriptive methods (RDM) offer a faster alternative to conventional descriptive profiles (CDP) in sensory evaluation. Systematic reviews show RDMs can effectively characterize foods, especially with semi-trained panels and individual attribute evaluation.
Area of Science:
- Food Science
- Sensory Evaluation
- Research Methodology
Background:
- Conventional descriptive profile (CDP) requires extensive panel training, limiting its efficiency.
- Rapid descriptive methods (RDM) have emerged as time-saving alternatives for sensory analysis.
- Validation of RDMs against CDP is crucial for reliable food characterization.
Purpose of the Study:
- To adapt systematic review (SR) protocols for evaluating the validation of RDMs against CDP.
- To assess the efficacy of RDMs in generating comparable food descriptive profiles to CDP.
- To determine the reliability and quality of studies validating RDMs.
Main Methods:
- Utilized a systematic review (SR) framework adapted from health sciences.
- Employed the Population Intervention Comparison Outcome Study (PICOS) framework for study design.
- Analyzed sensory descriptive analyses comparing RDMs (intervention) with CDP (comparison) for food/beverages (population).
Main Results:
- The proportion of studies finding RDM similarity to CDP varied widely (0%–100%).
- A significant majority of studies (87%) presented low risk of bias, with 13% moderate risk.
- RDMs using semi-trained assessors and evaluating individual attributes showed higher concordance with CDP.
Conclusions:
- Systematic review methodology is applicable for validating rapid descriptive methods in sensory science.
- RDMs are a viable alternative to CDP for food characterization, particularly under specific conditions.
- Future RDM development should consider semi-trained assessors and focused attribute evaluation for optimal performance.
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