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Quality Control of Biscuit Products by Applying Methods of Sensory Analysis—DSKAS and CATA

[ Vol. 14 , Issue. 5 ]

Author(s):

Marieta Stefanova* and Denka Zlateva   Pages 391 - 399 ( 9 )

Abstract:


Background: Modern sensory evaluation methods have two potential applications in biscuit production: to establish product conformity to regulatory and company requirements and to confirm a sustainable product quality or minimum shelf life. To ensure product quality control and effective management, sensory evaluation procedures that can be implemented during the biscuit production process are needed.

Objective: This study aimed to develop and validate a procedure for biscuit product quality management based on two sensory analysis methods: Difference Scoring with Key Attribute Scales (DSKAS) using trained evaluators and Check-All-That-Apply (CATA) using untrained evaluators, such as production workers.

Methods: The potential of two sensory analysis methods, DSKAS and CATA, to serve as real-time quality measures during biscuit production was assessed. Various factors that may contribute to reliable assessments using these methods were analyzed. A process for sensory evaluation was established and sensory indicators for biscuit product quality were benchmarked.

Results: Comparable results were obtained using the two methods. Results obtained for the two methods (despite the stated study limitations) showed no significant difference in the scores of product quality between the panels of trained and untrained experts. The results indicated that a quality control system based on these sensory methods has practical applications in biscuit production and permits the rapid collation of information regarding the causes of deviations in quality indicators.

Conclusion: Thus, the DSKAS and CATA methods could be successfully applied during an uninterrupted production process to analyze the quality conformity of biscuit products based on sensory indicators.

Keywords:

Biscuit, CATA, DSKAS, quality, sensory analysis, sensory indicators.

Affiliation:

Department of Commodity Science, Faculty of Economics, Varna University of Economics, bul. Knyaz Boris I № 77, Varna 9002, Department of Commodity Science, Faculty of Economics, Varna University of Economics, bul. Knyaz Boris I № 77, Varna 9002



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