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Research Project:
Sensory and Physicochemical Property Relationships in Assessment and Prediction of End-Use Food Quality
Location:
Quality Assessment Research Unit
Project Number: 6612-44000-023-00
Project Type:
Appropriated
Start Date: Sep 12, 2004
End Date: Sep 11, 2009
Objective:
Determine how sensory and physicochemical properties relate in order to develop the means to assess and predict end-use food quality. The specific objectives are directed toward identified problems critical to the poultry industry: (1) Determine the relationships among sensory, physical, and chemical properties of poultry meat that result from non-traditional processing, such as applications that hasten the onset of rigor or air-chilling to reduce water use; (2) Determine the relationships among sensory, physical, and chemical properties of poultry meat that result from further-processing treatments, such as marination to increase yield and improve sensory quality.
Approach:
Develop comprehensive profiles of the measurable sensory attributes of foods and food products and relate these profiles to the food's physical and chemical properties in order to enhance product development and accurately predict end-use quality. Develop indexes, methods, or strategies to predict, evaluate, modify, and control end-use quality based on data-relationships.
The overall framework of the research involves six steps; (1) Develop specific sensory objectives relating to the commodity problem; (2) Select the range of characteristics encompassed by the problem that will be tested; (3) Develop the appropriate databases of sensory, chemical, physical properties for characteristics determined in Step 2; (4) Pre-process the data using multivariate methods (principal component analysis, factor analysis, variable cluster analysis, Procrustes, discriminant analysis) to reduce and simplify the data to the main factors for further analysis and interpretation; (5) Develop and test plausible models to explain and predict sensory quality; (6) Test selected variables in more stringent experimental designs to relate cause and effect and to verify variables as predictors of quality.
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