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MOSKOWITZ B. The Approach of Optimization C. Experimental Designs D. Sensory Evaluation Tests E. Developing the Product Model F. Results: Modeling G. The Product Model H. Optimizing Acceptance I. Changing Formulation Limits J. Constraining Cost and/or Sensory Attributes K. Exploring the Response Surface VI. Matching a Product to a Concept VII. Contrasting and Relating Expert Panel versus Consumer Panel Data VIII. An Overview of Sensory Analysis References 50 50 50 52 54 54 56 58 58 60 61 63 65 66 I.

Describing the Sensory Attributes of Foods A. Introduction B. Developing a Language for Taste, Odor, Texture, and Appearance C. Descriptive Systems for Odor, Flavor, and Texture III. Measuring Intensity of Perception A. Thresholds versus Sensory Intensity B. Using the Panelist to Measure Intensity by Category Scales. C. Using Category Data in Sensory Analysis D. Types of Category Scales Currently Used E. Benefits and Drawbacks of Category Scales for Applied Research F. Ratio Scales of Perception in Sensory Analysis G.

2. Regression Regression or curvefitting(Draper and Smith, 1966) allows the researcher to develop a predictive and descriptive equation relating the rating assigned by the panelist to the physical level or processing variable. The typical equation follows a straight line of the form Rating = A + ^(stimulus level) For category ratings researchers have found that the underlying relation exhibits a substantial degree of curvature, so that the relation does not follow a simple straight line (although as we increase the stimulus level we will increase the rating of perceived intensity).

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