Complying with food regulations and, more importantly, quality standards, requires practical and reliable methods to estimate a product’s shelf life. Emphasizing the importance of the consumer’s perception of when food has reached the end of its shelf life, Sensory Shelf Life Estimation of Food Products provides a tool for adequately predicting sensory shelf life (SSL).
- Explains how to design a shelf life estimation experiment
- Develops the application of survival analysis statistics to SSL prediction using acceptance/rejection data obtained from consumers
- Presents instructions, code and downloadable example files to be used with the freely available R-statistical package
- Details the cut-off point methodology as an alternative to survival analysis.
- Covers non-linear and survival analysis modeling of Arrhenius’ equation to obtain adequate predictions of activation energies
- Includes an R-function to perform a non-linear regression to better estimate activation energy
- Describes extensions of survival analysis statistics to other food applications
- Sensory Shelf Life Definition
- Labeling Regulations
- Shelf Life of Foods Is Sensory Shelf Life
- Importance of the Consumer in Defining Food Quality
- Books on Shelf Life of Foods
Principles of Sensory Evaluation
- Definition of Sensory Evaluation
- Sensory Analysis: Trained Panels versus Experts
- General Requirements and Conditions for Sensory Tests
- Physiological Factors
- Psychological Factors
- Sensory Evaluation Methods
Design of Sensory Shelf-Life Experiments
- Initial Considerations
- Approximations of Shelf-Life Values
Survival Analysis Applied to Sensory Shelf Life
- What is Survival Analysis?
- Survival and Failure Functions
- Shelf Life Centered on the Product or on Its Interaction with the Consumer?
- Experimental Data Used to Illustrate the Methodology
- Censoring in Shelf-Life Data
- Model to Estimate the Rejection Function
- Calculations Using the R Statistical Package
- Interpretation of Shelf-Life Calculations
- An Additional Example
- Should Consumers be Informed?
- Is There a Way to Deal with Totally New Products?
Survival Analysis Continued: Number of Consumers, Current Status Data, and Covariates
- Number of Consumers
- Current Status Data
- Introducing Covariates in the Model
Cut-Off Point Methodology
- When is the Survival Statistics Methodology Difficult to Apply?
- Basics of the Cut-Off Point Methodology
- Approaches in Establishing a COP
- Methodology to Measure the COP
- Instrumental Cut-Off Points
- Caveats for Using COP Methodology
- Arrhenius Equation and Activation Energy
- The Use of Q10
- Survival Analysis Accelerated Storage Model
- Potential Pitfalls of Accelerated Shelf-Life Testing
- Conclusion on Accelerated Testing
Other Applications of Survival Analysis in Food Quality
- Consumer Tolerance Limits to a Sensory Defect
- Optimum Concentration of Ingredients in Food Products
- Optimum Salt Level in French Bread
- Internal Cooking Temperature of Beef
- Optimum Ripening Times of Fruits