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For desirable attributes in food products such as red color in a strawberry yogurt, the color can be too light, okay, or too dark, leading to 2 events of interest: the transition of too light to ok, and the transition of ok to too dark. The objective of the present work was to develop a model using survival analysis statistics to allow modeling these 2 events and thus allow prediction of the optimum color based on acceptance or rejection data obtained from consumers. Concepts and calculations were applied to a data set obtained from 60 consumers who each looked at 7 yogurt samples with different red color intensities, answering whether they found the samples too light, okay, or too dark. From this censored data set parametric models were obtained which allowed optimum color estimation and segmentation of consumers in groups according to whether they liked lighter or darker colored yogurts. Applications of the model to other food ingredients and to the ripening and spoilage of fruit are discussed.

When talking about shelf life of foods, in the vast majority of cases we are talking about sensory shelf life of foods. The review presents an overview of the published research over the past decades classified according to the following topics: (1) cut‐off point methodology (arbitrary and regression‐based cut‐off points); (2) methods based on product failure or consumers' rejection (failure with no censorship, logistic regression and survival analysis); (3) accelerated studies; and (4) other topics and further research. PRACTICAL APPLICATIONS Going through the aisles of the food and beverage sections of a supermarket shows that the number of food products whose shelf life is dependent on their sensory properties is far greater than those products whose shelf life depends on microbiological and/or nutritional properties. The present review allows researchers and practitioners to count on a summary of the salient research articles published on the theme of sensory shelf life. Articles which deal with methodological and design issues are presented, together with a critical review of articles where poor methodology has been applied.

For years, just-about-right (JAR) scales have been among the most used techniques to obtain sensory information about consumer perception, but recently, some researchers have harshly criticized the technique. The present study aimed to apply survival analysis to estimate the optimum sucrose concentration in probiotic petit suisse cheese and compare the survival analysis to JAR scales to verify which technique more accurately predicted the optimum sucrose concentration according to consumer acceptability. Two panels of consumers (total=170) performed affective tests to determine the optimal concentration of sucrose in probiotic petit suisse using 2 different methods of analysis: JAR scales (n=85) and survival analysis (n=85). Then an acceptance test was conducted using naïve consumers (n=100) between 18 and 60 yr old, with 2 samples of petit suisse, one with the ideal sucrose determined by JAR scales and the other with the ideal sucrose content determined by survival analysis, to determine which formulation was in accordance with consumer acceptability. The results indicate that the 2 sensory methods were equally effective in predicting the optimum sucrose level in probiotic petit suisse cheese, and no significant differences were detected in any of the characteristics related to liking evaluated. However, survival analysis has important advantages over the JAR scales. Survival analysis has shown the potential to be an advantageous tool for dairy companies because it was able to accurately predict the optimum sucrose content in a consumer-friendly way and was also practical for researchers because experimental sensory work is simpler and has been shown to be more cost effective than JAR scales without losses of consumer acceptability.

The objectives of this research were to determine the sensory cutoff points for dulce de leche (DL) critical descriptors, both for defective off-flavors and for storage changes in desirable attributes, and to estimate the shelf life of DL as a function of storage temperature. The critical descriptors used to determine the cutoff points were plastic flavor, burnt flavor, dark color, and spreadability. Linear correlations between sensory acceptability and trained panel scores were used to determine the sensory failure cutoff point for each descriptor. To estimate shelf life, DL samples were stored at 25, 37, and 45 degrees C. Plastic flavor was the first descriptor to reach its cutoff point at 25 degrees C and was used for shelf-life calculations. Plastic flavor vs. storage time followed zero-order reaction rate. Shelf-life estimations at different temperatures were 109 d at 25 degrees C, 53 d at 37 degrees C, and 9 d at 45 degrees C. The activation energy, necessary to calculate shelf lives at different temperatures, was 14,370 +/- 2080 cal/mol.

Survival analysis methodology was used to estimate the shelf life of alfajor (a chocolate‐coated individually wrapped cake) at 20 and 35C by using results obtained from consumers when asked if they would accept or reject samples with different storage times. Sensory acceptability (measured by consumers), off‐flavor (measured by a trained panel) and moisture content were linearly related to time. These correlations were used to estimate values at the shelf‐life times calculated for 25 and 50% rejection probability. Survival analysis provided the following shelf‐life estimation: 74 days at 20C and 33 days at 35C for a 25% of rejection, 87 days at 20C and 39 days at 35C for a 50% of rejection. An alfajor stored at 20C having an acceptability value below 4.9 (1–9 hedonic scale) and off‐flavor intensity above 5.3 (0–10 scale) would be rejected by 25% of the consumers. Chemical data were not good shelf‐life predictors.