Survival analysis concepts to be used in sensory shelf life studies were introduced, together with the equations necessary for calculations. The survival function was defined as the probability of consumers accepting a product beyond a certain storage time. Censoring phenomena, a key concept in survival analysis, was defined and has been shown to occur in sensory shelf-life data. Concepts and calculations were applied to a data set obtained from 50 consumers who each tasted seven yogurt samples with different storage times, answering "yes" or "no" to whether they would consume the samples. From this censored data set, nonparametric and parametric models were obtained that allowed shelf-life estimations.

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.

: :Sensory shelf lives of Argentine commercial stirred yogurts of different compositions stored at 10 °C were studied. Variations were as follows: fat‐free and whole‐fat, and vanilla and strawberry flavors. Yogurts were tested between 0 and 84 d of storage by consumers who expressed their acceptance or rejection of each sample; yogurts also were measured overall, as well as their attribute acceptability, with a hedonic scale. Survival analysis statistics were used to estimate shelf lives. Considering 25% of consumers rejecting the product, shelf lives were between 28 and 41 d; thus, a unique shelf life for this product does not seem reasonable. A log‐linear model and a direct quantile comparison formula were introduced to analyze the effect of formulation on rejection time distributions and shelf life values, respectively. Overall, fat‐free yogurts had lower shelf lives than whole‐fat yogurts.

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