INFLUENCE OF TEMPERATURE ON SHELF LIFE OF BUTTERHEAD LETTUCE LEAVES UNDER PASSIVE MODIFIED ATMOSPHERE PACKAGING

The Use of Modeling Tools to Better Evaluate the Packaging Benefice on Our Environment

Packaging play a key role on food quality preservation and shelf-life increase. Even if the link between shelf life and food loss has not yet clearly been formalized, it is generally observed that a well-designed packaging contributes to reduce food loss and waste and thus the corresponding useless negative impact that producing and distributing uneaten or inedible food has on our environment and economy. In order to anticipate the usage benefit of a given packaging, decision making tools are needed to be developed. While some authors' separately showed the importance of shelf life model, food loss and waste prediction model and Life Cycle Analysis, so far no connection was really made between them. In this context, this paper aims to analyze the different mathematical modeling approaches proposed in the available scientific literature, from the prediction of food shelf life gain thanks to well-designed packaging to the environmental benefice due to the decrease of food loss and waste. The article presents a review of 29 models developed on this thematic during the last two decades. The analyzed models were split in three categories: (1) the food shelf life models, (2) the models linking shelf life to food loss and waste, and (3) the Life Cycle Analysis including direct (production, processing and end of life) and indirect (food loss and waste) packaging environmental impacts. In one hand, the review showed that if many predicting approaches were conducted to assess food shelf life, only few of them were enough mechanistic (by coupling mass transfer to food deterioration) to be used in other conditions than the ones initially studied. Moreover, the consumers' practices and believes being strongly influent on the quantity of food waste at household, it should be more systematically integrated in the food loss and waste estimation for a fairer evaluation. On the other hand, this review highlighted that even if indirect environmental benefit of packaging, e.g., through food loss and waste decrease, is more and more integrated in life cycle analyses of the food packaging system, most of studies were only based on rough estimation and not on real quantification of the food loss and waste reduction obtained thanks to the well-designed packaging. Therefore, further research is needed to facilitate the representation/quantification of the links between shelf life increase for packed food, resulting food loss and waste reduction and environmental benefit to support the packaging sectors to choose and validate the best packaging solution to decrease the environmental impact of food/packaging system.

Quality Characteristics Analysis and Remaining Shelf Life Prediction of Fresh Tibetan Tricholoma matsutake under Modified Atmosphere Packaging in Cold Chain

Tricholoma matsutake (T. matsutake) growing in Tibet is very popular for its high economic and medicinal value, but fresh T. matsutake has an extremely short shelf life. The shelf life of T. matsutake is complex, influenced by product characteristics, surrounding environmental conditions, and spoilage development. The objective of this work was to study the quality characteristics of fresh T. matsutake during its shelf life period in modified atmosphere packaging (MAP) conditions and establish its remaining shelf life prediction models in a cold chain. In this study, we measured and analyzed quality indicators of fresh T. matsutake, including hardness (cap, stipe), color, odor of sensory characteristics, pH, soluble solids content (SSC), and moisture content (MC) of physical and chemical characteristics under the temperature condition of 4 °C and relative humidity (RH) of 90%. The sensory evaluation results showed that the odor indicator in sensory characteristics was more sensitive to the freshness of T. matsutake. The changes of pH, SSC, and MC were divided into three periods to analyze the physiological changes of T. matsutake. The cap spread process could affect the changes of pH, SSC, and MC in period S₁, and they changed gradually in period S₂. In the period S₃, they changed complicatedly because of deterioration. The remaining shelf life prediction model of T. matsutake was established by the back propagation (BP) neural network method to quantify the relationship between the quality indicators and the remaining shelf life. The shelf life characteristics are complex, which were optimized by correlation analysis. Significant benefits of this work are anticipated on the transportation and preservation of fresh T. matsutake to the market and the reduction of its losses in the postharvest chain.

Estimation of failure criteria in multivariate sensory shelf life testing using survival analysis

For most food products, shelf life is determined by changes in their sensory characteristics. A predetermined increase or decrease in the intensity of a sensory characteristic has frequently been used to signal that a product has reached the end of its shelf life. Considering all attributes change simultaneously, the concept of multivariate shelf life allows a single measurement of deterioration that takes into account all these sensory changes at a certain storage time. The aim of the present work was to apply survival analysis to estimate failure criteria in multivariate sensory shelf life testing using two case studies, hamburger buns and orange juice, by modelling the relationship between consumers' rejection of the product and the deterioration index estimated using PCA. In both studies, a panel of 13 trained assessors evaluated the samples using descriptive analysis whereas a panel of 100 consumers answered a "yes" or "no" question regarding intention to buy or consume the product. PC1 explained the great majority of the variance, indicating all sensory characteristics evolved similarly with storage time. Thus, PC1 could be regarded as index of sensory deterioration and a single failure criterion could be estimated through survival analysis for 25 and 50% consumers' rejection. The proposed approach based on multivariate shelf life testing may increase the accuracy of shelf life estimations.