Shelf-life prediction of convenient foods by accelerated storage studies and sensory analyses
Special Symposium - Innovations in Food Technology (LMC Congress)
Innovations in Food Technology - Poster Session (LMC/Food - P1)
Keywords: Shelf life, Accelerated Shelf life Testing (ASLT), sensory, convenient foods, prediction
Shelf-life of heat processed foods packed in plastic packaging is lower than the same product canned with an equivalent heat process. This is due to the different permeability of the packaging materials to external factors affecting product stability, primarily oxygen and light. Therefore, food companies that decide to adapt their canned products to the new packaging trends need to recalculate the shelf life of their products. For practical reasons, especially when the actual storage time is long (up to 5 years in heat-stable products), the industry resorts to accelerated test techniques to shorten the process of obtaining the experimental data.
In this study, Accelerated Shelf-Life Testing (ASLT) was used to predict the shelf life of four types of ready-to-eat vegetable foods packed in retortable plastic containers. For heat stable products, the end of shelf life is limited by changes in sensory properties that eventually, make the product unacceptable for the consumers. Therefore, product acceptability was established using sensory analysis conducted by 30-50 consumers who answered “yes” or “no” to whether they would consume samples stored at different storage temperatures (4, 23, 30, 35, 40ºC) and with different storage times for each temperature. Additionally, they rated the overall acceptance using a 9-point hedonic scale, with 1= dislike extremely, 5= neither like nor dislike, and 9= like extremely. A staggered design was used, increasing the number of consumers as the sampling time approached the end of shelf life. End of shelf-life, at a certain temperature, was the time at which 50% of consumers found the product unacceptable. Consumer’s acceptance or rejection data were analyzed by survival analysis and an Arrhenius model.
Presented Wednesday 19, 13:30 to 15:00, in session Innovations in Food Technology - Poster Session (LMC/Food - P1).
