Epsilon Archive for Student Projects

Abstract

The advantage of being “First to Market” is tremendous, but keeping a high and consistent level of quality is determinant as well for the success of a food company. Low quality products cause damage to the brand and monetary loses in the long run. Quality is strongly influenced by a correct estimation of shelf life, but full length shelf life tests demands large inputs of time and money. The need for a more efficient method of estimating shelf life is therefore required, and the use of accelerated storage tests has gained in popularity in recent years. “Accelerated Shelf Life Tests” is by definition a method that allows the estimation of shelf life through short term storage tests. This is done by converting the accelerated storage results mathematically to represent normal storage conditions, often using different kinetic models. This project intends to evaluate the potential of using accelerated shelf life as a method for shelf life estimation for wet sauces. Two sauces was evaluated in this study; Pizza topping and Taco sauce with previously known shelf life of nine months and 18 months respectively.
The shelf life was estimated by exposing the samples to high temperatures and light during a time period of eight weeks in Climate Chambers (Sanyo Gallenkamp Prime Incubator, INC-000- MA1.9). The light source was a LED lamp that emitted light around 680 to 770 lux and the samples was stored at 22° C, 30° C and 40° C. The samples were then evaluated by sensory analysis and by measuring pigment degradation.
The result showed some inconsistencies with the theoretical aspects of the study. The Pizza topping was estimated to have a shelf life of eight months, and the Taco sauce was predicted to maintain quality for about 17 months. These values correspond well to the current estimated shelf life used. However, the results yielded different estimations depending on how the results were calculated. Q10 – modelling, a method that deduces a conversion factor that allows for direct translation of accelerated storage test results into normal storage condition yielded considerably shorter estimated shelf life values while the use of the Arrhenius equation seemed to results in more realistic values. In addition, the colour analysis resulted in different results when compared to the sensory analysis.
The recommendation is that accelerated shelf life tests have the potential to be a valuable tool when predicting product shelf life in a fast-paced innovation environment. However, due to the inconsistencies of the results it is recommended to perform further investigations before adopting accelerated shelf life tests as a standard method for shelf life estimation.