Study Of Light Accelerated Testing Method To Predict Shelf Life Of Packaged Fat Foods Based On Photo-oxidation

Fat foods can easily get oxidized when subjected to the adverse environment, especially the light and oxygen during storage, which resulted the shelf life becoming shorter. Photo- oxidation occurred much more quickly than auto-oxidation. In addition to take the effective packaging materials and packaging technology to prevent and mitigate the fat oxidation, how to predict the shelf life of packaged fat foods accurately is also critical. Accelerated testing is the most commonly used methods, and to predict such foods, light acceleration factor can not be ignored. In this paper, canola oil as the typical photosensitive product, combined with light and packaging factors for the accelerated testing. The kinetic equation under different accelerated factors was fitted and finally established a reasonable shelf-life prediction model.The light accelerated test methods and the basis of fat food packaging optimization were also obtained:(1) The fat oxidation of canola oil packaged by different OTR films under dark and light conditions was determined based on common oxidation indicators. The trends of fat oxidation in different packaging and reasonable oxidation index for predict shelf life was obtained, while the appropriate packaging material for later light accelerated testing was chosen.(2) The effect of light intensity and temperature on the fat oxidation in packaged canola oil were investigated with accelerated testing. Measuring the corresponding index to explore the correlation between the two factors showed that temperature affect the rate of light oxidation. The shelf life prediction modal based on photo oxidation under the multivariate accelerated factors light and temperature was derived. Meanwhile the changes of the oxygen permeability of the film under different light intensities were measured to simulate the difference to the light accelerated testing.(3) Took the liquid depth and light exposed area as the acceleration factors respectively. The result by the light accelerated testing showed that the light intensity decreased exponentially with the increase of liquid depth. In another way which can combine with the relationship between light intensity and the oxidation rate, the prediction model of liquid depth and oxidation rate can be set up then. This model was also found a exponential relation which was consistent with the experimental results. While the oxidation rate was proportional to the light exposed surface.(4)The predict model of packaged fat foods with light multivariate factors was gotten by combining the corresponding representation models under different light accelerated conditions. With the photo-oxidation under acceleration factors, the appropriate acceleration conditions, a generally accelerated testing method based on photo-oxidation also gotten and the light accelerated testing program was improved and simplified, which can be more comprehensive predict the shelf life of fat foods under different packaging specifications. In addition, the basis to optimize the packaging structure for liquid fat foods was suggested.