Evaluation and modeling of changes in color, firmness, and physicochemical shelf life of cut pineapple (Ananas comosus) slices in equilibrium-modified atmosphere packaging.

Abstract

In this study cut, pineapple slices of 1cm thick were packaged and stored at different temperatures and equilibrium modified atmosphere packages (EMAPs) to determine changes of color and firmness over time to represent physicochemical shelf life. From the experimental data, a variance analysis was performed to determine the effect of temperature and O2 level on the evolution of color (CIELAB coordinates) and firmness. It was observed that the evolution in L* , a* , and b* coordinates is independent on O2 concentration in the EMAP system. After that, suitable models were adjusted to represent the change of the quality properties as a function of temperature by using first-order models to represent color and a power model for firmness. Likewise, a modified normal distribution function was adjusted to represent the coefficient of firmness loss depending on the O2 level besides the temperature effect. The firmness model was used to obtain a suitable equation to predict shelf life of the pineapple slices for different EMAP systems. Finally, a validation experiment was performed at 8 °C obtaining a high capacity of prediction (R2 adj >0.90) compared with the experimental data. The adjusted model can be used to configure a satisfactory EMAP system for the best preservation of minimally processed pineapple from the predicted evolution of color, firmness, and shelf life depending on temperature and O2 concentration. PRACTICAL APPLICATION: In this work, we built a mathematical model to simulate the shelf life of pineapple cut into slices based on changes in color and firmness and as a function of temperature and oxygen level. These properties are truly relevant because they are very clear evidence of the fruit deterioration, and for that reason, we chose them for the model. The model we developed can be applied in retail and supermarket systems to determine precisely how long the product on the shelf can last before being disposed of, reducing material losses.