A simulation approach based on transport phenomena is proposed in this paper, to help manage the logistics of fresh broccoli during cold chain. Indeed, for many varieties of fresh vegetables their shelf-life depends critically on storage temperature progress, affecting the visual quality (VQ) as a consequence of changes in intrinsic quality parameters. Broccoli was chosen as a model food, and average ammonium (NH4+) concentration was adopted as a proper quality parameter associated with residual VQ. Therefore, a mathematical model for predicting the residual VQ is proposed depending on the keeping temperature (among 5 and 20 °C), for a relatively long storage duration (up to 12 days). Model validation is brought over by comparing experimental and computed VQ. The predictions were affected by maximum errors of about 3%, 13% and 16% for runs at 5, 10 and 20 °C respectively. The effect of temperature fluctuations were then explored. Two non-isothermal scenarios commonly occurring during retail stores in European and US handlers were first analyzed to test the model's ability to predict the visual quality score. Moreover, the model can be easily applied to assess the household or retail shelf-life, or in general the expiration date after a given storage duration.
Preliminary modeling of the visual quality of broccoli along the cold chain
Maria Cefola;Bernardo Pace
2016
Abstract
A simulation approach based on transport phenomena is proposed in this paper, to help manage the logistics of fresh broccoli during cold chain. Indeed, for many varieties of fresh vegetables their shelf-life depends critically on storage temperature progress, affecting the visual quality (VQ) as a consequence of changes in intrinsic quality parameters. Broccoli was chosen as a model food, and average ammonium (NH4+) concentration was adopted as a proper quality parameter associated with residual VQ. Therefore, a mathematical model for predicting the residual VQ is proposed depending on the keeping temperature (among 5 and 20 °C), for a relatively long storage duration (up to 12 days). Model validation is brought over by comparing experimental and computed VQ. The predictions were affected by maximum errors of about 3%, 13% and 16% for runs at 5, 10 and 20 °C respectively. The effect of temperature fluctuations were then explored. Two non-isothermal scenarios commonly occurring during retail stores in European and US handlers were first analyzed to test the model's ability to predict the visual quality score. Moreover, the model can be easily applied to assess the household or retail shelf-life, or in general the expiration date after a given storage duration.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.