Impact of temperature fluctuations on quality changes of frozen green beans and carrots during storage.

The quality of vegetables during frozen storage and distribution chain is affected by fluctuating temperature regimes. The temperature variations influence ice-water displacement due to ice crystal growth and ice-sublimation. Hence, the description of quality changes of frozen vegetables during temperature fluctuations is indispensable in the frozen food industry. In this context, frozen carrots and green beans were stored under four different temperatures: -8 °C ± 3 °C, -12 °C ± 3 °C, -18 °C ± 3 °C and -23 °C ± 3 °C for 12 months. In each storage condition, two different partitions were created to achieve different amplitudes of temperature fluctuations, namely low (±0.3 °C) and large (±2 °C). The evolution of frost forming and drip loss in green beans and carrots were analysed in addition to the changes of ascorbic acid in green beans. The results indicated that high mean storage temperature and large amplitude of fluctuation significantly affect the quality indicators. The quality data for drip loss and ascorbic acid were fitted to a first-order kinetic model. An Arrhenius model was applied to describe the temperature dependency by incorporating the temperature fluctuation scenarios. A simplified physical model was used to simulate frost formation during frozen storage in green beans and carrots. Finally, the models were validated using the data collected at -18 °C and -12 °C with low and large amplitudes of fluctuation.

Modelling of firmness variability of Jonagold apple during postharvest storage.

The firmness of Jonagold apples is an important quality attribute during postharvest chain. However, postharvest handlers are faced with variability in the firmness that exists within apples even of those of the same batch and cultivar. Here, Jonagold apples were stored at 1 °C and 4 °C with different controlled atmospheric gas compositions for 170 d, and then exposed to shelf-life conditions for 15 d, and other portion of apples was immediately stored to shelf-life scenario for 21 d. The firmness and ethylene emission of the apples were quantified during storage. A kinetic model equation was established to predict the firmness breakdown of apples depending on storage conditions. The model was based on a stochastic technique that incorporated biological variability in firmness. A relative sensitivity analysis was carried out to analyse the utmost stochastic parameters and fruit-specific data were obtained. The Monte Carlo method was applied to predict how the initial fruit variability in firmness within Jonagold apples propagates throughout the postharvest storage. The simulation outputs suggest that the model established in study may be useful to manage the biological variability and describe how the initial firmness variability propagates during the postharvest chain.