Quantifying and visualising variation in batch operations: A new heterogeneity index

Time–Temperature Management Along the Food Cold Chain: A Review of Recent Developments

“…The inventory management system based on time–temperature measurement also needs to be implemented at the pallet, or even package, scale in order to account for this variability (Nunes and others ). The heterogeneity of temperature can be explained by, among other things, variability in harvest temperature and in time until precooling; nonuniform precooling; nonuniform temperature variation during ground operations; proximity to refrigeration units; door openings; and poor performance of containers causing a low rate of air circulation around some pallets and a low rate of air penetration inside the pallets (Pelletier ; Nunes and others ; Defraeye and others ; Olatunji and others ). The operating conditions (such as the air circulation rate within a container), loading protocols (to obtain optimal gaps between the pallets, providing a proper balance between cooling rate and uniformity), package design (number, size, and position of vent areas), box stacking pattern on the pallet (to avoid bypass or air between packages), and container design (such as the proper design of floor gratings to improve bottom‐air delivery systems) are different factors that can be modified to decrease the temperature heterogeneity within shipments (Smale ; Ferrua and Singh ; Jedermann and others ; Defraeye and others , ; O'Sullivan and others ).…”

“…Modeling a complete precooling process for different numbers of pallets, products, and operating conditions, for instance, using a lattice Boltzmann approach, would provide a dynamic and detailed description of the food's state and offer a relevant decision‐support tool for efficient precooling. In addition, the model can be combined with a quantitative heterogeneity index, in order to identify package designs and tunnel operating conditions that promote uniform precooling (Ferrua and Singh ; Olatunji and others ). Accurate forecasts of the impacts of management systems based on time–temperature measurement : Accurate forecasts of the capital and operating costs, reduction in food waste, and improvement in food safety resulting from management systems based on time–temperature measurement are required by the industry to justify the investments needed to implement such systems. Estimates of the food waste reduction resulting from management systems based on time–temperature measurement have been made in the literature for different food products (Koutsoumanis and others , ; Dada and Thiesse ; Dittmer and others ; Lütjen and others ; Tromp and others ; Nunes and others ).…”

Sensitivity analysis of heat and mass transfer characteristics during forced‐air cooling process of peaches on different air‐inflow velocities

“…Olatunji et al (2017) indicated a new heterogeneity index (HI), which quantified the levels of cooling uniformity over the entire process time from a product‐side perspective, namely, the overall heterogeneity index OHI = ∆ Y max − ∆ Y min . A lower value of OHI presents better homogeneity over the whole processing time, conversely, the worse uniformity of temperature distribution is.where Y avg, t is the average dimensionless temperature of all monitored fruits, ∆ Y max‐ P , t and ∆ Y min‐ N , t are the maximum and minimum values of ∆ Y n at single time points, HI t is the instantaneous cooling homogeneity at a certain moment.…”

“…Olatunji et al (2017) indicated a new heterogeneity index (HI), which quantified the levels of cooling uniformity over the entire process time from a product-side perspective, namely, the overall heterogeneity index OHI = ∆Y max − ∆Y min . A lower value of OHI presents better homogeneity over the whole processing time, conversely, the worse uniformity of temperature distribution is.…”

The cold chain in New Zealand – A review

“…The Centre for Postharvest and Refrigeration Research at Massey University has a strong tradition of conducting research with New Zealand's fruit export industries, and strengthening the cool chain of these industries. Foci of this research are associated with design of packaging to assist cooling and temperature control of fresh produce, (Defraeye et al, 2015;East et al, 2013b;Olatunji et al, 2016;O'Sullivan et al, 2013;O'Sullivan et al, 2016;O'Sullivan et al, 2017;, development of new methods to measure and cool chain systems (East et al, 2009;O'Sullivan et al, 2014;Redding et al, 2016;Huang et al, 2017;Olatunji et al, 2017), measurement of real world cool chain scenarios (East et al, 2003a;Bollen et al, 2015;O'Sullivan, 2016;Shim et al, 2016;Tanner and Paniagua et al, 2014;East et al, 2013a;East et al, 2013c;Paniagua et al, 2012;Zhao et al, 2015) culminating in the development of mathematical models to predict fruit quality based on supply chain temperature information (Hertog et al, 2016;East et al, 2016;East, 2011).…”