Improvement in fresh fruit and vegetable logistics quality: berry logistics field studies

Abstract

Shelf life of fresh fruits and vegetables is greatly influenced by environmental conditions. Increasing temperature usually results in accelerated loss of quality and shelf-life reduction, which is not physically visible until too late in the supply chain to adjust logistics to match shelf life. A blackberry study showed that temperatures inside pallets varied significantly and 57% of the berries arriving at the packinghouse did not have enough remaining shelf life for the longest supply routes. Yet, the advanced shelf-life loss was not physically visible. Some of those pallets would be sent on longer supply routes than necessary, creating avoidable waste. Other studies showed that variable pre-cooling at the centre of pallets resulted in physically invisible uneven shelf life. We have shown that using simple temperature measurements much waste can be avoided using ‘first expiring first out’. Results from our studies showed that shelf-life prediction should not be based on a single quality factor as, depending on the temperature history, the quality attribute that limits shelf life may vary. Finally, methods to use air temperature to predict product temperature for highest shelf-life prediction accuracy in the absence of individual sensors for each monitored product have been developed. Our results show a significant reduction of up to 98% in the root-mean-square-error difference between the product temperature and air temperature when advanced estimation methods are used.

Reducing food losses by intelligent food logistics

“…-the first case study focuses on berries to illustrate how losses can be avoided by more effective pre-cooling management, shelf life modelling and stock rotation (FEFO in real operations), as well as accurate mapping and estimation of the product temperature [3]; -the quality changes of bananas during trans-ocean transportation can be described by the concept of green life, giving the time span until an unwanted ripening process takes place; in the second case study, we present models for green life and temperature prediction inside a loaded container and show how cooling can be improved by better packing [4]; and -although most of the work is concentrated on FFVs, the same principles apply to the supply chain for meat products; in this case study, we present the application of a shelf life model covering the supervision of a chain, including four different truck transports and three distribution centres (DCs) [5].…”

“…Although most of the models presented in this Theme Issue [2][3][4][5] include factors such as humidity and atmospheric gas concentrations, they all agree on the point that temperature is the most critical factor influencing quality. The spread of models presented in this Theme Issue shows that there is no unique approach.…”

“…One common approach is to relate shelf life to respiration activity [3]. It is assumed that the speed of ageing processes increases proportionally to the increase in the CO 2 production rate at higher temperatures.…”

“…For example, Tijskens & Polderdijk [31] published a list of model parameters for 60 FFVs in 1996. A review of the existing shelf life models for berries, for example, can be found in [3].…”

“…-farmers do not pre-cool after harvest; the 'cut-to-cool' time is recognized as being very important for many commodities [3] but is typically not monitored effectively; -the actual temperature conditions during transport and storage often do not meet the optimal product-specific values; and -customers keep fresh products for hours in the warm boot of their car or set the temperature of their fridge to achieve minimal power consumption, thus ignoring the recommended storage temperatures.…”