(Editor’s Note: This is an online-only article attributed to the October/November 2018 issue.)
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How many berries actually make their way to the consumer and how many go bad at the supermarket, in transit, or even at the farm? The problem of waste has some invisible causes within the fresh food supply chain.
The most likely reason is the product ran out of shelf life because it wasn’t handled properly. The resultant mushy berries or sprouted fungus mean these fruits are money wasted, going directly into the trash.
In this day and age, why can’t this waste be prevented?
The fact is this issue can be prevented, but because so much of the fresh food supply chain relies on outdated approaches to quality and freshness management, the problem persists.
All produce has a finite shelf life. The maximum shelf life is based on the specific product, the harvest conditions, and post-harvest temperature management. Raspberries, for example, have a particularly short shelf life. They last five to seven days at most and that’s only if they’re handled and stored in optimal conditions. Strawberries, when properly processed and handled, can have up to 12 days of shelf life.
The primary issue with handling in the supply chain is temperature management. Like all living things, produce breathes or respirates. The higher the temperature, the faster it respirates and the faster it ages. The best way to slow the respiration rate—and maximize the shelf life—is to cool the product down (to about 34 degrees Farenheit for berries) as quickly as possible after harvest and maintain the desired temperature from the packing house to the store. Time and temperature are what’s critical.
Unfortunately, managing time and temperature is often challenging because of a number of variables in the fresh food supply chain. Time at high temperatures varies from pallet-to-pallet. If a pallet spends hours in the field, it could lose days of shelf life. For instance, a pallet left at 85 degrees for three hours will lose three days of shelf life. Another pallet could quickly be precooled and retain its shelf life. Time waiting before precooling or sitting on a loading dock can also differ significantly as can temperature during transit, and all of these variables will have an impact on the freshness of a product.
In the end, each pallet of produce will likely have a different shelf life. If a grocer unknowingly sells a clamshell of raspberries or strawberries that go bad the day after purchase, it’s probably because they didn’t know the dynamic remaining shelf life of the product when they received it. They just lacked good information.
Most suppliers and retailers monitor the temperature of product as it moves through the supply chain but typically only for cold chain compliance (ensuring there are no temperature excursions) and only at the trailer level. So, if a temperature excursion is noted, an entire trailer of product could be tossed, leading to waste, increased costs, and reducing profits. These practices exacerbate the problem rather than solving it and employ a reactive approach.
Solving the freshness problem requires proactive supply chain management. Begin by determining the maximum shelf life for a product. Then the temperature of the product needs to be monitored and managed at the pallet level from harvest to delivery. With this data, modern technology including machine learning and predictive analytics can be applied to dynamically calculate the true shelf life of the product in real-time. For example, it may have been determined that Pallet A has 12 days of remaining shelf life and Pallet B has only eight days of remaining shelf life. With this data, intelligent pallet routing can be implemented. Pallet A could be shipped the five days from California to New York, for example, and arrive with seven days of remaining shelf life. Pallet B could be shipped to a closer location, such as Seattle, and arrive with sufficient shelf life for the retailer to sell it and the customer to enjoy and consume it for five more days. This approach helps to eliminate the chances of retailers selling berries that are going to prematurely turn to mush or grow mold.