What is Shelf Life Prediction?
Shelf life prediction is a technology that has risen with the need to track the freshness of food.
Currently, static testing is the most common way of measuring shelf life. This involves leaving produce on a shelf and waiting for it to expire. But, this is slow, leads to unnecessary food waste, and not accurate.
New technologies are able to assess fresh produce and tell you the number of days it has left.
Imagine how powerful your decisions could be if you knew the life of any batch of fruits and vegetables.
Shelf life prediction benefits businesses at each stage of the food supply chain. Also, AI has made it more powerful and affordable to use.
Why Measure Shelf Life?
It is important to understand and predict how long food will last. This ensures that high-quality produce reaches the end destination. Also, customers are more likely to buy and consume fresher produce, so it helps reduce food waste.
Benefits of measuring shelf life include:
- Sending fresher produce to customers
- Reduced costs in transportation, processing, and storage
- Sending produce to the right place at the right time with dynamic routing
- Recovering food closer to the top of the food recovery hierarchy
What Methods of Shelf Life Prediction are Available?
The food system uses four main methods (other than static testing) to predict shelf life. Most measure the internal status and external conditions of fresh produce.
Spectroscopy uses light to analyze the internal status of fruits and vegetables. Researches already use spectroscopy in multiple ways for food analysis. This technology offers real-time shelf life and freshness measurement of fruits and vegetables. You can also combine it with other data to further improve accuracy.
Imaging in both the visual field and outside the visual spectrum can be helpful in determining the current state of produce. A smartphone camera assesses whatever the human eye sees and is quite good at doing so. But, we still can’t visualize much of the ripening process because it occurs underneath the surface. Spectral cameras visualize more of the ripening and rotting processes because they see things the eye cannot.
3. Chemical Analysis
Ethylene is a gas that most fruits produce during the ripening process. By measuring the levels of ethylene continuously, you can know the time that fruit begins to ripen. However, it is difficult to measure ethylene of individual items because most fruits and vegetables produce it. Artificial ripening also uses ethylene, which limits the usage of this technology across the supply chain.
Keeping food cold throughout the supply chain is important. If the cold chain is broken, it can harm shelf life. You can track the life of fresh produce by monitoring temperature. The current temperature of a single piece of produce in a given moment is not useful. However, you can look at the temperature history of that fruit or vegetable and even combine it with other data to gain a better idea of shelf life.
Which Type is Best?
The answer to this question depends on the application. Combining multiple technologies may even be the most accurate.
The best fits for the following technologies are:
- Spectroscopy- Measuring accurate shelf life across the entire supply chain
- Chemical Analysis- Determining when fruits or vegetables ripen in the middle of the supply chain
- Temperature- Understanding how temperature affects shelf life across the supply chain
- Imaging- Analyzing visual defects and internal processes in produce across the supply chain
Below is a chart to see how the different methods compare against each other.
What Features are Important to Have?
The technology to measure shelf life is important, but what is more important is the value you gain from analyzing and acting on the data.
These are the features that are most important for shelf life prediction solutions:
What Should The Steps to Implementation Be?
The earlier this process is started, the closer you are to saving food waste and improving sustainability metrics.
The ideal path to implementation that we’ve found is:
- Evaluate potential solutions and suppliers
- Prioritize most important produce to target
- Begin a trial with most critical variety (this can be done with a supplier/customer at the same time)
- Analyze the results of the trial and verify your ROI
- Expand the solution into more varieties/more sites
- Implement the solution at supplier and customer levels, if beneficial
A few different types of technologies for predicting shelf life are currently available.
The best choice of technology depends on the application it is used for, and it may be best to combine technologies.
When implementing shelf life prediction, it is important that it meets the criteria laid out in this post to avoid headaches in the future.
Want to learn more about fresh produce shelf life prediction? Check out our Ultimate Guide!
What Does OneThird Do?
We use spectroscopy and other data sources to predict shelf life. Also, our cloud platform and AI algorithms allow you to share this information and to connect with partners.
Trials with early adopters have proven the accuracy of this technology and have confirmed it saves them money and time.
Contact us to learn more about how OneThird can help you predict shelf life and prevent food waste.