Apeel has announced plans to introduce new solutions to instantly and non-destructively determine the maturity level of lawyers.
“Expanding our technology offerings will increase access to information to create a smarter supply chain that maximizes shelf life, quality and sustainability of fresh produce,” said James Rogers, CEO.
Devices scan avocados and group them into categories based on maturity and dry matter
These efforts include:
- Deployment of an improved AI data model for product sorter imaging devices in packing and distribution centers. Developed in collaboration with MAF Industries, these devices scan avocados and instantly group them into categories according to their maturity and dry matter.
- Launched a product quality scanner for distributors and grocery retailers that can be used to assess the ripeness and dry matter of individual avocados. These devices are more than five times faster than existing methods, do not damage fruit like current methods, and information is automatically entered into a cloud database.
- The launch of an avocado maturity scanner for consumers could allow shoppers to know the exact maturity window of products like avocados before buying them. Apeel’s RipeFinder, available for demonstration at the International Fresh Produce Association’s Global Produce & Floral Show in Orlando this week, also features a consumer-friendly user interface (i.e. it reveals information such as “Your avocado will be ready in about 4 days”).
Maturity scanners could let shoppers know the exact ripening window of produce like avocados before buying them
Previously, the ripeness of avocados was typically tested using a penetrometer, a device that uses a needle to poke a hole in the fruit and measure the tenderness of samples. Dry matter, an approximate measure of oil content, is an industry standard indicator of quality and is determined by a laborious and expensive process that typically involves cooking samples in a microwave.
The imaging system works by sending light into the avocado, where it penetrates several millimeters below the skin. A sensor measures the amount of reflected light in the visible spectrum and in the near infrared.
A sensor measures the amount of reflected light in the visible spectrum and in the near infrared
Machine learning models are then tasked with converting this measured light spectrum into an accurate estimate of the avocado’s firmness and dry matter. Measurements can indicate how soon the fruit is ready to eat.
“The Global Avocado Maturity Model was developed using machine learning by collecting data on tens of thousands of avocados across multiple seasons, blooms, and countries of origin,” said Lou Perez, co-founder and Vice President of New Product Launch.
This technology is currently only available for avocados, but Apeel is working on models for other products, including limes, mangoes and tangerines.
Booth n°1143 to see this technology in action.
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