Apeel announced its plan to introduce new solutions to instantly and non-destructively determine the ripeness of avocados.
“The expansion of our technology offerings will increase access to insights to create a smarter supply chain maximizing the lifespan, quality and sustainability of fresh produce,” says James Rogers, CEO.
The devices scan avocados and group them into categories according to ripeness and dry matter.
These efforts include:
- Deploying an improved AI data model for imaging hardware in produce sorters at packing houses and distribution centers. Developed in collaboration with MAF Industries, these devices scan avocados and instantly group them into categories according to ripeness and dry matter.
- Launching a produce quality scanner for distributors and grocery retailers that can be used to evaluate 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 insights are automatically captured in a cloud database.
- Unveiling an avocado ripeness scanner for consumers could allow shoppers to know the exact ripeness window of produce like avocados before purchasing. The Apeel RipeFinder, available for demo 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”).
Ripeness scanners could allow shoppers to know the exact ripeness window of produce like avocados before purchasing.
Prior to this, avocado ripeness was commonly tested using a penetrometer, a device that uses a needle to punch a hole in the fruit and measure the tenderness of samples. Dry matter, a proxy measurement of oil content, is an industry-standard quality indicator and is determined by a laborious and wasteful process that typically involves microwaving samples.
The imaging system works by shining light into the avocado where it will penetrate several millimeters below the skin. A sensor measures how much light is reflected in the visible and near-infrared spectrum.
A sensor measures how much light is reflected in the visible and near-infrared spectrum.
Machine learning models are then tasked with converting this measured light spectrum into an accurate prediction of the avocado's firmness and dry matter. The measurements can inform how long before the fruit is ready for consumption.
“The global avocado ripeness model was developed using machine learning by collecting data on tens of thousands of avocados throughout multiple seasons, blooms and countries of origin,” said Lou Perez, co-founder and SVP of new product introduction.
This technology is currently only available for avocados, but Apeel is working on models for other produce including limes, mangos and mandarins.
Visit Apeel at booth #1143 to see this technology in use.
For more information:
Olivia Ferraro
Apeel Sciences
Tel: +1 (323) 857-9100
Olivia.Ferraro@edible-inc.com
https://www.apeel.com/