Imaging Technology for Food Waste Reduction

Apeel Sciences

Andrea Strang/als2380

Summary of Problem:

In America, roughly 40% of food that is produced goes to waste. While food losses occur at every point of the food supply chain, the most significant losses occur as food waste. Food waste is defined as by the US Department of Agriculture’s (USDA) Economic Research Service (ERS) as food discarded by retailers due to color or appearance and plate waste by consumers. Households are the largest contributors of food waste, with approximately 40-50% of food waste happening at the consumer level. In addition to the lost costs of uneaten food items, wasted food puts a strain on our environment through excess resource depletion (water, land, and energy) and methane emissions in landfills.

Technology Solution:

Apeel Acquires Imaging Technology for Better Ripening Insight, Produce Blue Book, https://www.producebluebook.com/2021/05/11/apeel-acquires-imaging-technology-for-better-ripening-insight/#  

  • Apeel Sciences, a company that develops and produces science based solutions to extend the shelf-life of fresh produce and mitigate food waste, will be incorporating ImpactVision hyper-spectral imaging technology into their application system.
  • ImpactVision imaging technology allows users to see the inside of produce and collects quantifiable quality data such as ripeness, freshness, and nutritional density. The datasets from ImpactVision can be used by suppliers to sort and ship produce in a more strategic fashion. For example, riper products will be shipped sooner and across shorter distances to prevent spoilage and ensure retailers get a higher quality product.
  • The combination of ImpactVision datasets alongside Apeel’s plant-derived coatings that effectively double the shelf-life of produce can greatly reduce post-harvest food losses and waste.

Stakeholders:

Stakeholders include food suppliers, retailers, and regional populations who will be positively impacted by a reduction in wasted resources and greenhouse gas (GHG emissions). Food suppliers will be able to use ImpactVision datasets to more effectively distribute produce and reduce food waste, ultimately improving their bottom-line. In turn, retailers will likely receive a better quality product with optimal ripeness for consumer purchase, likewise eliminating food waste and seeing positive financial impacts.

Next Steps:

  1. Begin with a pilot program. A small pool of food suppliers and retailers should be utilized to get feedback about application improvement opportunities from their standpoint as end-users.
  2. Utilize the feedback from selected users to make adjustments and ensure user-friendliness of application for wide-scale deployment.
  3. Offer reduced cost deals during the early stage of application deployment and invest in digital/social media advertising to garner publicity and reach a broader audience.

3 thoughts on “Imaging Technology for Food Waste Reduction

  1. Thanks for sharing, Andrea, this is fascinating stuff. I’m curious to learn more about their original product, as well.

    One point I wanted to add is that it seems that they recognize the lack of available data as an opportunity for the Image Scanning technology they have created. So, I think Apeel sees potential beyond their current model of reimagining supply chain, and potentially into selling data? Possibly, this would be to farmers/growers or other ag tech companies?

    Like

  2. This was super cool technology that I honestly would have never even thought feasible at the scale they are considering. I’d definitely like to see more of how the operations at distribution facilities would work; particularly with sorting the foods once the different factors have been identified.

    One very interesting part is how the technology will be able to “identify unique visual cues that relate to freshness, degree of maturity, phytonutrient content, and other aspects of fruit quality.” I think as the software is used more and more and the database of information expands. The technology will get smarter and more efficient at identifying these cues which will make for an even more efficient software.

    Like

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