HYPERSPECTRAL
TECHNOLOGY
www.foodtechnology.co.nz 19
TO HELP AVOCADO GROWERS
Current quality assurance methods for avocados and other
produce generally involve randomly selecting individual pieces
of fruit and performing various destructive tests to determine
Today, the percentage of produce
that can be sampled
ranges from 0.1 to 3%, and
because every product is
different, applying statistical analyses
based on sample testing leads to
inconsistency of end product, fuelling
rejection rates, shrink and customer
complaints.
But what if it was possible to analyse
100% of products, without performing
destructive tests? This is what
one company in California is saying
it has achieved by applying a space
technology to food supply chains.
ImpactVision is bringing to the market
hyperspectral imaging technology,
capable of analysing an entire packing
line of produce. Chief executive Abi
Ramanan is hoping that this technology
will help to reduce food waste
by accurately predicting ripeness and
other key freshness measures as well
as identifying foreign matter to prevent
product recalls.
“Globally, a staggering 45% of fruits
and vegetables are wasted and much
of that has to do with how products
are processed through the supply
chain,” she says. “There is a huge
amount of inconsistency when it
comes to testing avocados for dry
matter, for example. It is largely based
on destructive tests that sample
perhaps 0.1 to 3% of products. Of
course, with the natural variance in
food products, statistical models are
not sufficient to provide quality information
for 100% of products, particularly
at volumes of tens of millions or
even billions of units per year.”
The company’s product is a package:
firstly, a hyperspectral imaging camera
combined with ImpactVision’s
proprietary software which interprets
hyperspectral data and sends back
actionable information on ripeness,
freshness or shelf-life. The cameras
are designed to sit on top of packing
line conveyors and analyse every
information such as sugar levels, pH and ripeness.
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