Making the Grade
A great-looking apple is no guarantee of great taste. Internal defects
are difficultif not impossibleto detect. USDA inspectors
sample apples to gauge taste and other quality factors. But if they
so much as pick up an apple, it has to be discarded. And there are grading
tests done on sample apples when they are first bought from growers,
before the fruit ever reaches the packing line. But, again, all those
tests require destroying (or eating) the applewhich means the
ones tested are guaranteed to be the ones we never get to eat.
So Renfu Lu, an ARS agricultural
engineer working in Michigan, the third-largest U.S. apple-producing
state, is using remote sensing techniques borrowed from NASA and the
military to do an automatic, hands-off sampling of every single apple
before it gets to your handsor mouth.
Washington State produces almost half the nation's applesand
is partially funding Lu's workwhile New York and Michigan together
produce another 20 percent of the annual crop. Lu's research is critical
to these and all other U.S. apple-producing areas.
After joining the ARS Sugarbeet and Bean Research Unit in East Lansing,
Michigan, in 1999, Lu visited packinghouses in Michigan and Washington
to help him understand industry's needs.
Apple packinghouses currently rely on digital camera imagery to sort
apples by surface appearance only, flagging those that are visibly defective
or the wrong size or color.
"That system is literally skin-deep," Lu says. "It can't
detect bruises beneath the skin."
Lu's system would bounce light off apples one at a time as they pass
by on processing lines. The returning light would be detected by an
imaging spectrometer to create a spectral image of the apple on a computer
screen. Specially designed software would allow the computer to sort
the apples by internal quality attributes required for various grades.
Lu's tests have shown that his system can detect bruises deep within
the apple's flesh. But first he is focusing on the top two things that
make a great-tasting applesugar content and firmness. Lu developed
mathematical equations that relate sugar content to the amount of light
absorbed by an apple and firmness to the amount of light bounced off
the apple. He hopes to expand the system to detect acid content.
Industry studies have shown there to be different demands for various
types of apples, Lu says. "Oldsters tend to prefer softer, sweeter
apples, while youngsters like them hard and sour," he says. "With
a taste- and firmness-sorting system, each apple gets to the right person."
Lu is confident that his work with applesand cherries, toowill
be easy to adapt to oranges, peaches, or pears. His system could be
merged with current digital imagery systems with very little modification.By
Agricultural Research Service Information Staff.
This research is part of Quality and Utilization of Plant and Animal
Products, an ARS National Program (#306) described on the World Wide
Web at http://www.nps.ars.usda.gov.
|"Making the Grade" was published in the August 2002 issue of Agricultural Research magazine.|