Vanilla e-sense

But there was more. The grapes used for 23 of the bottles were grown in one region of northern Italy, the expert asserted, while those in the other 30 bottles came from a different region—a region, it turns out, just 60 miles from the first and featuring only minor differences in soil and sunlight.

That degree of discrimination would be impressive in any tasting club. But it was especially notable because, in this case, the expert was a bundle of high-tech chemical probes.

The successful test of that electronic tongue and nose was one of several in recent years hinting that automated food and beverage sensors may someday match, or even outperform, their human counterparts.

Human sommeliers are not at risk of being replaced by machines just yet, scientists say, although a Japanese consortium recently released a Health and Food Advice Robot that can distinguish among 30 kinds of wine, as well as various cheeses and breads, and has the irritating capacity to warn its owner against poor eating habits.

But that day may come. Recent improvements in sensors, and in computer programs able to interpret their highly complex inputs, give credence to the once-discounted idea that machines may someday become the ultimate arbiters of taste.

Last month, for example, the US Agriculture Department launched a program that uses machines to grade livestock carcasses for official ratings of tenderness and flavour that for 80 years have been based solely on the judgment of journeymen meat graders.

The system is still being perfected, said William Sessions, associate deputy administrator of the department’s livestock and seed program, which oversees meat grading. “But a high percentage of the time we can predict with a large degree of accuracy the eating experience you will have.”

The robotic graders, being tested at four Nebraska slaughterhouses, capture photographic images of sides of beef as they cruise by at rates of up to 400 head per hour. The graders focus on the rib-eye muscle, between the 12th and 13th ribs, and measure the redness of the meat, the degree to which it is marbled with tasty fat, and the thickness of the outer fatty layer.

Human graders are being kept on hand to confirm the machines’ ratings and override the robots when necessary. But the degree of agreement is very high. And one handy thing about a hard-wired judge is that it is not susceptible to pressure from plant owners, some of whom have been known to lean on agency graders.

At the same time, placing trust in computers to make such economically important decisions raises risks, including “cyber-security issues,” Sessions said, “like somebody being able to hack into the system. It could be a huge advantage to a plant if the equation (in a machine’s software) were altered.” For that and other reasons, Sessions said, live employees will be needed “well into the future.”

Many university laboratories and companies have joined the race to develop e-noses and e-tongues, some with such evocative names as FreshSense and LibraNose.

The journal Nature last month described a Japanese-made hand-held fiber-optic infrared sensor that measures oleic acid levels in raw meat, reputed by some to be a better indicator of tastiness than conventional marbling measures.

In Australia, supermarkets already are using a tastiness rating system in which cuts of meat earn labels with as many as five stars, based on a number of automated inputs including fat depth, extent of marbling and post-slaughter aging.

And in Russia, Andrey Legin and colleagues at St. Petersburg University have made an electronic tongue that can distinguish among various blends of coffee or soft drinks just as accurately as people can – a potential boon for beverage makers wishing to ensure batch-to-batch consistency while avoiding the expense of human tasting panels.
-Rick WEISS (The Washington Post)