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NIR Hyperspectral Imaging Roots out Peanut Contamination

Photonics.com
Apr 2015
MADRID, April 7, 2015 — Near-infrared hyperspectral imaging could eliminate uncertainty for food producers required to include the warning “May contain peanuts” on their packaging.

A team of researchers from Spain and France have adapted the technique to quantify peanut contamination in powdered foodstuffs such as wheat flour.

“These results show the feasibility of using HSI systems for detecting traces of peanut and similar products that are present in low percentages in powder foods with contrasting spectra,” said Puneet Mishra, graduate research assistant at Universidad Politécnica of Madrid.

Any food product may contain traces of peanut if it is made with powdered foodstuffs, such as wheat flour, that were ground up in a facility that also grinds peanuts. This contamination can be impossible to prevent, and even trace levels of peanut can be a major problem for peanut-allergic individuals.

Several techniques already exist for detecting peanut contamination, such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR). But these techniques are destructive, work only with small samples and tend to be time-consuming.

Near-infrared (NIR) spectroscopy detects specific molecules based on their absorption and reflection of light. Peanut powder is known to generate different NIR spectra than wheat flour, powdered milk and cocoa. The problem with conventional NIR spectroscopy is that it collects an average NIR spectrum over a large area, meaning that trace peanut contamination may be missed.

NIR hyperspectral imaging, on the other hand, produces images in which every pixel contains spectral data. The researchers developed a scoring system to determine whether or not specific pixels in an image of wheat flour contained peanut powder, which allowed them to estimate the level of contamination.

They tested this system on samples of wheat flour spiked with powder from four different types of peanut, including raw, blanched and roasted. It was able to detect peanut concentrations as low as 0.01 percent, though it could only accurately determine the level of contamination between 0.1 and 10 percent.

Mishra and colleagues are now looking to apply the same technique to detecting contamination by other nuts that can also cause serious allergic reactions.

“Although peanut is the most common cause of nut allergy, peanut allergic patients are frequently also sensitive to tree nuts,” he said. “We are presently sampling different tree nut mixtures of almond, walnut and hazelnut to check the feasibility of HSI for detecting them.”

The research was published in the Journal of Near Infrared Spectroscopy (doi: 10.1255/jnirs.1141).

For more information, visit www.upm.es.


GLOSSARY
hyperspectral imaging
Methods for identifying and mapping materials through spectroscopic remote sensing. Also called imaging spectroscopy; ultraspectral imaging.
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