Near Infrared Hyperspectral Imaging Detects Peanut Contamination

April 3, 2015

New research indicates that near infrared (NIR) hyperspectral imaging (HIS) may be an effective way to detect peanut contamination in processed foods (1).

New research indicates that near infrared (NIR) hyperspectral imaging (HIS) may be an effective way to detect peanut contamination in processed foods (1).

 

Even at trace levels, peanut contamination can be a major problem for people with severe allergies, potentially triggering a life-threatening reaction. 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 up peanuts, which means it can be impossible to prevent contamination from occurring.

 

It was already known that peanut powder generates NIR spectra that is different from those of various other powdered foodstuffs, including wheat flour, 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.

 

To solve that problem, a team of scientists at the Madrid Polytechnic University (UPM) in Spain and the French National Institute for Environmental and Agricultural Technologies (IRSTEA), led by Puneet Mishra, used NIR HIS. Each pixel can contain spectral information about peanut contamination, making NIR HIS much more sensitive than conventional NIR spectroscopy and allowing it to detect trace levels of peanut over a large area.

 

As a first test, the scientists confirmed that peanut powder generates NIR spectra that are different from wheat flour when analyzed by NIR HIS, allowing the two powders to be distinguished from each other.

 

Next, the team developed a scoring system that could determine whether or not specific pixels in an image of wheat flour contained peanut powder. Using this scoring system, they could then estimate the level of contamination simply by determining the percentage of pixels that contained spectra of peanut powder.

 

The team tested this system on samples of wheat flour spiked with powder from four different types of peanuts, including raw, blanched, and roasted, at concentrations varying between 0.01% and 10%. The system was able to detect peanut contaminations even at concentrations as low as 0.01%, although it could only accurately determine the level of contamination at between 0.1% and 10%.

 

Reference

 

(1) P. Mishra, A. Herrero-Langreo, P. Barreiro, J.M. Roger, B. Diezma, N. Gorretta, and L. Lleó, “Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis,” J. Near Infrared Spectrosc.23(1), 15–22 (2015). doi: http://dx.doi.org/10.1255/jnirs.1141