Imaging technique evaluated for food authenticity testing

By Joseph James Whitworth contact

- Last updated on GMT

Spectral imaging in authenticity testing evaluated in pasta model

Related tags: Wheat, Eu

Spectral imaging shows potential as a non-destructive analytical approach for use in food authenticity testing, according to a study.

Using the adulteration of pasta as a model example, the research demonstrated the imaging techniques could rapidly distinguish between durum wheat and the adulterant common wheat and assign percentage adulteration levels.

It offers potential benefits over existing DNA approaches including time, processing (i​.e​. non-destructive) and no requirement for specialised training or expensive reagents/consumables.

“Other potential benefits associated with this approach for food authenticity testing include short testing times and high potential sample throughput, making the approach suited for in-line monitoring found within today’s food production industry​,” said the researchers.

Distinguishing which wheat is which

Multispectral imaging (MSI) and hyperspectral imaging (HSI) differ on the complexity of spectral data collected: hyperspectral systems measure energy in narrower and more numerous bands than multispectral systems.

The study focused on investigating the technique to distinguish between T​. durum ​and T​. aestivum ​wheat grains (important in the production of pasta) based on the spectral signature of each grain species, using a panel of deliberately adulterated wheat samples designed to be at or close to the EU legislative limit.

A panel of 23 wheat test samples (two calibration controls, 21 test mixtures) were prepared which represented different levels of adulteration.

It was made up of seven levels of sample adulteration, which represented 0%, 0.5%, 2%, 3%, 5%, 10%, and 100% (grain/grain) of T​. aestivum ​in total grain (T​. aestivum ​and T​. durum​).

Pasta products are typically based on durum wheat, a more costly species considered ideal for pasta.

Authenticity of pasta samples is determined using molecular biology techniques such as PCR which focus on DNA as the target analyte. Whilst relatively accurate, current DNA approaches often require relatively laborious upstream and complex sample preparation phases inclusive of destructive DNA extraction procedures

For manufacture of pasta, EU law allows up to 3% (w/w) contamination with other wheat (T​. aestivum ​or common wheat).

Based on visual methods alone, it is very hard to reliably tell the difference between the two cultivars of T​. aestivium ​and T​. durum ​cultivars used, when they are in a mixed sample, said the study.

Two spectral imaging instruments were evaluated: the VideometerLab 2, a MSI system distributed by Analytik and the NEO HySpex VNIR-1600, a HSI system distributed by Mapping Solutions.

“Low-level percentage adulteration samples (e.g. 0.5% grain/grain) appear to be more challenging for both instruments as demonstrated by the larger measurement uncertainty estimates.

“Given the analytical uncertainty that has been reported at this level using the accepted standard of real-time PCR approaches for quantitation of durum wheat adulteration… the larger uncertainty estimate was not unexpected and is comparable to that of real-time PCR.”

Spectral imaging potential

The researchers said the work provides evidence of the applicability of spectral imaging as a rapid and cost effective screening approach for testing grain shipments for potential adulteration, where any suspect samples could be further analysed using real-time PCR for confirmation of adulteration.

The team said further work should look at the applicability for determining differences based on more genotypes, cultivation practices, weather conditions, post-harvest storage conditions, etc and evaluate additional performance characteristics (e.g. the Limit of Detection) and applicability to other food matrices.

They added that unlike the pure grain samples used, real samples are likely to contain a range of impurities such as chaff and broken grain fragments so analytical performance could be improved by including distinguishing physical characteristics into the models employed for discrimination.

Source: Food and Nutrition Sciences, 7, 355-361

Feasibility Study for Applying Spectral Imaging for Wheat Grain Authenticity Testing in Pasta​”

Authors: Wilkes, T., Nixon, G., Bushell, C., Waltho, A., Alroichdi, A. and Burns, M

Related topics: Food Safety & Quality

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