The cheeselet, also known as ġbejna, is a popular traditional Maltese delicacy. During the ripening process, cheeselets can become contaminated with fungi, resulting in a poorer quality product.
Since high-quality food is a primary goal for food industries, producers are always looking for novel approaches to detect any potential contaminations at an early stage. Currently, standard testing typically involves chemical and microbiological tests which are time-consuming and destructive.
For the past two years, the Centre for Biomedical Cybernetics, together with the Department of Food Sciences and Nutrition, both within the University of Malta, and Farm Fresh Ltd have been working on a collaborative project to develop an imaging system to detect fungi at an early stage in dairy products, with a focus on cheeselets.
In this project entitled ‘Food Inspection using Hyperspectral Imaging’ (FIHI), a hyperspectral imaging system was used to scan food items for contaminants. The human eye detects visible light in three wavelength bands – red, blue and green. However, hyperspectral imaging divides the spectrum into hundreds of narrow bands extending beyond the visible spectrum.
Through hyperspectral imaging, it is possible to obtain a spectrum for each pixel in the image and this can yield much more information than a typical digital camera or the naked eye can provide. The hyperspectral data provides a form of spectral ‘fingerprint’ of the food item being inspected, which can be used for early fungal detection and identification.
For this project, cheeselets were prepared at our laboratories, then injected with fungal strains. The cheeselets were monitored over a number of days. By analysing the hyperspectral data, it was possible to distinguish contaminated samples from uncontaminated ones, even before the fungal growth became visually evident.
Figure 1(a) shows a standard image of a contaminated cheeselet. At this stage it is difficult to visually detect the presence of any moulds because at early stages the fungi are of a whitish colour. Figure 1(b) shows the processed image using the hyperspectral data, where contaminated regions are highlighted in red. The results from the FIHI project show that hyperspectral imaging has can detect food contamination at an early stage in a rapid, non-contact and non-destructive manner.
This work forms part of the FIHI Project financed by the Malta Council for Science & Technology, for and on behalf of the Foundation for Science and Technology, through the FUSION: R&I Technology Development Programme.
Jessica Falzon is a research support officer at the Centre for Biomedical Cybernetics.
Sound bites
• Raw milk is the ideal environment for the growth of many microorganisms since it has the ideal acidity value ( pH value of 6.6). Microorganisms can be present in the farm premises, feed, milk equipment and cows’ teats and udders. It was found that when the rate of milking is high, the milking machines enlarge and deform the cows’ teat duct, resulting in a higher amount of bacteria present in the udder. To minimise or avoid bacterial contamination of raw cow milk, one must ensure that cows are healthy. Proper milking procedures and good hygiene together with the use of machines will help in the prevention of bacterial contamination.
https://onlinelibrary.wiley.com/doi/full/10.1111/1541-4337.12526
• Lactic acid bacteria (LAB) is one of the most important groups of probiotic organisms, usually found in fermented dairy products and it has many benefits, one of which is preventing colon cancer. Different strains of LAB show different behaviour. Some strains may encourage colon cancer growth but other strains may shrink the tumour mass. From experiments, it was found that LAB such as Lactobacillus rhamnosus ATCC9595 helped in preventing this type of cancer.
https://www.researchgate.net/publication/49687659_Beneficial_effects_of_lactic_acid_bacteria_
on_human_beings
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Did you know?
• NASA created the hyperspectral imaging technology about 30 years ago but companies started using hyperspectral cameras recently as they were very expensive and large.
• The Technical Research Centre of Finland modified an iPhone to take hyperspectral images.
• Hyperspectral imaging is being used as an imaging modality for disease diagnosis and image-guided surgery.
• The smallest hyperspectral cameras are the xiQ cameras having dimensions of 26.4mm x 26.4mm x 31mm (length x width x height) and weighing 31g.