In March 2023, Dr Malcolm Burns, Head of the GMO Analytical Unit at the National Measurement Laboratory at LGC presented presented at the International Conference on GMO and New Genomic Techniques on 'Analytical strategies for detection of GMO's and NGT products- status and challenges'. The presentation explored some of the opportunities and challenges for the development of methods for the detection of NGT products.
You can now view Malcolm's presentation here.
Note: all information given in the presentation was correct at the time of the presentation in March 2023.
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This paper (purchase required) reports a proof-of-concept study to detect, with a point-of-use NIR scanner, the adulteration of ground almonds with apricot kernels . The authors built a classification model by preparing their own ground almond from different almonds (120 samples) purchased at local markets and then preparing blends (up to 50%, in 2% intervals) with ground apricot kernel. They collected NIR spectra using a portable and benchtop spectrometer and analyzed the data by Soft Independent Modeling of Class Analogy (SIMCA) and Conditional Entropy (CE) with machine learning algorithms to generate a classification model. They used Partial Least Square Regression (PLSR) and CE with machine learning algorithms to predict the levels of apricot kernel in ground almonds. The authors reported that both SIMCA and CE algorithms combined with spectral data obtained from the spectrometers provided very distinct clusters for pure and adulterated samples (100% accuracy). Both units also performed well in predicting apricot kernels using PLSR with rval>0.96 with a standard error prediction (SEP) 3.98%. They conclude that, based on the SIMCA, PLSR, and CE-based models, NIR spectroscopy showed great potential for real-time surveillance to detect apricot kernel adulteration.
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Spectrometric classification models are usually constructed by multivariate analysis of measurements from multiple samples from authenticated reference database. In this study (open access) the authors used a simplified approach. They tood a single measurement: the integrated IR spectrum between 3000-2800 cm2. They used factorial mixture design, on an Excel spreadsheet, to construct a calibration curve based only upon 3 reference samples: 100% Arabica, 100% Rustica and a 50/50 mix. They then validated the curve using a range of other mix proportions, and concluded that it was suitable for detecting Rustica adulteration in “pure Arabica” down to 2.5%. The authors propose this as a useful and cheap strategy for building specific classification models for the routine checking of adulteration in individual coffees that purportedly come from a consistent and well-characterised source.
In this publication (open access) the authors reviewed the potential frauds that could be applied to cultured meat, which of them could be detected by existing “conventional” meat test methods and controls, and which would require new authentication standards or testing. They highlighted some threats which would require a new risk-management approach such as
- Use of conventional chicken meat in cultivated chicken nuggets
- Use of mouse myoblasts for cell sheet-based porcine meat
- 3D-printed steak produced by Company A using Wagyu-sourced muscle cell imitated by Company B with non-Wagyu-sourced muscle cells labelled as “Wagyu”
- Imitation of a plant protein scaffold-based cultivated meat by mixing conventional meat mush with extruded plant protein
The authors propose a scheme for establishing cultured meat authentication standards (pictured)
A recent study (purchase required), “Qualitative assessment on the chances and limitations of food fraud prevention through distributed ledger technologies in the organic food supply chain”, set out to answer three questions using structured qualitative research. 1) To what extent can Distributive Ledger Techonolgies (DLTs) help to prevent food fraud against the background of routine activity theory, by controlling target or offender or functioning as guardian, respectively? 2) How are stakeholders in the organic food industry familiar with DLTs today? 3) What is the role of the human factor i.e., what are potential hurdles for the practical implementation of technical feasible measures?. Research methods included literature searches and stakeholder interviews. The authors conclude that the reason DLTs have not seen widespread adoption in the Organic supply chain include valid concerns about data protection, costs, business models, consumer perceptions, and digital infrastructure. They recommend ways in which these concerns could be addressed.
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A recent study (purchase required) reports a new rapid method to classify whether “cream” is dairy, vegetable-based, or dairy adulterated with small amounts of vegetable oil. The method requires no sample preparation, using rapid evaporative ionization mass spectrometry (REIMS, called the “ion knife” when originally developed for surgical diagnostics) to obtain a fingerprint of ions from lipids in the cream. 26 ions were picked using multivariate statistical analysis as salient contributing features to distinguish between milk fat cream and non-dairy cream. Then, employing discriminant analysis, decision trees, support vector machines, and neural network classifiers, machine learning models were utilized to classify non-dairy cream, milk fat cream, and small quantities of non-dairy cream adulterated in milk fat cream. These approaches were enhanced through hyperparameter optimization and feature engineering. The authors conclude that this artificial intelligent method of machine learning-guided REIMS pattern recognition can accurately identify adulteration of whipped cream.
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There are four Protected Designation of Origin (PDO) descriptors of fortified wines in Andalucía (‘Condado de Huelva’, ‘Jerez-Xérès-Sherry’, ‘Manzanilla-Sanlúcar de Barrameda’, and ‘Montilla-Moriles’). Within each PDO, there are recognised different categories according to their particular winemaking conditions such as the ageing process (Fino and Manzanilla, Oloroso, Amontillado and Palo Cortado). There is also a price premium dependent on the age of the wine.
This study (open access) aimed to differentiate volatile profiles of fortified wines obtained by headspace solid phase microextraction in conjunction with gas chromatography-mass spectrometry. From the analysis of 104 reference samples, the authors used chemometric tools to identify the marker volatile compounds most related to fortified wine types. 28 marker volatile compounds gave enough information to discriminate by ageing process (biological, oxidative, or mixed) providing useful markers for the identification of each specific type of fortified wine. Among them, some esters were strongly related to biological ageing, aldehydes and acids to oxidative ageing, and lactones to mixed ageing. These volatile molecules involved in their differentiation could explain the unique organoleptic characteristics or attributes of these PDO fortified wines.
This study used the chemometric analysis of colloid profiles to classify milk. Colloidal nanosystems were separated by Field Flow Fractionation (FFF) working in saline carrier. Rather than downstream detailed analysis of their composition, the FFF signals were measured directly. There was minimal preprocessing . A set of 47 bovine milk samples was analyzed: a single analysis yielded a characteristic multidimensional colloidal dataset, that once processed with multivariate tools allowed simultaneously four different discriminations: fat content, thermal treatment, brand and manufacturing plant. The work represents the first attempt to identify milk sub-typologies based on colloidal profiles, and the most complete study concerning multivariate analysis of FFF fingerprint. The authors recommend this as a sustainable technique, with limited pretreatment, non-toxic chemicals, and high throughput results. They conclude that the analytical methodology is fast, green, simple, and inexpensive and could offer great help in the field of quality control and fraud identification.
This review covers recent applications of metabolomic techniques to identify non-Halal components in a food or pharmaceutical products. Examples include the detection of pig meat and the differentiation of chicken meat that is Zabiha (slaughtered by cutting the neck without detaching the spinal cord) from non-Zabiha (completely detaching the neck). The paper highlights chemometric methods using data generated from small biological molecules (< 1500 kDA) measured by spectroscopic or chromatographic methods. The authors conclude that metabolomics is a valuable tool in authenticating Halal products.
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The UK Government Chemist Annual Review 2022 is published.
The Annual Review is a summary of referee casework, research projects, advice and impact of work carried out by the Government Chemist team during 2022.
Access the review here.
The US FDA have updated their guidance on implementation of the new CFR menu nutrition labelling requirements. They have invited comments on the guidance. Closing date for comments to be taken into account in the next revision is 12 February 2024.
The menu labelling rules only apply to standard menu items offered by “covered establishments,” which are defined as restaurants and similar retail food establishments with 20 or more locations doing business under the same name and offering for sale substantially the same menu items, as well as restaurants and similar retail establishments that register to voluntarily subject themselves to the menu labeling requirements. The rules require disclosure of calories on menu and menu boards, and require that other nutrition information (e.g., fat, sugar, protein) be available in written form on the premises and provided to the customer upon request.
The invitation to comment is here
The draft guidance (a Q&A format) is here
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The Analysis for Innovators Programme grants you special access to NML's world-leading experts. Submit your application and collaborate with us to solve your measurement and analytical challenges.
Through the Programme, the NML engages directly with businesses from sectors ranging from healthcare to food and cosmetics, providing access to our state-of-the-art measurement and analytical capabilities, helping them address problems and challenges in innovative ways, and offering bespoke solutions, not available commercially.
Over 90% of businesses completing an Analysis for Innovators Project have reported business growth due to increased productivity, and over 60% saw their competitiveness improved in their markets.
So if you have a food measurement challenge that you'd like help with, find out more about how the NML supports UK companies through the A4I programme here, and information about how to apply here.
Applications close: Wednesday 3 January 2024 @11:00am GMT.
Do you have a question regarding the Programme for the NML? Email a4i-nml@lgcgroup.com
Premium olive oil has always been a prime suspect for industrial-scale adulteration, theft or substitution risks. This year commodity prices have been particularly volatile and olive oil fraud has moved higher up the risk registers. Evidence that business-to-business fraud is occurring has continued to emerge over the past few weeks with police seizures of bulk quantities of adulterated oil in three different jurisdictions, multiple arrests, and freezing of bank accounts. In two cases the oil was intended for distribution on the global market.
In Spain …… fraudsters mixed cloudy oils – a sub-product of the olive oil producing process – with better quality olive oil so as to obtain the correct levels of fats and other markers to meet the EVOO. They also impeded traceability by not registering their companies’ oils.
In Italy …….. in a linked case, the carabinieri discovered a similar alleged falsification operation involving two large oil-processing companies.
In Brazil …….. there have been two unrelated bulk seizures, one in Panana where soybean oil had been tailored to pass off as EVOO and a national case where supply to major retailers was found to be low quality oil unfit for human consumption. The former case was revealed by NMR analysis.
Work conducted by scientists at the National Measurement Laboratory at LGC for the UK Government Chemist, in collaboration with the British Coffee Association, on the effect of roasting on the boron isotopic composition of coffee beans has been published.
Boron (11) isotope values of green and roasted coffee beans from 20 locations worldwide were studied with the aim to investigate boron isotope fractionation during roasting.
The study showed that boron isotopic composition of roasted coffee can be used as a marker of regional differences in coffee origin.
Access paper: https://doi.org/10.1016/j.foodchem.2023.138128
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An EU complaint filed against some of the biggest soft drinks brands would have ramifications for all food and drink packaging if upheld. Filed on 7 November by the Bureau Européen des Unions de Consommateurs (BEUC, the European Consumer Organisation), it is gaining coverage within the legal press.
The complaint alleges a breach of current law; it is not in anticipation of the new EU Green Claims Directive.
The basis of the complaint is that it is deliberately misleading to label plastic drinks bottles as “100% recyclable”, “made from 100% recycled material” or to use prominent recycling logos when the brand owners are aware that
- “100% recyclable” depends on many factors outside of the manufacturer’s control, including the available infrastructure, the sorting process and the recycling process
- “100% recycled” suggests that the bottle in its entirety is made from recycled materials, when bottle lids cannot be made of recycled materials by EU law and some brands also add non-recycled plastic to the body
- use of green imagery, such as closed loops, green logos or nature images, promotes the idea that the products have environmental neutrality or even a positive impact on the environment.
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“Organic” is a certification of a production system rather than a product. The permitted inputs vary slightly between countries. The EU organic production rules prohibit the use of GMOs, ionizing radiation, synthetic fertilizers, herbicides, and pesticides as well as the use of hormones and antibiotics. In the US a product can be labelled organic if it is certified to have been cultivated on soil that has not been treated with synthetic fertilizers or pesticides in the 3 years preceding harvest. Animals used for meat, milk, eggs, and other animal products must be fed 100 % organic feed and not be administered antibiotics or hormones.
The type of fertilizer or feed inputs can, in principle, be inferred from stable-isotope ratio analysis of the food product. This literature review (open access) examines recent applications of stable isotope ratio analysis in this field. The authors describe different isotope ratio mass spectrometry (IRMS) techniques, including bulk IRMS analysis and the combination of IRMS with novel sample preparation and compound extraction techniques. They also cover compound-specific IRMS analysis comprising mainly hyphenated techniques, such as GC-IRMS. They consider that this can overcome the limitations exhibited by bulk analysis. The review covers a wide range of food product categories, including cereals, vegetables, fruit, animal products, and seafood. The authors discuss the importance of statistical analysis in determining which stable isotopic compositions (δ(15N), δ(34S), δ(18O), δ(13C), or δ(2H)) could be used as reliable organic authenticity markers.
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This free 30 minute webinar recording from solicitors Stevens & Bolton gives an overview of the new corporate offence under the UK Economic Crime and Transparency Act 2022 of “Failure to Prevent Fraud”. It covers which companies are within scope and how companies can mitigate the risk. A particular scenario captured by this legislation is a rogue employee committing a fraud for the benefit of a customer rather than for personal or direct corporate gain.
The "sugar to acid ratio" or "Brix to acid ratio" is used to describe the taste or tartness of fruit juices. Higher Brix to acid ratios indicate a higher sugar content resulting in a less tart juice. This ratio can be manipulated by adding pulp-wash to adulterate the juice with the aim of achieving lower tartness levels.
A recent conference presentation reported a novel feasibility study to use two handheld NIR spectrometers as rapid screening techniques, in combination with class modelling (DD-SIMCA and soft-PLS-DA) and discrimination strategies (ensemble learning and hard-PLS-DA) to authenticate orange juice samples and identify levels of Brix to citric acid ratio in pulp-wash as adulterants.
It was reported that both NIR spectrometers coupled with DD-SIMCA demonstrated 100% sensitivity and specificity in calibration and prediction sets. Furthermore, ensemble learning approaches such as Gradient Boosting Tree (GBT) and Adaptive Boosting (Adaboost) coupled with the NIR Tellspec spectrometer were able to perfectly predict the levels of adulterants with a limit of detection (LOD) of 2% and 5% for Brix to citric acid ratio and pulp-wash, respectively. This outperformed hard-PLS-DA, which is the most commonly used technique in food control studies.
The abstract, and contact details of the authors, are here.
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The US FDA has issued guidance for Small and Medium Enterprises to comply with the upcoming (1 January 2024) Standard of Identity rules for yoghurt. Such guidance is a reminder to any laboratory testing compliance with a food’s “legal name” that the legal specification will vary depending on the country of sale.
The new US rules cover pH, minimum counts of active cultures or vitamins (if claimed). and minimum requirements for milk fat and milk solids. There are specific labelling requirements for lower fat yoghurts.
Photo by Dennis Klein on Unsplash
