2.3.1 Focus on portable devices

2.3.1 Focus on portable devices

Technology submission 7

Food analysis has to consider the thousands of ingredients and additives with different chemical compositions, as well as how different food manufacturing processes affect them. The existing portable devices can essentially be grouped into two categories:

1) devices to specifically analyse one or a few analytes and,

2) devices that generate fingerprint profiles, which are typically used for screening analysis.

The increasing number of analytes make it practically and economically impossible to test for every single compound in a targeted analysis. However, there is a different approach known as non-targeted analysis also referred to as untargeted, in which the analytical technology does not test for specific compounds but generates composition fingerprints. Typical fingerprints for ingredients are stored in databases. Sample fingerprints are then compared with the typical fingerprints stored in the database. Variations proven to be statistically different from the typical profile are called abnormal samples. One of the main advantages of non-targeted analysis is the fact that one can potentially discover new adulterants that were previously unknown, simply based on an aberration of the spectrum. The aberration is then investigated to identify the cause of it. The cause for the abnormality is often not known in non-targeted analysis, requiring additional analytical investigation with targeted methods to identify the identity of the compound(s) causing the deviation. Yet, most of the devices have the algorithms already adjusted to detect some of the compounds based on their spectrum.

The technology enables the so-called Smart Sampling, a procedure where the decision of which sample to take is supported by a device (e.g., a portable NIR or RAMAN spectrometer). The approach consisting of a portable device allows the stakeholders to perform an on-site screening of the product. Screening locally would provide a quick detection of products with deviating profiles, allowing the examination of a larger quantity of products with aberrant profiles. Samples would then be taken from those products and sent to the laboratory for confirmatory analysis. This would identify the substance causing the deviation, i.e., the potential adulterant.

Cases of Smart Sampling can be observed in different situations. The portable device can perform a Near Infrared (NIR) analysis, which is a spectroscopic technique that uses the naturally occurring electromagnetic spectrum. NIR is considered an accurate and rapid analysis method that is adequate for the quantitative determination of the main constituents in most types of food and agricultural products. For example, it can be used to test the freshness of fruit, to differentiate farmed from wild fish, or to identify a variety of types of a product, such as rice.

Furthermore, the mid-infrared portable spectrometer is another type of device that can be placed in any location with a fairly small footprint to perform an analysis on the composition of food. This is not a handheld-point device, but it can be placed on a table at a factory site. As an example, this device can be used to perform a trans-fat analysis.

Another possible option is to adopt a multi sensor approach, where different techniques are applied to perform a comprehensive study of the product. In this case, a combination of sensors measures fluorescence, visible and UV light, as well as light in the near infrared range. This can be used to determine the authenticity of the product, e.g., the authenticity of extra virgin olive oil.

These devices do not require a scientist to operate them nor to read the results, facilitating the implementation of these technology options. Moreover, they will enable a risk-based sampling (Smart Sampling). The advent of these decision-support devices will ultimately shift the first line of analytical defence from laboratories to the food manufacturing sites, enabling risk-based sampling that will contribute to identifying quality issues and adulteration at an earlier stage than is now possible.

Submission received from FOCOS.

This technology submission allows us to discuss the interesting role that can be played by on-field portable testing devices which can provide a rapid analysis of the composition of the product.

This submission presents some unique elements if compared to the other technologies discussed in this chapter. These basically derive from the fact that, as anticipated, this submission has been designed as a portable technology for fast field testing. A field-site screening portable device permits the rapid identification of suspect samples which would have otherwise been taken randomly and sent to a laboratory. This approach saves both time and cost. Many of these portable devices require little or no sample preparation, which is another advantage. This approach will shift the first line of analytical defence from the laboratories to the food manufacturing sites or to the place where the control is performed, enabling risk-based sampling that will contribute to identifying quality issues and adulteration at an earlier stage.

The technology option does not require scientific expertise to be operated. Developed devices have easy-to-use user interfaces making them suitable for non-experts, for example trained factory workers, quality control managers and law enforcement agencies. When combined with some of the submissions presented in the chapter dedicated to supply chain security technology, this technology can complement rapid DNA analysis to check the information contained in the DNA ID of the food, improving the effectiveness of controls and law enforcement response against food frauds.

Source: FOCOS

For portable (as well as for laboratory) devices using non-targeted methodologies like NIR or FT-IR, appropriate reference databases are needed for the correct identification of aberrations from a reference profile. Some of these databases already exist, others will need to be built. A second important aspect that needs to be considered for such portable devices which are operated by non-scientific staff is that the validation needs to be extended. Current validations only evaluate the method in a laboratory environment. For portable devices, the validation needs to include use by non-scientific staff under field conditions (i.e. at food manufacturers’ sites or at port of entry).

Source: FOCOS

For what concerns the application to the risk scenarios, and given the focus on the composition of the food itself, the use of the technology can mitigate risks related, in particular, to repacking operations and the substitution of original products with counterfeit ones and the mislabelling of packaging to promote false claims related to the origin process or composition of the product. Furthermore, it can be used to identify if the product has been diluted or if there are adulterants in its composition. XFR can be used to identify the mineral composition of a product, which can be used to get an idea of if the product is more likely to come from the same place where it usually comes from, however, a specific “origin” identification like the one that can be obtained from a stable isotope ratio analysis is currently out of the scope of portable devices. XRF provides a multi-component, however, some of the main problems of XRF include the limited sensitivity for high mass elements and the need for pure samples. Even when an ultrapure reagent is used, impurities can appear, therefore it is mandatory to carefully measure the reference samples.1 At the current stage, XRF is a support tool for when reference materials from one location are available and need to be compared to another, but as mentioned, this cannot be executed on a global scale at this point due to lacking databases and sensitivity.

With regard to the three risk scenarios, the solution targets some of the issues, in particular:

For what concerns risk scenario 1, the forensic analysis element is capable of unequivocally identifying the geographical origin of the products as well as its components. However, it has to be taken into account that these technologies will come into play once an incident occurs or once a suspicion arises. In the case of portable devices, it would be feasible to make frequent analysis of the products during their processing in the supply chain. Portable devices can be used throughout the supply chain, and identify fraud early, before it reaches consumers, and potentially even before it reaches food manufacturers. They cannot be used to prevent the criminal activity from happening (unless their continuous use over time creates a dissuasive effect on criminals), but they can be used to unequivocally identify the adulteration of a product or the fraudulent behaviour of criminals involved in food fraud. For example, if there is a person checking every bag in the incoming raw materials department, criminals would likely realize that it is complicated to infiltrate the supply chain through this means. Therefore, the portable device would also have a deterrent effect once in operation. Another possible advantage can be attained if people in one supply chain use the same technology and scan every batch. In this case, the stakeholders would be able to

1 Katerinopoulou, K., Kontogeorgos, A., Salmas, C. E., Patakas, A., & Ladavos, A. (2020). Geographical origin authentication of agrifood products: A review. Foods, 9(4), 489. doi:10.3390/foods9040489

literally trace the material, based on its NIR profile (or SERS profile), through the supply chain. Consequently, these technologies may play a role in uncovering the following steps of the criminal plan:

 Control of the supply chain by using original packaging of the businesses controlled by the criminal group to market substandard and fraudulent products.

 Distribution of the falsified goods via the criminal group comprehensive and well- structured network, which includes wholesalers and supermarkets controlled by their frontmen.

 Copying local producers’ packaging design and subsequent infiltration of these products into the legitimate supply chain.

 Use of low-quality milk or dairy products.

By analysing the products marketed by the criminal group with the proposed technologies, it will be immediately visible that they are of low quality and that they do not originate from the correct geographical location. Adulterations and possible toxic/poisonous substances will also be revealed. On-field analysis with the portable device would enable stakeholders to perform a risk-based sampling that will contribute to identifying quality issues and adulteration at an earlier stage. The different analysis methods that can be adopted in portable devices for smart sampling offer a variety of options to examine a wide range of products. The analysis of specific elements in the composition of a product enables the clear authentication of the goods. Furthermore, by progressively analysing samples in the supply chain, it will also be able to trace back the source of the incident and present this evidence in court.

In the case of risk scenario 2, the technology may reduce the following steps of the criminal plan:

 Control of the anti-counterfeiting solutions to market fraudulent products using original packaging bearing authentication technology.

 Procurement of low-quality materials from areas with high levels of pollution, marketing vegetables grown using illicit pesticides as well as low-quality and diluted tomato concentrate.

 Develop a fully-fledged supply chain for vegetables and dairy products.

 Building a parallel market for catering food supplies targeting small shops.

If suspicions of criminal operations arose, the technology could be used to confirm what the criminal group was marketing using the original packaging or what elements do not correspond to the original composition of the product, and this element can also be brought in court as evidence.

The considerations already made in the case of risk scenario 1 are also valid for mitigating these steps of the criminal plan, since the technology is capable of recognizing the geographical origin of food products as well as their composition, including the presence of toxic ingredients and if they have been diluted. The technology cannot prevent infiltration but can be used to identify counterfeit products and their characteristics after the security breach occurs.

For what concerns risk scenario 3, the technology can limit the following steps:

 Selling fraudulent food as genuine via the e-supermarkets controlled by the criminal group. The same considerations presented for the previous risk scenarios also apply in this scenario in relation to analysis that can be performed in the case of incidents or following investigations to determine the nature of products marketed by the criminal group.

Other steps of the criminal plan highlighted by the risk scenarios cannot be prevented by using this type of technology.

Summary table for submission 7: possible application to limit risks highlighted by the scenarios

Scenario

Scenario 1: Infiltration of the dairy supply chain Step 1 – Control of the distribution market by owning or controlling legitimate operators.

Step 2 – Control of the supply chain using the technology owned by the controlled legitimate operators.

Step 3 – Copying local producers’ packaging design and subsequent infiltration of these products into the legitimate supply chain.

Step 4 – Procurement of low-level milk or dairy products, their packaging with falsified labels imitating the design of legitimate and well-known local producers, and their insertion into the supply chain.

Step 5 – Distribution of the falsified goods via the criminal group comprehensive and well- structured network, which includes wholesalers and supermarkets controlled by their frontmen.

Applicability of the solution

The technology will be able to analyse the marketed products and determine if they are fraudulent and/or of low quality. The technology solution is able to detect counterfeit products. However, it is relevant to highlight that this technology cannot prevent infiltration, rather it works as a mechanism to identify counterfeit products and their characteristics after the security breach occurs. Criminal activity cannot be prevented unless their continuous use over time creates a dissuasive effect on criminals, but they can be used to unequivocally identify the adulteration of a product or the fraudulent behaviour of criminals involved in food fraud. Adulterations and the presence of possible toxic/poisonous substances can be revealed by the technology. If the product is a milk powder, it may be possible to test with NIR-based devices which are handheld. The authentic spectra of the original is required – high quality milk powder (ideally across seasons to capture variation) and potentially adulterated, lower quality milk powder – to also train the system to distinguish the differences. If the product is liquid milk, options include: a top-level scan done by portable XRF to determine the minerals and metals in a dairy product. If it has been adulterated with a lower quality one, the mineral composition is likely to be different. This is not the most sensitive method, but it is handheld. The second option is the use of FT-IR devices. They can determine if milk has been diluted, if the protein level is lower or if other materials have been added. However, this is not handheld, even if it has a small size footprint. Again, it would be important to have authentic reference samples. These could be samples pulled directly from the farmers when they are milking the cattle. The previous considerations apply to this step. The solution can identify products that are fraudulent, of low quality and whether they do not originate from the correct geographical location.

Scenario 2: Parallel market for catering supplies Step 1 – Control over legitimate businesses.

Step 2 – Control of the anti-counterfeiting solutions used by the infiltrated businesses.

Step 3 – Develop a fully-fledged supply chain for vegetables and dairy products. In case of proven or suspected criminal operations, the technology can be used to confirm what the criminal group was marketing using the original packaging, and the anti-counterfeiting features and this element can be brought in court as evidence.

For solid products, NIR can be used to test authenticity and composition, including the fat, protein, and sugars of a product – any changes may be an indication of adulteration. However, for composite products this may be more complicated. For example, if you have pure minced meat, you will obtain similar profiles every time. If you have a sausage with varying ingredients, your profile will significantly differ. Therefore, NIR is useful for single ingredient (solid) products, but less useful if you test ready meals.

The same considerations described in step 3 of risk scenario 1 apply to this step.

Step 4 – Use of low quality and diluted materials. Since the technology is capable of recognizing the geographical origin of food products as well as their composition, including the presence of toxic ingredients and if they have been diluted. Dilution can be tested by FT-IR in a similar way to how the dilution of milk is detected. Tomato concentrate may be tested with NIR and XRF, applying two tools that are handheld.

Step 5 – Building a parallel market for catering food supplies targeting small shops As previously stated, the analysis would detect fraudulent or low-quality products as well as their origin. Yet, it cannot prevent infiltration, rather it works as a mechanism to identify counterfeit products and their characteristics after the security breach occurs. Criminal activity cannot be prevented, but they can be used to unequivocally identify the adulteration of a product.

Step 6 – Distortion of competition.

Scenario 3: E-commerce: criminal infiltration of online supermarket chains for home delivery of fake food Step 1 – Control of legitimate e-operators.

Step 2 – Selling fraudulent food as genuine through the controlled e-supermarkets.

Step 3 – Expansion of e-commerce market through the creation of a Super E-food app. The technology solution can be used to identify counterfeit products. Single component products are suitably analysed by NIR and potentially XRF, while liquids can be analysed by RAMAN, XRF (if they have minerals) and FT-IT.

Step 4 – Creation of dedicated social network groups/ pages to sell fraudulent products to final customers.