Advancing Mycotoxin Detection in Food and Feed: Novel Insights from Surface-Enhanced Raman Spectroscopy (SERS).

The implementation of low-cost and rapid technologies for the on-site detection of mycotoxin-contaminated crops is a promising solution to address the growing concerns of the agri-food industry. Recently, there have been significant developments in surface-enhanced Raman spectroscopy (SERS) for the direct detection of mycotoxins in food and feed. This review provides an overview of the most recent advancements in the utilization of SERS through the successful fabrication of novel nanostructured materials. Various bottom-up and top-down approaches have demonstrated their potential in improving sensitivity, while many applications exploit the immobilization of recognition elements and molecular imprinted polymers (MIPs) to enhance specificity and reproducibility in complex matrices. Therefore, the design and fabrication of nanomaterials is of utmost importance and are presented herein. This paper uncovers that limited studies establish detection limits or conduct validation using naturally contaminated samples. One decade on, SERS is still lacking significant progress and there is a disconnect between the technology, the European regulatory limits, and the intended end-user. Ongoing challenges and potential solutions are discussed including nanofabrication, molecular binders, and data analytics. Recommendations to assay design, portability, and substrate stability are made to help improve the potential and feasibility of SERS for future on-site agri-food applications.

Utilization of Hyperspectral Imaging with Chemometrics to Assess Beef Maturity.

There is a growing demand from consumers for more assurance in premium food products such as beef and especially steak. The quality of beef steak is primarily dictated by the maturation which ultimately influences its taste and flavor. These enhanced qualities have resulted in steak becoming a premium product that consumers are willing to pay a premium price for. A challenge, however, is analyzing the maturity of beef by traditional analytical techniques. Hyperspectral imaging (HSI) is a methodology that is gaining traction mainly due to miniaturization, improved optics, and software. In this study, HSI was applied to wet aged beef supplied at various stages of maturity, with spectral data generated using a portable hyperspectral camera. Two trials were conducted over a five-month period: (i) proof of principle and (ii) a bespoke sampling trial for the industry. With the support of industry participation, all samples were sourced from a highly reputable UK/Ireland supplier. To enhance data interpretation, the spectral data collected were combined with multivariate analysis. A range of chemometric models were generated using unsupervised and supervised methods to determine the maturity of the beef, and external validation was performed. The external validation showed good accuracy for "unknown samples" tested against the model set and ranged from 74 to 100% for the different stages of maturity (20, 30, and 40 days old). This study demonstrated that HSI can detect different maturity timepoints for beef samples, which could play an important role in solving some of the challenges that the industry faces with ensuring the authenticity of their products. This is the first time that portable HSI has been coupled with chemometric modeling for assessing the maturity of beef, and it can serve as a model for other food authenticity and quality applications.

A model framework to communicate the risks associated with aflatoxins.

Risk communication is defined as the interactive exchange of information and opinions concerning risk, risk-related factors and risk perceptions amongst all the stakeholders of food safety throughout the risk analysis process. The interactive exchange of information occurs at three different levels i.e. informed level, dialogue level and engagement level. For an effective food safety risk communication (FSRC), it is important that the information should adhere to the core principles of risk communication which are transparency, openness, responsiveness and timeliness. Communication of a food safety risk within all the components of risk communication strategy constitutes a complex network of information flow that can be better understood with the help of a framework. Therefore, a model framework to communicate the risks associated with aflatoxins (AFs) dietary intake has been developed with the aim of (a) creating general awareness amongst public and (b) involving industry stakeholders in the prevention and control of risk. The framework has been motivated by the learnings and best practices outlined in the identified technical guidance documents for risk communication. Risk assessors, risk managers, industry stakeholders and general public have been identified as the major stakeholders for the present framework. Amongst them, industry stakeholders and general public has been selected as the major target audience for risk managers. Moreover, population residing in low- and middle-income countries (LMIC) has been identified as the main target group to reach.

Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence.

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and quadratic discriminant analyses, k-nearest neighbors, random forest, support vector machine, and linear regression, as well as ensemble and majority voting methods, were used to explore spectroscopy data measured on fillets and to train classification models to predict freshness. Our results show that multi-mode spectroscopy achieves 95% accuracy, improving the accuracies of the FL, VIS-NIR and SWIR single-mode spectroscopies by 26, 10 and 9%, respectively. We conclude that multi-mode spectroscopy and data fusion analysis has the potential to accurately assess freshness and predict shelf life for fish fillets and recommend this study be expanded to a larger number of species in the future.

Handheld SERS coupled with QuEChERs for the sensitive analysis of multiple pesticides in basmati rice.

Pesticides are a safety issue globally and cause serious concerns for the environment, wildlife and human health. The handheld detection of four pesticide residues widely used in Basmati rice production using surface-enhanced Raman spectroscopy (SERS) is reported. Different SERS substrates were synthesised and their plasmonic and Raman scattering properties evaluated. Using this approach, detection limits for pesticide residues were achieved within the range of 5 ppb-75 ppb, in solvent. Various extraction techniques were assessed to recover pesticide residues from spiked Basmati rice. Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERs) acetate extraction was applied and characteristic spectral data for each pesticide was obtained from the spiked matrix and analysed using handheld-SERS. This approach allowed detection limits within the matrix conditions to be markedly improved, due to the rapid aggregation of nanogold caused by the extraction medium. Thus, detection limits for three out of four pesticides were detectable below the Maximum Residue Limits (MRLs) of 10 ppb in Basmati rice. Furthermore, the multiplexing performance of handheld-SERS was assessed in solvent and matrix conditions. This study highlights the great potential of handheld-SERS for the rapid on-site detection of pesticide residues in rice and other commodities.

Assessment of the Analytical Performance of Three Near-Infrared Spectroscopy Instruments (Benchtop, Handheld and Portable) through the Investigation of Coriander Seed Authenticity.

The performance of three near-infrared spectroscopy (NIRS) instruments was compared through the investigation of coriander seed authenticity. The Thermo Fisher iS50 NIRS benchtop instrument, the portable Ocean Insights Flame-NIR and the Consumer Physics handheld SCiO device were assessed in conjunction with chemometric modelling in order to determine their predictive capabilities and use as quantitative tools through regression analysis. Two hundred authentic coriander seed samples and ninety adulterated samples were analysed on each device. Prediction models were developed and validated using SIMCA 15 chemometric software. All instruments correctly predicted 100% of the adulterated samples. The best models resulted in correct predictions of 100%, 98.5% and 95.6% for authentic coriander samples using spectra from the iS50, Flame-NIR and SCiO, respectively. The development of regression models highlighted the limitations of the Flame-NIR and SCiO for quantitative analysis, compared to the iS50. However, the results indicate their use as screening tools for on-site analysis of food, at various stages of the food supply chain.

The potential of handheld near infrared spectroscopy to detect food adulteration: Results of a global, multi-instrument inter-laboratory study.

Fraud in the food supply system will be exacerbated by shortages caused by climate change and COVID-19's impact. The dried herbs market exemplifies complex supply chains attractive to criminals seeking financial gain. Real-time remote testing is achievable through development of globally accessible chemometric models for portable near infrared devices, deployed throughout supply chains. This study describes building of models for detection of oregano adulteration, on portable near infrared devices, and comparison to a laboratory-based Fourier-Transform Infrared spectroscopy method. 33/34 portable devices were able to correctly classify 5 out of 6 samples successfully with all adulterated samples being correctly classified following the use of appropriate transferability pre-processing routines. The devices native setup shows limited ability to perform a true screening of oregano using the setup offered. However modifications to the setup could in the future offer a solution that facilitates fit-for-purpose real time detection of adulterated samples within the supply chain.

A rapid food chain approach for authenticity screening: The development, validation and transferability of a chemometric model using two handheld near infrared spectroscopy (NIRS) devices.

This study assesses the application of a handheld, near infrared spectroscopy (NIRS) device, namely the NeoSpectra Micro, for the determination of oregano authenticity. Utilising a large sample set of oregano (n = 295) and potential adulterants of oregano (n = 109), models were developed and validated using SIMCA 15 software. The models demonstrated excellent predictability for the determination of authentic oregano and adulterant samples. The optimal model resulted in a 93.0% and 97.5% correct prediction for oregano and adulterants, respectively. Different standardisation approaches were assessed to determine model transferability to a second NIRS device. In the case of the second device, the best predictions were achieved with data that had not undergone any spectral standardisation (raw). Subsequently, the optimal model was able to correctly predict 90% of authentic oregano samples and 100% of the adulterant samples on the second device. This study demonstrates the potential of the device to be used as a simple, cost effective, reliable and handheld screening tool for the determination of oregano authenticity, at various stages of the food supply chain. It is believed that such forms of monitoring could be highly beneficial in other areas of food authenticity analysis to help combat the negative economical and health implications of food fraud.

Recent food safety and fraud issues within the dairy supply chain (2015-2019).

Milk and milk products play a vital role in diets around the globe. Due to their nutritional benefits there has been an increase in production and consumption over the past thirty years. For this growth to continue the safety and authenticity of dairy products needs to be maintained which is a huge area of concern. Throughout the process, from farm to processor, different sources of contamination (biological, chemical or physical) may occur either accidently or intentionally. Through online resources (the EU Rapid Alert System for Food and Feed (RASFF) and HorizonScan) safety and fraud data were collected from the past five years relating to milk and milk products. Cheese notifications were most frequently reported for both safety alerts (pathogenic micro-organisms) and fraud incidences (fraudulent documentation). Alongside the significant number of biological contaminations identified, chemical, physical and inadequate controls (in particular; foreign bodies, allergens, industrial contaminants and mycotoxins) were also found. Although the number of incidents were significantly smaller, these contaminants can still pose a significant risk to human health depending on their toxicity and exposure. Grey literature provided a summary of contamination and fraud issues from around the globe and shows its potential to be used alongside database resources for a holistic overview. In ensuring the integrity of milk during ever changing global factors (climate change, competition between food and feed and global pandemics) it is vital that safety and authenticity issues are continually monitored by industry, researchers and governing bodies.

The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools.

The spice paprika (Capsicum annuum and frutescens) is used in a wide variety of cooking methods as well as seasonings and sauces. The oil, paprika oleoresin, is a valuable product; however, once removed from paprika, the remaining spent product can be used to adulterate paprika. Near-infrared (NIR) and Fourier transform infrared (FTIR) were the platforms selected for the development of methods to detect paprika adulteration in conjunction with chemometrics. Orthogonal partial least squares discriminant analysis (OPLS-DA), a supervised technique, was used to develop the chemometric models, and the measurement of fit (R2) and measurement of prediction (Q2) values were 0.853 and 0.819, respectively, for the NIR method and 0.943 and 0.898 respectively for the FTIR method. An external validation set was tested against the model, and a receiver operating curve (ROC) was created. The area under the curve (AUC) for both methods was highly accurate at 0.951 (NIR) and 0.907 (FTIR). The levels of adulteration with 100% correct classification were 50-90% (NIR) and 40-90% (FTIR). Sudan I dye is a commonly used adulterant in paprika; however, in this study it was found that this dye had no effect on the outcome of the result for spent material adulteration.

Hydrophilic Divinylbenzene for Equilibrium Sorption of Emerging Organic Contaminants in Aquatic Matrices.

Hydrophilic divinylbenzene (DVB) (Bakerbond) has surfaced as a promising sorbent for active sampling of analytes from aqueous matrices over a very broad polarity range. Given this, hydrophilic DVB may likewise offer potential for passive sampling, if sorbent/water partitioning coefficients (Ksw) were to be available. In this work, static exposure batch experiments were performed to quantitatively study the equilibrium sorption of 131 environmentally relevant organic contaminants (P values ranging from -1.30 to 9.85) on hydrophilic DVB. The superior affinity of hydrophilic DVB, as compared to Oasis HLB, for compounds with a broad polarity range was confirmed by functional Fourier-transform infrared spectroscopy and Raman characterization, demonstrating the presence of carboxyl moieties. Concentration effects were studied by increasing compound concentrations in mixture experiments and resulted in the steroidal endocrine disrupting compounds in higher Ksw, while lower Ksw were obtained for the (alkyl)phenols, personal care products, pesticides, pharmaceuticals, and phthalates. Nevertheless, Ksw remained constant in the said design for equilibrium water concentrations at environmentally relevant seawater levels. An independent analysis of thermodynamic parameters (change in enthalpy, entropy, and Gibbs free energy) revealed the nature of the main partitioning processes. While polar (log P < 4) compounds were mainly served by physisorption, nonpolar (log P > 4) compounds also exhibited binding by multiple hydrogen bonding. In conclusion, this research facilitates the future application of hydrophilic DVB for active as well as passive sampling in the analysis of organic contaminants for monitoring purposes and for toxicity testing.

Rapid detection and specific identification of offals within minced beef samples utilising ambient mass spectrometry.

The morphological transformation of beef tissues after various processing treatments facilitates the addition of cheap offal products. Undetectable to the naked eye, analytical techniques are required to identify such scenarios within minced and processed products. DNA methodologies are ill-equipped to detect adulteration of offal cuts from the same species and vibrational spectroscopic studies, although rapid and non-destructive, have proved inconclusive as to whether the specific adulterant can be identified. For the first time we present a mass spectrometric approach employing an ambient ionisation process to eliminate sample preparation and provide near-instantaneous results. Rapid evaporative ionisation mass spectrometry (REIMS) was used to assess its capabilities of detecting minced beef adulteration with beef brain, heart, kidney, large intestine and liver tissues and chemometric analysis enabled unique or significant markers to be identified. The adulteration levels detected with the REIMS technology when analysing raw adulterated beef burgers were; brain (5%); heart (1-10%); kidney (1-5%); large intestine (1-10%) and liver (5-10%). For boiled adulterated samples; brain (5-10%); heart (1-10%); kidney (1-5%); large intestine (1-10%) and liver (5-10%). REIMS allows rapid and specific identification of offal cuts within adulterated beef burgers and could provide a paradigm shift across many authenticity applications.

The Rapid Detection of Sage Adulteration Using Fourier Transform Infra-Red (FTIR) Spectroscopy and Chemometrics.

Background: Sage, a common term for the various species of the genus Salvia L., is an herb that is mainly used as a seasoning, or for medicinal purposes. Valuable herbs such as sage, are under constant threat from criminals dealing in economically motivated adulteration. Objective: In this study, the development of a rapid screening technique to detect adulteration in sage was developed using FTIR and chemometrics. Method: A range of sage samples were collected, along with possible known adulterants, olive leaves, myrtle leaves, sumac, hazelnut leaves, cistus and phlomis, strawberry tree leaves and sandalwood. The samples were analyzed on the Thermo Nicolet iS5 FTIR with iD7 attenuated total reflectance accessory and diamond crystal. Chemometric techniques were applied to convert this raw spectral data obtained from the instrument into qualitative models. The qualitative chemometric models for adulteration detection were obtained using principal component analysis and orthogonal partial least squares-discriminant analysis following preprocessing of the spectra. Results: The orthogonal partial least squares-discriminant analysis models had a measurement of fit of 0.978 and 0.952 and a measurement of prediction of 0.975 and 0.936 for binary and multiclass models, respectively. The receiver operating curves following external validation had an area under the curve of 1, indicating excellent method performance. Conclusions: The use of FTIR and chemometrics can potentially screen unknown sage samples for adulteration and can be used in the fight against fraud in the herb and spice industry.

Development of a comprehensive analytical platform for the detection and quantitation of food fraud using a biomarker approach. The oregano adulteration case study.

Due to increasing number of food fraud incidents, there is an inherent need for the development and implementation of analytical platforms enabling detection and quantitation of adulteration. In this study a set of unique biomarkers of commonly found oregano adulterants became the targets in the development of a LC-MS/MS method which underwent a rigorous in-house validation. The method presented very high selectivity and specificity, excellent linearity (R2>0.988) low decision limits and detection capabilities (<2%), acceptable accuracy (intra-assay 92-113%, inter-assay 69-138%) and precision (CV<20%). The method was compared with an established FTIR screening assay and revealed a good correlation of quali- and quantitative results (R2>0.81). An assessment of 54 suspected adulterated oregano samples revealed that almost 90% of them contained at least one bulking agent, with a median level of adulteration of 50%. Such innovative methodologies need to be established as routine testing procedures to detect and ultimately deter food fraud.

A real time metabolomic profiling approach to detecting fish fraud using rapid evaporative ionisation mass spectrometry.

INTRODUCTION: Fish fraud detection is mainly carried out using a genomic profiling approach requiring long and complex sample preparations and assay running times. Rapid evaporative ionisation mass spectrometry (REIMS) can circumvent these issues without sacrificing a loss in the quality of results. OBJECTIVES: To demonstrate that REIMS can be used as a fast profiling technique capable of achieving accurate species identification without the need for any sample preparation. Additionally, we wanted to demonstrate that other aspects of fish fraud other than speciation are detectable using REIMS. METHODS: 478 samples of five different white fish species were subjected to REIMS analysis using an electrosurgical knife. Each sample was cut 8-12 times with each one lasting 3-5 s and chemometric models were generated based on the mass range m/z 600-950 of each sample. RESULTS: The identification of 99 validation samples provided a 98.99% correct classification in which species identification was obtained near-instantaneously (≈ 2 s) unlike any other form of food fraud analysis. Significant time comparisons between REIMS and polymerase chain reaction (PCR) were observed when analysing 6 mislabelled samples demonstrating how REIMS can be used as a complimentary technique to detect fish fraud. Additionally, we have demonstrated that the catch method of fish products is capable of detection using REIMS, a concept never previously reported. CONCLUSIONS: REIMS has been proven to be an innovative technique to help aid the detection of fish fraud and has the potential to be utilised by fisheries to conduct their own quality control (QC) checks for fast accurate results.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach.

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Determination of the Mycotoxin Content in Distiller's Dried Grain with Solubles Using a Multianalyte UHPLC-MS/MS Method.

There are more than 300 potential mycotoxins that can contaminate food and feed and cause adverse effects in humans and animals. The data on the co-occurrence of mycotoxins in novel animal feed materials, such as distiller's dried grain with solubles (DDGS), are limited. Thus, a UHPLC-MS/MS method for the quantitation of 77 mycotoxins and other fungal metabolites was used to analyze 169 DDGS samples produced from wheat, maize, and barley and 61 grain samples. All DDGS samples analyzed were contaminated with 13-34 different mycotoxins. Fumonisins were present in all 52 maize DDGS samples (81.0-6890 µg/kg for fumonisin B1), and deoxynivalenol was present in all 99 wheat DDGS samples (39.3-1120 µg/kg). A number of co-occurring mycotoxins were also identified. Due to the high co-occurrence of mycotoxins, routine screening of the animal feed ingredients is highly recommended to allow the highlighted risks to be effectively managed.

Origin authentication of distillers' dried grains and solubles (DDGS)--application and comparison of different analytical strategies.

In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.

Classification the geographical origin of corn distillers dried grains with solubles by near infrared reflectance spectroscopy combined with chemometrics: A feasibility study.

In this study, 137 corn distillers dried grains with solubles (DDGS) samples from a range of different geographical origins (Jilin Province of China, Heilongjiang Province of China, USA and Europe) were collected and analysed. Different near infrared spectrometers combined with different chemometric packages were used in two independent laboratories to investigate the feasibility of classifying geographical origin of DDGS. Base on the same dataset, one laboratory developed a partial least square discriminant analysis model and another laboratory developed an orthogonal partial least square discriminant analysis model. Results showed that both models could perfectly classify DDGS samples from different geographical origins. These promising results encourage the development of larger scale efforts to produce datasets which can be used to differentiate the geographical origin of DDGS and such efforts are required to provide higher level food security measures on a global scale.

Identification of vegetable oil botanical speciation in refined vegetable oil blends using an innovative combination of chromatographic and spectroscopic techniques.

European Regulation 1169/2011 requires producers of foods that contain refined vegetable oils to label the oil types. A novel rapid and staged methodology has been developed for the first time to identify common oil species in oil blends. The qualitative method consists of a combination of a Fourier Transform Infrared (FTIR) spectroscopy to profile the oils and fatty acid chromatographic analysis to confirm the composition of the oils when required. Calibration models and specific classification criteria were developed and all data were fused into a simple decision-making system. The single lab validation of the method demonstrated the very good performance (96% correct classification, 100% specificity, 4% false positive rate). Only a small fraction of the samples needed to be confirmed with the majority of oils identified rapidly using only the spectroscopic procedure. The results demonstrate the huge potential of the methodology for a wide range of oil authenticity work.