Detection Of Food Contaminants Research Articles

Method development and validation for acrylamide in potato cutlet by UHPLC-MS/MS

Surge in consumption of healthy and safe foods has challenged researchers to develop sensitive, precise, robust detection and quantification of food contaminants like acrylamide even if they are present in trace. Keeping this in view, a robust and sensitive analytical method was developed and validated for acrylamide quantification in a potato-based food product (potato cutlet), using LC-MSMS with positive electrospray ionization (+ESI). The method consists of adding acrylamide-d3 (deuterium labelled acrylamide) as an internal standard, extraction by modified QuEChERS method with d-SPE clean-up. Extracts were run on a reverse phase C-18 column for analysis by liquid chromatography. The limit of detection (LOD) and limit of quantification (LOQ) were determined as 0.7 and 2.0 μg kg−1, respectively, demonstrating the sensitivity of the method for trace detection. The developed method showed excellent results in terms of recoveries (91.0–109.16%), repeatability (RSD 1.8–10.60%), reproducibility (RSD 2.3–11.24%) and robustness (RSD 1.74–4.54%). The repeatability, reproducibility and robustness respectively, show the consistency, accuracy and stability of the developed method. The deviations in ion ratio and retention time were 17.25% and −0.01 min, respectively. Compared to previous findings, the current study has achieved lower LOD and LOQ levels that reveals the higher sensitivity of this method for acrylamide quantification in potato cutlet.

Application of Electrochemical Biosensors for Determination of Food Spoilage

Food security is significantly affected by the mass production of agricultural produce and goods, the growing number of imported foods, and new eating and consumption habits. These changed circumstances bring food safety issues arising from food spoilage to the fore, making food safety control essential. Simple and fast screening methods have been developed to detect pathogens and biomarkers indicating the freshness of food for safety. In addition to the traditional, sequential, chemical analytical and microbiological methods, fast, highly sensitive, automated methods suitable for serial tests have appeared. At the same time, biosensor research is also developing dynamically worldwide, both in terms of the analytes to be determined and the technical toolkit. Consequently, the rapid development of biosensors, including electrochemical-based biosensors, has led to significant advantages in the quantitative detection and screening of food contaminants. These techniques show great specificity for the biomarkers tested and provide adequate analytical accuracy even in complex food matrices. In our review article, we summarize, in separate chapters, the electrochemical biosensors developed for the most important food groups and the food safety issues they can ensure, with particular respect to meat and fish products, milk and dairy products, as well as alcoholic and non-alcoholic beverages.

Cas12a/Guide RNA-Based Platforms for Rapidly and Accurately Identifying Staphylococcus aureus and Methicillin-Resistant S. aureus.

In order to ensure the prevention and control of methicillin-resistant Staphylococcus aureus (MRSA) infection, rapid and accurate detection of pathogens and their resistance phenotypes is a must. Therefore, this study aimed to develop a fast and precise nucleic acid detection platform for identifying S. aureus and MRSA. We initially constructed a CRISPR-Cas12a detection system by designing single guide RNAs (sgRNAs) specifically targeting the thermonuclease (nuc) and mecA genes. To increase the sensitivity of the CRISPR-Cas12a system, we incorporated PCR, loop-mediated isothermal amplification (LAMP), and recombinase polymerase amplification (RPA). Subsequently, we compared the sensitivity and specificity of the three amplification methods paired with the CRISPR-Cas12a system. Finally, the clinical performance of the methods was tested by analyzing the fluorescence readout of 111 clinical isolates. In order to visualize the results, lateral-flow test strip technology, which enables point-of-care testing, was also utilized. After comparing the sensitivity and specificity of three different methods, we determined that the nuc-LAMP-Cas12a and mecA-LAMP-Cas12a methods were the optimal detection methods. The nuc-LAMP-Cas12a platform showed a limit of detection (LOD) of 10 aM (~6 copies μL-1), while the mecA-LAMP-Cas12a platform demonstrated a LOD of 1 aM (~1 copy μL-1). The LOD of both platforms reached 4 × 103 fg/μL of genomic DNA. Critical evaluation of their efficiencies on 111 clinical bacterial isolates showed that they were 100% specific and 100% sensitive with both the fluorescence readout and the lateral-flow readout. Total detection time for the present assay was approximately 80 min (based on fluorescence readout) or 85 min (based on strip readout). These results indicated that the nuc-LAMP-Cas12a and mecA-LAMP-Cas12a platforms are promising tools for the rapid and accurate identification of S. aureus and MRSA. IMPORTANCE The spread of methicillin-resistant Staphylococcus aureus (MRSA) poses a major threat to global health. Isothermal amplification combined with the trans-cleavage activity of Cas12a has been exploited to generate diagnostic platforms for pathogen detection. Here, we describe the design and clinical evaluation of two highly sensitive and specific platforms, nuc-LAMP-Cas12a and mecA-LAMP-Cas12a, for the detection of S. aureus and MRSA in 111 clinical bacterial isolates. With a limit of detection (LOD) of 4 × 103 fg/μL of genomic DNA and a turnaround time of 80 to 85 min, the present assay was 100% specific and 100% sensitive using either fluorescence or the lateral-flow readout. The present assay promises clinical application for rapid and accurate identification of S. aureus and MRSA in limited-resource settings or at the point of care. Beyond S. aureus and MRSA, similar CRISPR diagnostic platforms will find widespread use in the detection of various infectious diseases, malignancies, pharmacogenetics, food contamination, and gene mutations.

Concatenated DNA walking and rolling machines with programable interfacial tracks for kanamycin detection

Antibiotic residue has been emerged as serious threaten for food safety. In this work, we integrated enzyme-powered single-leg and multipedal DNA walkers and constructed concatenated DNA machine as signal amplifier for the sensitive detection of kanamycin. By integrating two kinds of motion pattern, the walking track particle not only guarantees the single-legged walking process, but also serves as multipedal walker to perform rolling process via interparticle relative motion. Through reasonable modulating the interface of track particle, the optimum enzyme reaction kinetics at interface was obtained, which enabling the effective synergism of walking and rolling machines. Under optimum condition, it was able to achieve a limit of detection as low as 62.5 fM for kanamycin by the concatenated DNA machines in 80 min. Furthermore, the proposed method exhibited good selectivity and the recoveries results of spiked milk and honey samples were in the range from 95.9% to 106.3%. This concatenated DNA Machine provides a promising strategy for sensitive detection of other food contaminants of interest.

Multiplex Surface-Enhanced Raman Scattering: An Emerging Tool for Multicomponent Detection of Food Contaminants.

For survival and quality of human life, the search for better ways to ensure food safety is constant. However, food contaminants still threaten human health throughout the food chain. In particular, food systems are often polluted with multiple contaminants simultaneously, which can cause synergistic effects and greatly increase food toxicity. Therefore, the establishment of multiple food contaminant detection methods is significant in food safety control. The surface-enhanced Raman scattering (SERS) technique has emerged as a potent candidate for the detection of multicomponents simultaneously. The current review focuses on the SERS-based strategies in multicomponent detection, including the combination of chromatography methods, chemometrics, and microfluidic engineering with the SERS technique. Furthermore, recent applications of SERS in the detection of multiple foodborne bacteria, pesticides, veterinary drugs, food adulterants, mycotoxins and polycyclic aromatic hydrocarbons are summarized. Finally, challenges and future prospects for the SERS-based detection of multiple food contaminants are discussed to provide research orientation for further.

Electrochemical Biosensors as a Novel Platform in the Identification of Listeriosis Infection.

Listeria monocytogenes (L.M.) is a gram-positive bacillus with wide distribution in the environment. This bacterium contaminates water sources and food products and can be transmitted to the human population. The infection caused by L.M. is called listeriosis and is common in pregnant women, immune-deficient patients, and older adults. Based on the released statistics, listeriosis has a high rate of hospitalization and mortality; thus, rapid and timely detection of food contamination and listeriosis cases is necessary. During the last few decades, biosensors have been used for the detection and monitoring of varied bacteria species. These devices are detection platforms with great sensitivity and low detection limits. Among different types of biosensors, electrochemical biosensors have a high capability to circumvent several drawbacks associated with the application of conventional laboratory techniques. In this review article, different electrochemical biosensor types used for the detection of listeriosis were discussed in terms of actuators, bioreceptors, specific working electrodes, and signal amplification. We hope that this review will facilitate researchers to access a complete and comprehensive template for pathogen detection based on the different formats of electrochemical biosensors.

Portable AIE hydrogel sensor for rapid and visual field detection of heavy metal residue in food

Mercury contamination causes a wide range of symptoms in organisms, and affects human brain, kidneys and nervous system in particular. Most food sources high in mercury come from saltwater species like fish and other sea animals. Recently, fluorescent biofilm, electrostatic spinning film, and hydrogel were used for the potable detection of mercury. However, the photostability of the fluorescent probe in the film and the challenge of solid food sample analysis are the main issues to be addressed. In this work, sodium alginate hydrogel (SA) was used for developing a hydrogel sensor in combination with the phenanthroline modified-tetraphenylethylene (TPE) derivatives (DTPEP). Based on its aggregation-induced emission (AIE) characteristic and high specificity to mercury, the AIE hydrogel mercury sensor was coated on different carriers, such as gloves, sticky notes, etc., as flexible sensors for portable and rapid field testing of mercury contamination. The visualization results were analyzed using the greyscale-based Android software “Detect” to Quantification of Hg2+. The detection limit could be as low as 0.06 μM with the detection time within 15 min. The gray value was linearly related to the concentration of Hg2+, ranging from (0–2 μM). The flexible Visual and rapid sensing systems have not only great potential applications in the detection of mercury in food samples but are also suitable for the detection of environmental and food contaminants.

Metal-organic frameworks for food contaminant adsorption and detection.

Metal-organic framework materials (MOFs) have been widely used in food contamination adsorption and detection due to their large specific surface area, specific pore structure and flexible post-modification. MOFs with specific pore size can be targeted for selective adsorption of some contaminants and can be used as pretreatment and pre-concentration steps to purify samples and enrich target analytes for food contamination detection to improve the detection efficiency. In addition, MOFs, as a new functional material, play an important role in developing new rapid detection methods that are simple, portable, inexpensive and with high sensitivity and accuracy. The aim of this paper is to summarize the latest and insightful research results on MOFs for the adsorption and detection of food contaminants. By summarizing Zn-based, Cu-based and Zr-based MOFs with low cost, easily available raw materials and convenient synthesis conditions, we describe their principles and discuss their applications in chemical and biological contaminant adsorption and sensing detection in terms of stability, adsorption capacity and sensitivity. Finally, we present the limitations and challenges of MOFs in food detection, hoping to provide some ideas for future development.

Surface plasmonic biosensors: principles, designs and applications.

Recently, surface plasmon resonance (SPR) biosensors have been widely used in environmental monitoring, food contamination detection and diagnosing medical conditions due to their superior sensitivity, label-free detection and rapid analysis speed. This paper briefly elaborates on the development history of SPR technology and introduces SPR signal sensing principles. A summary of recent applications of SPR sensors in different fields is highlighted, including their figures of merit and limitations. Finally, the personal perspectives and future development trends about sensor preparation and design are discussed in detail, which may be critical for improving the performance of SPR sensors.

Raman spectroscopy: Principles and recent applications in food safety.

Food contaminant is a significant issue because of the adverse effects on human health and economy. Traditional detection methods such as liquid chromatography-mass spectroscopy for detecting food contaminants are expensive and time-consuming, and require highly-trained personnel and complicated sample pretreatment. Raman spectroscopy is an advanced analytical technique in a manner of non-destructive, rapid, cost-effective, and ultrasensitive sensing various hazards in agri-foods. In this chapter, we summarized the principle of Raman spectroscopy and surface enhanced Raman spectroscopy, the methods to process Raman spectra, the recent applications of Raman/SERS (surface-enhanced Raman spectroscopy) in detecting chemical contaminants (e.g., pesticides, antibiotics, mycotoxins, heavy metals, and food adulterants) and microbiological hazards (e.g., Salmonella, Campylobacter, Shiga toxigenic E. coli, Listeria, and Staphylococcus aureus) in foods.

High-performance homogeneous carboxymethylcellulose-stabilized Au@Ag NRs-CMC surface-enhanced Raman scattering chip for thiram detection in fruits

Cellulose material holds considerable promise for effective surface-enhanced Raman scattering (SERS) substrate construction due to its extensive availability, chemically modifying capacity, ease of manufacture, high flexibility and low optical activity. A large-area, high-sensitivity, stable and uniform Au@Ag nanorods (NRs)-CMC substrate was successfully developed via electrostatic repulsion by using negatively-charged core–shell Au@Ag NRs as SERS active plasmonic nanomaterial, combined with negatively-charged carboxymethylcellulose (CMC) hydrogel for nanoparticles stabilization, homodisperse and protection. The obtained Au@Ag NRs-CMC substrate showed excellent sensitivity for the detection of thiram residues in fruits containing low and abundant pigment interferents, such as apples and blueberries, with detection limits of 58 and 78 ppb, respectively. Additionally, it retained more than 80% SERS performance after storage for 9 months under ambient conditions, demonstrating its great potential in facilitating the commercialization of cellulose-based SERS technology for cost-effective detection of food contaminants with advantages of facile preparation procedure, uniformity, reproducibility and long-term stability.

Accelerated and signal amplified nanozyme-based lateral flow assay of acetamiprid based on bivalent triple helix aptamer

The lateral flow assay (LFA) has received extensive attention and been widely used in various targets. However, the development of aptamer based LFA (Apt-LFA) is still far behind, especially for small molecule targets detection. The shortcoming of long response time severely hindered the Apt-LFA strip application in on-site detection of small molecules contaminants in environment and foods. Herein, we introduce bivalent triple helix aptamer (BTHA) and nanozyme yielding an accelerated and signal amplified LFA for acetamiprid detection. We obtained a BTHA with two 10 nt arms, which could shorten the response time between the aptamer and acetamiprid by 6 times, thus dramatically accelerating the detection of acetamiprid. Moreover, we integrate Au@Pt nanozyme to further amplify the detection signal by catalyzing the color development of substrate. In conjunction with smartphone-based analytical device, the Apt-LFA strip enabled the on-site quantitative detection of acetamiprid residue. It is believed that our strategy will facilitate the development of Apt-LFA against small molecule contaminants.

Paper-Based Electrochemical Biosensors for Food Safety Analysis

Nowadays, foodborne pathogens and other food contaminants are among the major contributors to human illnesses and even deaths worldwide. There is a growing need for improvements in food safety globally. However, it is a challenge to detect and identify these harmful analytes in a rapid, sensitive, portable, and user-friendly manner. Recently, researchers have paid attention to the development of paper-based electrochemical biosensors due to their features and promising potential for food safety analysis. The use of paper in electrochemical biosensors offers several advantages such as device miniaturization, low sample consumption, inexpensive mass production, capillary force-driven fluid flow, and capability to store reagents within the pores of the paper substrate. Various paper-based electrochemical biosensors have been developed to enable the detection of foodborne pathogens and other contaminants that pose health hazards to humans. In this review, we discussed several aspects of the biosensors including different device designs (e.g., 2D and 3D devices), fabrication techniques, and electrode modification approaches that are often optimized to generate measurable signals for sensitive detection of analytes. The utilization of different nanomaterials for the modification of electrode surface to improve the detection of analytes via enzyme-, antigen/antibody-, DNA-, aptamer-, and cell-based bioassays is also described. Next, we discussed the current applications of the sensors to detect food contaminants such as foodborne pathogens, pesticides, veterinary drug residues, allergens, and heavy metals. Most of the electrochemical paper analytical devices (e-PADs) reviewed are small and portable, and therefore are suitable for field applications. Lastly, e-PADs are an excellent platform for food safety analysis owing to their user-friendliness, low cost, sensitivity, and a high potential for customization to meet certain analytical needs.

Bifunctional magnetic ZnCdSe/ZnS quantum dots nanocomposite-based lateral flow immunoassay for ultrasensitive detection of streptomycin and dihydrostreptomycin in milk, muscle, liver, kidney, and honey

In this study, bifunctional magnetic ZnCdSe/ZnS quantum dots nanocomposite (MQNs) were synthesized, and firstly used to develop a lateral flow immunoassay (LFIA) for streptomycin (STR) and dihydrostreptomycin (DHSTR) detection in milk, muscle, liver, kidney, and honey simultaneously. The fluorescence signal of MQNs was 9-fold stronger than that of the original quantum dots. The detection limits of the established MQNs-LFIA for STR and DHSTR in five samples were 0.08–1.78 μg/kg, the quantitation limits were 0.26–5.87 μg/kg, the recoveries were between 85.0% and 120.0%, and the coefficient of variations were between 0.8% and 19.3%, respectively. The sensitivity was up to 42-fold more sensitive than the reported LFIAs. The single blind test results of 25 samples were consistent with that of the confirmation method (R2 ≥ 0.99). Besides, a portable reader was self-developed and used for rapid quantification. Our study demonstrated MQNs as a promising signal-amplifying tag can be used for ultrasensitive detection of chemical contaminants in foods.

Single particle detection based colorimetric melamine assay with MnO2-modified gold nanoparticles

In this work, we demonstrate a simple and label-free single particle detection (SPD) method for the quantification of melamine (Mel) based MnO2-modified gold nanoparticles (Au@MnO2 NPs). Without Mel, MnO2 shell of Au@MnO2 NPs are able to be directly decomposed by gallic acid. In the existence of Mel, the decomposition process is restrained due to the strong hydrogen bonding between Mel and gallic acid. The selective etching of MnO2 shell on AuNPs surface results in evident color change from single Au@MnO2 NPs. Through quantitatively enumerating the number of color coded particles, trace amounts of Mel can be accurately detected. A linear range from 0.02 to 1 μM (R2 = 0.98) and a limit of detection of 16.7 nM are acquired. In milk sample, satisfactory recovery was acquired. Therefore, the SPD method is expected to be used for the detection of various chemical contaminants in food.

Simultaneous heptamerization of nanobody and alkaline phosphatase by self-assembly and its application for ultrasensitive immunodetection of small molecular contaminants in agro-products

Antibody affinity and enzyme loads are two critical factors in determining the sensitivity of enzyme-linked immunosorbent assay for small molecular contaminants in food. Multimerization is considered an effective strategy to improve antibody affinity and enzyme loads. Herein, we selected ochratoxin A (OTA) as the model antigen and constructed a nanobody-alkaline phosphatase (Nb-ALP) heptamer fusion for OTA, where the Nb and ALP were simultaneously heptamerized via the self-associating peptide from the α-chains of C4 binding protein (C4bpα). The heptamer was used to develop an enhanced colorimetric enzyme immunoassay for OTA. Under the optimal experimental parameters, the proposed method has a half maximal inhibitory concentration of 0.081 ng/mL for OTA, which is 12.5-fold lower than the Nb-ALP-based method. Negligible cross-reaction was observed with OTA analogs and other common cereal mycotoxins. Moreover, good recovery rates and repeatability were obtained in the spiked cereal samples. The developed method was then applied to the analysis of OTA in real agro-products, and the results correlated well with that of the LC-MS/MS method. Overall, this work demonstrated that the simultaneous heptamerization of nanobody and alkaline phosphatase by self-assembly is an effective strategy for improving antibody affinity and enzyme loads. It also showed the great potential of Nb–C4bpα-ALP heptamer as a robust dual-functional probe for sensitive, selective, and rapid detection of mycotoxin and other small molecular contaminants in food. • Dual-functional nanobody-alkaline phosphatase heptamer (Nb–C4bpα-ALP) for OTA. • Simultaneous heptamerization of Nb and ALP by the self-assembly strategy. • Nb–C4bpα-ALP shows better binding affinity and enzyme activity than Nb-ALP. • Nb–C4bpα-ALP-based enzyme immunoassay for small molecules was first reported. • The developed method has an IC 50 of 0.081 ng/mL with the assay time of 20 min.

Simultaneous Multiplexed Quantification of Banned Sudan Dyes Using Surface Enhanced Raman Scattering and Chemometrics.

Azo compounds such as the Sudan dyes I–IV are frequently used illegally as colorants and added to a wide range of foods. These compounds have been linked to a number of food safety hazards. Several methods have been proposed to detect food contamination by azo compounds and most of these are laboratory based; however, the development of reliable and portable methods for the detection and quantification of food contaminated by these chemicals in low concentration is still needed due to their potentially carcinogenic properties. In this study, we investigated the ability of surface enhanced Raman scattering (SERS) combined with chemometrics to quantify Sudan I–IV dyes. SERS spectra were acquired using a portable Raman device and gold nanoparticles were employed as the SERS substrate. As these dyes are hydrophobic, they were first dissolved in water: acetonitrile (1:10, v/v) as single Sudan dyes (I–IV) at varying concentrations. SERS was performed at 785 nm and the spectra were analyzed by using partial least squares regression (PLS-R) with double cross-validations. The coefficient of determination (Q2) were 0.9286, 0.9206, 0.8676 and 0.9705 for Sudan I to IV, respectively; the corresponding limits of detection (LOD) for these dyes were estimated to be 6.27 × 10−6, 5.35 × 10−5, 9.40 × 10−6 and 1.84 × 10−6 M. Next, quadruplex mixtures were made containing all four Sudan dyes. As the number of possible combinations needed to cover the full concentration range at 5% intervals would have meant collecting SERS spectra from 194,481 samples (214 combinations) we used a sustainable solution based on Latin hypercubic sampling and reduced the number of mixtures to be analyzed to just 90. After collecting SERS spectra from these mixture PLS-R models with bootstrapping validations were employed. The results were slightly worse in which the Q2 for Sudan I to IV were 0.8593, 0.7255, 0.5207 and 0.5940 when PLS1 models (i.e., one model for one dye) was employed and they changed to 0.8329, 0.7288, 0.5032 and 0.5459 when PLS2 models were employed (i.e., four dyes were modelled simultaneously). These results showed the potential of SERS to be used as a high-throughput, low-cost, and reliable methods for detecting and quantifying multiple Sudan dyes in low concentration from illegally adulterated samples.

Facile Fabrication of Highly Quantum Dot/AuNP-Loaded Tags for a Dual-Modal Colorimetric/Reversed Ratiometric Fluorescence Immunochromatographic Assay.

Developing an easily-prepared, sensitive, and accurate point-of-need immunochromatographic assay (ICA) is significant in food safety screening, clinical diagnosis, and environmental monitoring. However, the current single-modal ICAs are limited in certain instinct drawbacks that restrict analytical performances. Herein, we introduce an ultrasensitive dual-modal colorimetric/reversed ratiometric fluorescence ICA based on facilely prepared immunoprobes with a high loading capacity of red quantum dots and AuNPs. By smartly integrating these red-colored/fluorescent signal probes with an immobilized green quantum dot antigen on the test lines, discrete "turn-on" visual inspection and reversed ratiometric quantification via a portable smartphone-based analyzer were accomplished. As an application, this method was employed to detect 11 phosphodiesterase-5 inhibitors in health foods with ultralow detection limits (0.0028-0.045 ng/mL), high repeatability (coefficient of variations of 0.3-1.91%), and reasonable accuracy (recoveries of 86.6-107%). The proposed method was further validated by the authorized liquid chromatography with tandem mass spectrometry method in actual sample detection. This new assay format can be extended to ultrasensitive flexible detection of other food contaminants, environmental pollutants, or tumor biomarkers within minutes, and it just requires simply prepared signal reporters, easy-to-operate procedures, and a low-cost miniaturized analyzer.

Label-Free Fluorescence Sensing Strategy Based on Functional Nucleic Acids via Energy Transfer between DNA-Templated Silver Nanoclusters and Gold Nanorods.

A simple and low-cost fluorescence signal-on sensing strategy has been developed based on functional nucleic acids (FNAs) via energy transfer between DNA-templated silver nanoclusters (DNA-AgNCs) and gold nanorods (GNRs). FNAs were used as highly selective recognition probes, in which an aptamer was used to detect small molecules represented by tetracycline, and DNAzyme was used to detect heavy metal ions represented by Pb2+. The fluorescent DNA-AgNCs were synthesized by the designed oligonucleotide sequences, which consisted of three parts: AgNCs synthesis template C6G5C6, spacer T5, and complementary sequences of the aptamer or enzyme strand. The difference in electrostatic interactions between ss/dsDNA and positively charged GNRs leads to energy transfer with different efficiencies. The analytes represented by tetracycline and Pb2+ can destroy the dsDNA structure and reduce the energy-transfer efficiency between DNA-AgNCs and GNRs, thus achieving fluorescence recovery and a signal-on analytical strategy. This strategy has excellent specificity and sensitivity with limit of detections of 4.411 nM for tetracycline and 1.416 nM for Pb2+ and has been successfully applied to detect tetracycline in milk and Pb2+ in river water. Using DNA-AgNCs formed in situ as signal probes, this strategy does not require labels or modifications and can be completed without complex analytical instruments. Moreover, this strategy can be extended to detect other targets by replacing FNA sequences. Therefore, it has promising prospects in the sensitive, simple, and rapid detection of contaminants in food and environment samples.

Comparing AutoEncoder Variants for Real-Time Denoising of Hyperspectral X-Ray

Hyperspectral X-ray analysis is used in many industrial pipelines, from quality control to detection of low-density contaminants in food. Unfortunately, the signal acquired by X-ray sensors is often affected by a great amount of noise. This hinders the performance of most of the applications building on top of these acquisitions (e.g., detection of food contaminants). Therefore, a good denoising pipeline is necessary. This article proposes a comparison between three different AutoEncoder variants: the Variational AutoEncoder, the Augmented AutoEncoder, and a plain vanilla AutoEncoder. All the networks are trained in an unsupervised fashion to denoise a given noisy spectrum. Focusing on the specific application of recognizing possible food contaminants, we force the latent space of the networks to have just two parameters, as suggested by the physical law of Lambert–Beer. We validate our experiments on a synthetic dataset composed of roughly 15 million spectra. Results suggest that the Augmented AutoEncoder is the best network configuration for this task, showing excellent performance without suffering from the nondeterministic behavior of the Variational AutoEncoder.