Rapid and Quantitative Detection of Aflatoxin B1 in Grain by Portable Raman Spectrometer

Nanosilver-mediated enzyme-free electrochemical immunosensor with enhanced stability for aflatoxin B1 detection in food safety

The development and research of electrochemical immunoassays have attracted considerable attention. However, traditional electrochemical immunoassays inevitably require the participation of biological enzymes, which suffer from high cost, poor stability, inconvenient storage and easy inactivation. Herein, we constructed a bio-enzyme-free electrochemical immunoassay system specifically for the detection of aflatoxin B1 (AFB1). This method was based on the traditional antigen-antibody immune recognition system utilizing the nanosilver particles (NSPs) as signal markers to replace conventional natural enzymes. Subsequently, the labeled NSPs were transferred to silver ions in the presence of nitric acid. The concentration of silver ions was determined using anodic stripping voltammetry (ASV), which correlates closely to the concentration of the target. The current intensity measured by the bio-enzyme-free electrochemical sensor exhibited a negative correlation with the concentration of AFB1. Under optimized conditions, the electrochemical sensor was used to detect AFB1 in the dynamic concentration range of 0.01-100 ng mL-1, and the limit of detection was 0.4882 pg mL-1. The spiked recovery range of AFB1 in corn starch was determined to be between 100.98% and 109.42%, while the relative standard deviation (RSD) range was found to be from 0.34% to 3.82%. These results indicate that the electrochemical immunosensor without biological enzyme labeling has reliable accuracy, and the sensor has a broad application prospect in AFB1 detection.

Determination of aflatoxin B1 in wheat using Raman spectroscopy combined with chemometrics

Aflatoxin B1 (AFB1) is carcinogenic and highly susceptible to production in wheat. In this study, the quantitative detection of contaminant AFB1 in wheat was investigated by Raman spectroscopy combined with chemometric method realization. Firstly, Savitzky-Golay smoothing (SG) and baseline calibration methods were used to perform the necessary preprocessing of the collected raw Raman spectra. Then, three variable optimization methods, i.e., competitive adaptive reweighted sampling (CARS), iteratively variable subset optimization (IVSO), and bootstrap soft shrinkage (BOSS), were applied to the preprocessed wheat Raman spectra. Finally, partial least squares regression (PLSR) models were developed to determine AFB1 in wheat samples. The results showed that all three variable optimization algorithms significantly improved the predictive performance of the models. The BOSS-PLSR model has strong generalization performance and robustness. Its prediction coefficient of determination (RP2) was 0.9927, the root mean square error of prediction (RMSEP) was 2.4260 μg/kg, and the relative prediction deviation (RPD) was 11.5250, respectively. In conclusion, the combination of Raman spectroscopy and chemometrics can realize the rapid quantitative detection of AFB1 in wheat.

Raman Hyperspectral Imaging as a Potential Tool for Rapid and Nondestructive Identification of Aflatoxin Contamination in Corn Kernels

The potential of Raman hyperspectral imaging with a 785 nm excitation line laser was examined for the detection of aflatoxin contamination in corn kernels. Nine-hundred kernels were artificially inoculated in the laboratory, with 300 kernels each inoculated with AF13 (aflatoxigenic) fungus, AF36 (nonaflatoxigenic) fungus, and sterile distilled water (control). One-hundred kernels from each treatment were subsequently incubated for 3, 5, and 8 days. The mean spectra of single kernels were extracted from the endosperm side and the embryo area of the germ side, and local Raman peaks were identified based upon the calculated reference spectra of aflatoxin-negative and -positive categories separately. The principal component analysis-linear discriminant analysis models were established using different types of variable inputs including original full spectra, preprocessed full spectra, and identified local peaks over kernel endosperm-side, germ-side, and both sides. The results of the established discriminant models showed that the germ-side spectra performed better than the endosperm-side spectra. Based upon the 20 ppb-threshold, the best mean prediction accuracy of 82.6% was achieved for the aflatoxin-negative category using the original spectra in the combined form of both kernel sides, and the best mean prediction accuracy of 86.7% was obtained for the -positive category using the preprocessed germ-side spectra. Based upon the 100 ppb-threshold, the best mean prediction accuracies of 85.0% and 89.6% were achieved for the aflatoxin-negative and -positive categories separately, using the same type of variable inputs for the 20 ppb-threshold. In terms of overall prediction accuracy, the models established upon the original spectra in the combined form of both kernel sides achieved the best predictive performance, regardless of the threshold. The mean overall prediction accuracies of 81.8% and 84.5% were achieved with the 20 ppb- and 100 ppb-thresholds, respectively.

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.

Density Functional Theory Study on the Interaction between Aflatoxin B1/M1 and Gold Substrate

Aflatoxin M1 (AFM1) and its precursor, Aflatoxin B1 (AFB1), are highly pathogenic and mutagenic substances, making the detection and sensing of AFB1/M1 a long-standing focus of researchers. Among various detection techniques, surface-enhanced Raman spectroscopy (SERS) is considered an ideal method for AFB1/M1 detection due to its ability not only to enhance characteristic frequencies but also to detect shifts in these frequencies with high repeatability. Therefore, we employed density functional theory in conjunction with surface-enhanced Raman spectroscopy to investigate the interaction between AFB1/M1 and a Au substrate in the context of the SERS effect for the first time. To predict the potential binding sites of AFB1/M1 and Au within the SERS effect, we performed calculations on the molecular electrostatic potential of AFB1/M1. Considering the crucial role of the binding energy in molecular docking studies, we computed the binding energy between two molecules interacting with Au at different binding sites. The molecular frontier orbitals and related chemical parameters of AFB1/M1 and "molecular-Au" complexes were computed to elucidate the alterations in AFB1/M1 molecules under the SERS effect. Subsequently, the theoretical Raman spectra of AFB1/M1 and the complexes were compared and analyzed, enabling determination of the adsorption conformation of AFB1/M1 on the gold surface based on SERS surface selection rules. These findings not only provide a deeper understanding of the interaction mechanism between molecules and substrates in the SERS effect but also offer theoretical support for developing novel aflatoxin SERS sensors.

Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman)

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.

Advances, limitations, and considerations on the use of vibrational spectroscopy towards the development of management decision tools in food safety

Food safety and food security are two of the main concerns for the modern food manufacturing industry. Disruptions in the food supply and value chains have created the need to develop agile screening tools that will allow the detection of food pathogens, spoilage microorganisms, microbial contaminants, toxins, herbicides, and pesticides in agricultural commodities, natural products, and food ingredients. Most of the current routine analytical methods used to detect and identify microorganisms, herbicides, and pesticides in food ingredients and products are based on the use of reliable and robust immunological, microbiological, and biochemical techniques (e.g. antigen-antibody interactions, extraction and analysis of DNA) and chemical methods (e.g. chromatography). However, the food manufacturing industries are demanding agile and affordable analytical methods. The objective of this review is to highlight the advantages and limitations of the use of vibrational spectroscopy combined with chemometrics as proxy to evaluate and quantify herbicides, pesticides, and toxins in foods.

The potential and applicability of infrared spectroscopic methods for the rapid screening and routine analysis of mycotoxins in food crops

Infrared (IR) spectroscopy is increasingly being used to analyze food crops for quality and safety purposes in a rapid, nondestructive, and eco-friendly manner. The lack of sensitivity and the overlapping absorption characteristics of major sample matrix components, however, often prevent the direct determination of food contaminants at trace levels. By measuring fungal-induced matrix changes with near IR and mid IR spectroscopy as well as hyperspectral imaging, the indirect determination of mycotoxins in food crops has been realized. Recent studies underline that such IR spectroscopic platforms have great potential for the rapid analysis of mycotoxins along the food and feed supply chain. However, there are no published reports on the validation of IR methods according to official regulations, and those publications that demonstrate their applicability in a routine analytical set-up are scarce. Therefore, the purpose of this review is to discuss the current state-of-the-art and the potential of IR spectroscopic methods for the rapid determination of mycotoxins in food crops. The study critically reflects on the applicability and limitations of IR spectroscopy in routine analysis and provides guidance to non-spectroscopists from the food and feed sector considering implementation of IR spectroscopy for rapid mycotoxin screening. Finally, an outlook on trends, possible fields of applications, and different ways of implementation in the food and feed safety area are discussed.

Surface Plasmon Resonance (SPR) biosensor for detection of mycotoxins: A review

Mycotoxin is one of the most important natural pollutants, which poses a global threat to food safety. However, the pollution of mold in food production is inevitable. The detection technology of mycotoxins in food production is an important means to prevent the damage of mycotoxins, so rapid detection and screening to avoid pollution diffusion is essential. The focus of this review is to update the literature on the detection of mycotoxins by surface plasmon resonance (SPR) technology, rather than just traditional chromatographic methods. As a relatively novel and simple analytical method, SPR has been proved to be fast, sensitive and label-free, and has been widely used in real-time qualitative and quantitative analysis of various pollutants. This paper aims to give a broad overview of the sensors for detection and analysis of several common mycotoxins.

Aflatoxins in Cereals and Cereal-Based Products: Occurrence, Toxicity, Impact on Human Health, and Their Detoxification and Management Strategies

Cereals and cereal-based products are primary sources of nutrition across the world. However, contamination of these foods with aflatoxins (AFs), secondary metabolites produced by several fungal species, has raised serious concerns. AF generation in innate substrates is influenced by several parameters, including the substrate type, fungus species, moisture content, minerals, humidity, temperature, and physical injury to the kernels. Consumption of AF-contaminated cereals and cereal-based products can lead to both acute and chronic health issues related to physical and mental maturity, reproduction, and the nervous system. Therefore, the precise detection methods, detoxification, and management strategies of AFs in cereal and cereal-based products are crucial for food safety as well as consumer health. Hence, this review provides a brief overview of the occurrence, chemical characteristics, biosynthetic processes, health hazards, and detection techniques of AFs, along with a focus on detoxification and management strategies that could be implemented for food safety and security.

Optofluidic Platform for Rapid On-Chip Analysis of Total Phosphorus in Surface Water Using Absorption Spectrometry

Optofluidic devices are of high interest for online monitoring and analyzing biochemical targets in water by integrating the complex on-chip pretreatment of target analytes and spectral analysis. Compared with the traditional bulk equipment, versatile optical detection and biochemical analysis are more easily integrated on an optofluidic chip, which promotes the development of on-chip real-time rapid detection and monitoring. Here, we report an optofluidic platform for online monitoring total phosphorous in water by absorption spectrometry, which naturally combines the merits of both the photo-Fenton effect and microfluidics to realize the rapid on-chip digestion of phosphate at room temperature and normal pressure. The functional cells for chromogenic reaction and optical absorption detection are, respectively, fabricated on the platform to analyze the content of total phosphorus in surface water. In the experiment, the on-chip digestion time of phosphate is dramatically declined to 8.6 sec, and thus, the detection time is greatly shortened to a few minutes. The detection range of total phosphorus is demonstrated as 0.005-1.00 mg L^-1, which satisfies the detection requirements of most environmental water samples. Its availability for measuring the total phosphorous in real water samples is also verified. Predictably, this platform is adapted to on-chip analysis of many other biochemical targets in water.

Detection of Mycotoxins in Food Using Surface-Enhanced Raman Spectroscopy: A Review

Mycotoxins are toxic metabolites produced by fungi that contaminate many important crops worldwide. Humans are commonly exposed to mycotoxins through the consumption of contaminated food products. Mycotoxin contamination is unpredictable and unavoidable; it occurs at any point in the food production system under favorable conditions, and they cannot be destroyed by common heat treatments, because of their high thermal stability. Early and fast detection plays an essential role in this unique challenge to monitor the presence of these compounds in the food chain. Surface-enhanced Raman spectroscopy (SERS) is an advanced spectroscopic technique that integrates Raman spectroscopic molecular fingerprinting and enhanced sensitivity based on nanotechnology to meet the requirement of sensitivity and selectivity, but that can also be performed in a cost-effective and straightforward manner. This Review focuses on the SERS methodologies applied to date for qualitative and quantitative analysis of mycotoxins based on a variety of SERS substrates, as well as our perspectives on current limitations and future trends for applying this technique to mycotoxin analyses.