Gold@silver nanodumbbell based inter-nanogap aptasensor for the surface enhanced Raman spectroscopy determination of ochratoxin A

A Sensitive SERS Sensor Combined with Intelligent Variable Selection Models for Detecting Chlorpyrifos Residue in Tea

Chlorpyrifos is one of the most widely used broad-spectrum insecticides in agriculture. Given its potential toxicity and residue in food (e.g., tea), establishing a rapid and reliable method for the determination of chlorpyrifos residue is crucial. In this study, a strategy combining surface-enhanced Raman spectroscopy (SERS) and intelligent variable selection models for detecting chlorpyrifos residue in tea was established. First, gold nanostars were fabricated as a SERS sensor for measuring the SERS spectra. Second, the raw SERS spectra were preprocessed to facilitate the quantitative analysis. Third, a partial least squares model and four outstanding intelligent variable selection models, Monte Carlo-based uninformative variable elimination, competitive adaptive reweighted sampling, iteratively retaining informative variables, and variable iterative space shrinkage approach, were developed for detecting chlorpyrifos residue in a comparative study. The repeatability and reproducibility tests demonstrated the excellent stability of the proposed strategy. Furthermore, the sensitivity of the proposed strategy was assessed by estimating limit of detection values of the various models. Finally, two-tailed paired t-tests confirmed that the accuracy of the proposed strategy was equivalent to that of gas chromatography-mass spectrometry. Hence, the proposed method provides a promising strategy for detecting chlorpyrifos residue in tea.

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.

Improvement of the sensitivity of lateral flow systems for detecting mycotoxins: Up-to-date strategies and future perspectives

Mycotoxins are dangerous human and animal health-threatening secondary fungal metabolites that can be found in various food and agricultural products. Several countries have established regulations to restrict their presence in food and agricultural products destined for human and animal consumption. Consequently, the need to develop highly sensitive and smart detection systems was recognized worldwide. Lateral flow assay possesses the advantages of easy operation, rapidity, stability, accuracy, and specificity, and it plays an important role in the detection of mycotoxins. Nevertheless, strategies to comprehensively improve the sensitivity of lateral flow assay to mycotoxins in food have rarely been highlighted and discussed. In this article, a comprehensive overview was presented on the application of lateral flow assay in mycotoxin detection in food samples by highlighting the principle of lateral flow assay, presenting a detailed discussion on various analytical performance-improvement strategies, such as the development of high-affinity recognition reagents, immunogen immobilization methods, and signal amplification. Additionally, a detailed discussion on the various signal analyzers and interpretation approaches was provided. Finally, current hurdles and future perspectives on the application of lateral flow assay in the detection of mycotoxins were discussed.

Is chemical analysis suitable for detecting mycotoxins in agricultural commodities and foodstuffs?

The assessment of the risks of mycotoxins to humans through consuming contaminated foods resulted in specific legislation that evaluates the presence, quantities, and type of mycotoxins in agricultural commodities and foodstuffs. Thus, to ensure compliance with legislation, food safety and consumer health, the development of suitable analytical procedures for identifying and quantifying mycotoxins in the free or modified form, in low-concentration and in complex samples is necessary. This review reports the application of the modern chemical methods of analysis employed in mycotoxin detection in agricultural commodities and foodstuffs. It is reported extraction methods with reasonable accuracy and those present characteristics according to guidelines of Green Analytical Chemistry. Recent trends in mycotoxins detection using analytical techniques are presented and discussed, evaluating the robustness, precision, accuracy, sensitivity, and selectivity in the detection of different classes of mycotoxins. Sensitivity coming from modern chromatographic techniques allows the detection of very low concentrations of mycotoxins in complex samples. However, it is essential the development of more green, fast and more suitable accuracy extraction methods for mycotoxins, which agricultural commodities producers could use. Despite the high number of research reporting the use of chemically modified voltammetric sensors, mycotoxins detection still has limitations due to the low selectivity from similar chemical structures of mycotoxins. Furthermore, spectroscopic techniques are rarely employed due to the limited number of reference standards for calibration procedures.

Current State of Sensors and Sensing Systems Utilized in Beer Analysis

Beer is one of the most consumed beverages in the world. Advances in instrumental techniques have allowed the analysis and characterization of a large number of beers. However, review studies that outline the methodologies used in beer characterization are scarce. Herein, a systematic review investigating the molecular targets and sensometric techniques in beer characterization was performed following the PRISMA protocol. The study reviewed 270 articles related to beer analysis in order to provide a comprehensive summary of the recent advances in beer analysis, including methods using sensors and sensing systems. The results revealed the use of various techniques that include several technologies, such as nanotechnology and electronics, often combined with scientific data analysis tools. To our knowledge, this study is the first of its kind and provides the reader with a faithful overview of what has been done in the sensor field regarding beer characterization.

Dual-signal output fluorescent aptasensor based on DNA programmability and gold nanoflowers for multiple mycotoxins detection

Herein, a dual-signal output fluorescent aptamer sensor was constructed for the simultaneous detection of aflatoxin B₁ (AFB₁) and ochratoxin A (OTA) using the specific recognition ability of aptamers and the programmability of DNA. A functional capture probe (cDNA) was designed with the black hole quenching motif BHQ1 labeled at the 5' end and biotin (bio) labeled at the 3' end. The fluorescent dye Cy3-labeled aflatoxin B1 aptamer (AFB₁-Apt) and the carboxyfluorescein FAM-labeled ochratoxin A aptamer (OTA-Apt) were used as two fluorescent probes. The cDNA is anchored to the quenching material gold nanoflowers (AuNFs) by the action of streptavidin (SA) and biotin. Its ends can be complementarily paired with two fluorescent probe bases to form a double-stranded structure. The fluorescence of Cy3 was quenched by AuNFs, and the fluorescence of FAM was quenched by BHQ1 through the fluorescence energy resonance transfer (FRET) effect, forming a fluorescence quenching system. Due to the high affinity of the target and the aptamer, the structure of the aptamer probe changes and detaches from the sensor when AFB₁ and OTA are present, resulting in enhanced fluorescence. Under optimal conditions, the linear range of AFB₁ was 0.1-100 ng/mL (R² = 0.996), the limit of detection (LOD) was as low as 0.014 ng/mL, and the limit of quantification (LOQ) was 0.046 ng/mL. The linear range of OTA was 0.1-100 ng/mL (R² = 0.995), the limit of detection (LOD) was as low as 0.027 ng/mL, and the limit of quantification (LOQ) was 0.089 ng/mL. The sensor had high accuracy in detecting both AFB₁ and OTA in real sample analysis. The results of the t test show that there is no significant difference between the results of this study and the high-performance liquid phase (HPLC) method, indicating that the prepared sensor can be used as a potential platform for multiple mycotoxins detection.

Progress on aptamer-based SERS sensors for food safety and quality assessment: methodology, current applications and future trends

It is well known that food safety has aroused extensive attentions from governments to researchers and to food industries. As a versatile technology based on molecular interactions, aptamer sensors which could specifically identify a wide range of food contaminants have been extensively studied in recent years. Surface-enhanced Raman spectroscopy integrated aptamer combines the advantages of both technologies, not only in the ability to specifically identify a wide range of food contaminants, but also in the ultra-high sensitivity, simplicity, portable and speed. To provide beneficial insights into the evaluation techniques in the field of food safety, we offer a comprehensive review on the design strategies for aptamer-SERS sensors in different scenarios, including non-nucleic acid amplification methods ("on/off" mode, sandwich mode, competition model and catalytic model) and nucleic acid amplification methods (hybridization chain reaction, rolling circle amplification, catalytic hairpin assembly). Meanwhile, a special attention is paid to the application of aptamer-SERS sensors in biological (foodborne pathogenic, bacteria and mycotoxins) and chemical contamination (drug residues, metal ions, and food additives) of food matrix. Finally, the challenges and prospects of developing reliable aptamer-SERS sensors for food safety were discussed, which are expected to offer a strong guidance for further development and extended applications.

Determination of aflatoxin B1 (AFB1) in maize based on a portable Raman spectroscopy system and multivariate analysis

Aflatoxin B₁ (AFB₁) is the most widely distributed, most toxic, and most harmful, and it is widely present in moldy grains. This study proposes a new method for quantitative and rapid determination of the AFB₁ content in maize based on Raman spectroscopy. The Raman spectra of maize samples with different mildew degrees were collected by a portable laser Raman spectroscopy system. Three different spectral selection methods, which were bootstrapping soft shrinkage (BOSS), variable combination population analysis (VCPA) and competitive adaptive reweighted sampling (CARS), were applied to optimize the characteristic wavelength variables of the pretreated Raman spectra. The support vector machine (SVM) detection models based on different optimized characteristic wavelength variables were established, and the results of each detection model were compared. The results obtained showed that the performance of the SVM models established by optimized features was significantly better than the performance of the SVM model built by full-spectrum data. Among them, the SVM model based on the characteristic wavelength variables optimized by the CARS method had the best performance, and its root mean square error of prediction (RMSEP) was 3.5377 μg∙kg^-1, the determination coefficient of prediction (R_P²) was 0.9715, and the relative prediction deviation (RPD) was 5.8258. The overall results reveal that the rapid quantitative detection of the AFB₁ in maize by Raman spectroscopy has a promising application prospect. In addition, the implementation of the characteristic wavelength optimization of Raman spectra in the model calibration process can effectively improve the detection accuracy of chemometric models.

High Precisive Prediction of Aflatoxin B1 in Pressing Peanut Oil Using Raman Spectra Combined with Multivariate Data Analysis

This study proposes a label-free rapid detection method for aflatoxin B₁ (AFB₁) in pressing peanut oil based on Raman spectroscopy technology combined with appropriate chemometric methods. A DXR laser Raman spectrometer was used to acquire the Raman spectra of the pressed peanut oil samples, and the obtained spectra were preprocessed by wavelet transform (WT) combined with adaptive iteratively reweighted penalized least squares (airPLS). The competitive adaptive reweighted sampling (CARS) method was used to optimize the characteristic bands of the Raman spectra pretreated by the WT + airPLS, and a partial least squares (PLS) detection model for the AFB₁ content was established based on the features optimized. The results obtained showed that the root mean square error of prediction (RMSEP) and determination coefficient of prediction (RP2) of the optimal CARS-PLS model in the prediction set were 22.6 µg/kg and 0.99, respectively. The results demonstrate that the Raman spectroscopy combined with appropriate chemometrics can be used to quickly detect the safety of edible oil with high precision. The overall results can provide a technical basis and method reference for the design and development of the portable Raman spectroscopy system for the quality and safety detection of edible oil storage, and also provide a green tool for fast on-site analysis for regulatory authorities of edible oil and production enterprises of edible oil.