Dual function of magnetic nanocomposites-based SERS lateral flow strip for simultaneous detection of aflatoxin B1 and zearalenone.

Aflatoxin B1 (AFB1) and zearalenone (ZEN) are two mycotoxins that often co-occur in corn. A surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-LFIA) that can simultaneously detect AFB1 and ZEN in corn samples was developed employing the core-interlayer-satellite magnetic nanocomposites (Fe3O4@PEI/AuMBA@AgMBA) as dual-functional SERS tags. Under the optimal conditions, the detection ranges of AFB1 and ZEN in corn samples were 0.1-10 µg/kg and 4-400 µg/kg, respectively. Moreover, the test results for two mycotoxins in contaminated corn samples employing the suggested SERS-LFIA was in line with those of the HPLC technique. In view of its satisfactory sensitivity, accuracy, precision and short testing time (20 min), the developed system has a promising application prospect in the on-site simultaneous detection of AFB1 and ZEN.

Air and argon cold plasma effects on lipolytic enzymes inactivation, physicochemical properties and volatile profiles of lightly-milled rice.

This study investigated the effectiveness of cold-plasma treatment using air and argon as input gas on deactivation of lipolytic enzymes in lightly-milled-rice (LMR). The results showed no significant inactivation in lipase and lipoxygenase using air-plasma. However, using argon as input gas, the residual activities of lipase and lipoxygenase were reduced to 64.51 % and 29.15 % of initial levels, respectively. Argon plasma treatment resulted in more substantial augmentation in peak and breakdown viscosities of LMR starch, suggesting an enhancement in palatability of cooked LMR with increased stickiness and decreased hardness. In contrast to the decrease in volatile compounds in LMR following argon plasma treatment, the concentrations of several prevalent aroma compounds, including 1-hexanol, 1-hexanal, and 2-pentylfuran, exhibited significant increments, reaching 1489.70 ng/g, 3312.10 ng/g, and 58.80 ng/g, respectively. These findings suggest the potential for enhancing various facets of the commercial qualities of LMR by utilizing different input gases during plasma treatment.

Spoilage Monitoring and Early Warning for Apples in Storage Using Gas Sensors and Chemometrics.

In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing-partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (Rp) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse's sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.

Development of a Sensitive SERS Method for Label-Free Detection of Hexavalent Chromium in Tea Using Carbimazole Redox Reaction.

Tea plants absorb chromium-contaminated soil and water and accumulate in tea leaves. Hexavalent chromium (Cr6+) is a very toxic heavy metal; excessive intake of tea containing Cr6+ can cause serious harm to human health. A reliable and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed using Au@Ag nanoparticles as an enhanced substrate for the determination of Cr6+ in tea. The Au@AgNPs coated with carbimazole showed a highly selective reaction to Cr6+ in tea samples through a redox reaction between Cr6+ and carbimazole. The Cr6+ in the contaminated tea sample reacted with methimazole-the hydrolysate of carbimazole-to form disulfide, which led to the decrease in the Raman intensity of the peak at 595 cm-1. The logarithm of the concentration of Cr6+ has a linear relationship with the Raman intensity at the characteristic peak and showed a limit of detection of 0.945 mg/kg for the tea sample. The carbimazole functionalized Au@AgNPs showed high selectivity in analyzing Cr6+ in tea samples, even in the presence of other metal ions. The SERS detection technique established in this study also showed comparable results with the standard ICP-MS method, indicating the applicability of the established technique in practical applications.

Dual-layers Raman reporter-tagged Au@Ag combined with core-satellite assemblies for SERS detection of Zearalenone.

Zearalenone (ZEN) is a prevalent mycotoxin identified in corn. A SERS-based immunosensor by constructing core-satellite assemblies was developed for ZEN detection. ZEN monoclonal antibody modified gold nanostars (AuNSs) were fabricated as the capture probe (core). The Raman signal probes (satellites) utilized ZEN antigen linked to the core-shell structures loaded with two layers of Raman reporter molecules (AuMBA@AgMBANPs). The coupling between AuNSs and AuMBA@AgMBANPs can produce a poweful electromagnetic field, thus considerably amplifying the Raman signal. The detection range of ZEN for corn samples under the optimal conditions was 5 âˆ¼ 400 µg/kg with a LOD of 3 µg/kg, which completely satisfying the requirement of maximum residual level (60 µg/kg). Moreover, the proposed SERS method was consistent with the HPLC-FLD method for the detection of ZEN in naturally contaminated corn samples (90.58% ∼ 105.29%). Conclusively, fabricated immunosensor with exceptional sensitivity and specificity broaden the application of SERS in mycotoxin detection.

Application of colorimetric sensor array coupled with machine-learning approaches for the discrimination of grains based on freshness.

BACKGROUND: Volatile organic compounds (VOCs) in grain fluctuate depending on the degree of grain freshness. A new colorimetric sensor array (CSA) was developed as capture probes for the quantification of VOCs in grains in this work, and it was designed to monitor the variation of grain VOCs. CSA spectral data acquisition using visible-near-infrared spectroscopy and image processing of CSA's image imformation by computer were used comparatively. Then, machine-learning-based models - for example, synergistic interval partial least squares, genetic algorithm, competitive adaptive reweighted sampling (CARS) algorithm, and ant colony optimization (ACO) algorithm - were introduced to optimize variables. Moreover, principal component analysis, and linear discriminant analysis (LDA), and K-nearest neighbors (KNN) were used for the classification. Ultimately, quantitative models for detecting grain freshness are developed using various variable selection strategies. RESULTS: Compared with the pattern recognition results of image processing, visible-near-infrared spectroscopy could better separate the grains with different freshness from principal component analysis, and the prediction set of LDA models could correctly identify 100% of rice, 96.88% of paddy, and 97.9% of soybeans. In addition, compared with CARS and ACO, the LDA model and KNN model based on genetic algorithms show the best prediction performance. The prediction set could correctly identify 100% of rice and paddy samples and 95.83% of soybean samples. CONCLUSION: The method developed could be used for non-destructive detection of grain freshness. © 2023 Society of Chemical Industry.

Research on the correlation between three-dimensional morphology and temperature changes in potato slices during drying.

Drying is an effective method to reduce potato storage loss. However, potatoes have high porosity with high water content. Shrinkage during drying can lead to folding and cracking of the dried product form. Therefore, this study explored the correlation between the 3D morphology and temperature distribution changes of potato slices during drying, with the aim of providing a reference for the detection of quality changes. An online automatic acquisition device to obtain 3D morphology and temperature information was designed and built. Hot air-drying experiments were conducted on the potato slices. 3D morphology images and temperature images of the potato slices were acquired by 3D and temperature sensors, and the two images were registered using the random sample consensus (RANSAC) algorithm. The region of interest of each image was extracted by algorithms such as threshold segmentation, hole filling and morphological erosion, and the 3D morphology information and temperature information were obtained. The mapping, range and average of each acquisition point were calculated for correlation analysis. Spearman's rank correlation coefficients and Maximum Information Coefficient (MIC) values were selected as measures for the correlation study. The results showed that the Spearman's rank correlation coefficients between average height and average temperature were mostly above 0.7 in absolute value, and the MICs were mostly above 0.9. The average values of the 3D information and temperature information exhibited an extremely strong correlation. This paper gives a new approach to investigate the morphological changes in the drying process by quantifying the relationship between 3D morphology and temperature distribution. This can guide the improvement of potato drying and processing methods.

Bisphenol A detection based on nano gold-doped molecular imprinting electrochemical sensor with enhanced sensitivity.

A facile electrochemical sensor based on nano gold-doped molecularly imprinted polymer (MIP) was proposed to realize the selective detection of bisphenol A (BPA) with enhanced sensitivity. Initially, gold-doped MIP (Au@MIP) film was constructed by electropolymerizing p-aminobenzoic acid (PABA) and BPA with in situ gold reduction to distribute gold nanoparticles nearby the imprinted cavities. Subsequently, the template molecules were further extracted from the polymer film, then the MIP could rebind with the template molecules to achieve specific detection of BPA. The nano gold-doped MIP increased the effective surface area and promoted conductivity when BPA was oxidized in the imprinted cavities, which improved the determination sensitivity. Under optimal conditions, the prepared sensor displayed a linear range from 0.5 to 100 µM for BPA detection with a detection limit of 52 nM. The designed sensor was further used to detect BPA in food samples, obtaining satisfactory recoveries from 96.7% to 107.6%.

Three-Dimensional Appearance and Physicochemical Properties of Pleurotus eryngii under Different Drying Methods.

This study investigated the effects of different drying methods on the drying characteristics, three-dimensional (3D) appearance, color, total polysaccharide content (TPC), antioxidant activity, and microstructure of Pleurotus eryngii slices. The drying methods included hot air drying (HAD), infrared drying (ID), and microwave drying (MD). The results showed that the drying method and conditions significantly influenced the drying time, with MD having a significant advantage in reducing the drying time. The 3D appearance of P. eryngii slices was evaluated based on shrinkage and roughness as quantitative indexes, and the best appearance was obtained by hot air drying at 55 and 65 °C. HAD and ID at lower drying temperatures obtained better color, TPC, and antioxidant activity, but MD significantly damaged the color and nutritional quality of P. eryngii. The microstructure of dried P. eryngii slices was observed using scanning electron microscopy, and the results showed that drying methods and conditions had an obvious effect on the microstructure of P. eryngii slices. Scattered mycelia were clearly observed in P. eryngii samples dried by HAD and ID at lower drying temperatures, while high drying temperatures led to the cross-linking and aggregation of mycelia. This study offers scientific and technical support for choosing appropriate drying methods to achieve a desirable appearance and quality of dried P. eryngii.

Custom-Developed Reflection-Transmission Integrated Vision System for Rapid Detection of Huanglongbing Based on the Features of Blotchy Mottled Texture and Starch Accumulation in Leaves.

Huanglongbing (HLB) is a highly contagious and devastating citrus disease that causes huge economic losses to the citrus industry. Because it cannot be cured, timely detection of the HLB infection status of plants and removal of diseased trees are effective ways to reduce losses. However, complex HLB symptoms, such as single HLB-symptomatic or zinc deficiency + HLB-positive, cannot be identified by a single reflection imaging method at present. In this study, a vision system with an integrated reflection-transmission image acquisition module, human-computer interaction module, and power supply module was developed for rapid HLB detection in the field. In reflection imaging mode, 660 nm polarized light was used as the illumination source to enhance the contrast of the HLB symptoms in the images based on the differences in the absorption of narrow-band light by the components within the leaves. In transmission imaging mode, polarization images were obtained in four directions, and the polarization angle images were calculated using the Stokes vector to detect the optical activity of starch. A step-by-step classification model with four steps was used for the identification of six classes of samples (healthy, HLB-symptomatic, zinc deficiency, zinc deficiency + HLB-positive, magnesium deficiency, and boron deficiency). The results showed that the model had an accuracy of 96.92% for the full category of samples and 98.08% for the identification of multiple types of HLB (HLB-symptomatic and zinc deficiency + HLB-positive). In addition, the classification model had good recognition of zinc deficiency and zinc deficiency + HLB-positive samples, at 92.86%.

Detection of wheat toxigenic Aspergillus flavus based on nano-composite colorimetric sensing technology.

Volatile organic compounds (VOCs) are an important indicator for fungal-infected wheat identification. This work proposes a novel approach for toxigenic Aspergillus flavus infected wheat identification through characteristic VOCs analyzed by nano-composite colorimetric sensors. Nanoparticles of poly styrene-co-acrylic acid (PSA), porous silica nanoparticles (PSN), and metal-organic framework (MOF) were combined with boron dipyrromethene (BODIPY) to fabricate nano-composite colorimetric sensors. The combination mechanisms for nanoparticles and the information extracted from nano-colorimetric sensors by digital images were analyzed in the current work. Furthermore, linear discriminant analysis (LDA) and k-nearest neighbor (KNN) were used comparatively to analyze the data from images, and toxigenic Aspergillus flavus infected wheat samples could be 100.00% correctly identified when using the optimal KNN model. This research contributes to the practical analysis of VOCs and the detection of toxigenic Aspergillus flavus infected wheat.

Initial screening of gastric cancer using oral contrast-enhanced trans-abdominal ultrasonography in rural asymptomatic individuals.

BACKGROUND & AIMS: Initial screening for high-risk population of gastric cancer (GC) is needed in rural areas of large-population countries. This study aims to explore the feasibility of applying noninvasive ultrasonography as an initial screening strategy to improve the early diagnosis and prevention of GC. METHODS: Oral contrast-enhanced trans-abdominal ultrasonography (OCTU) was initially applied to screen around 15,000 residents from 24 different rural villages of Changxing Island in Shanghai, China, facilitating the identification of high-risk population for further endoscopy examination. RESULTS: 176 subjects (1.18 %) were initially identified with gastric diseases using OCTU while 14,787 ones (98.93 %) were normal with negative results. 145 out of 176 individuals (82.39 %) took further endoscopy examination, and 16 were diagnosed with GC with biopsy examination, with 9 of them at the early stage. We followed up with the Center for Disease Control and Prevention, and identified another 6 GC cases occurred within one year among OCTU-negative population, serving as an adjustment factor for sensitivity analysis. As a result, with a total of 22 GC cases included in this cohort, the positive predictive rate, the negative predictive value, sensitivity, and specificity were 9.09％, 99.96 %, 75.5 %, and 98.93 %, respectively. CONCLUSIONS: OCTU is feasible, non-invasive, low-cost, and widely acceptable in rural area, thus we proposed that OCTU is practicable to serve as a supplementary screening method to improve the early detection of GC in rural area of China and other developing countries with large population.

Relationship Between Invasive Fungal Infection and Hypostatic Pneumonia: A Prospective Cohort Study.

Background: The short-term mortality of hypostatic pneumonia (HP) is very high, and the treatment outcome is poor. The clinical diagnosis and treatment are primarily focused on bacterial and viral infection, ignoring the role of fungal infection at present. This study aims to validate the relationship between Invasive Fungal Infections (IFI) and HP. Methods: In the cross-sectional study, a total of 11,371 participants have been enrolled. In the prospective cohort study, 4,441 individuals have been included at baseline and followed up from 2015 to 2019 with a total person years of 8,484.65. The standard procedures were used to assess questionnaire investigations, laboratory testing, and anthropometric indicators. For data analysis, logistic regression, restricted cubic spline, log-rank regression, Cox regression, and linear mixed effects model were applied to assess the relationship between IFI and HP risk longitudinally. Results: In the cross-sectional study, elevated ß-D-Glucan (BDG) concentrations are associated with a higher risk of HP prevalence in the total population, men, and women (OR T3 vs . T1 [95% CIs]: 2.12 [1.55, 2.91]; 2.01 [1.35, 2.99]; 2.34 [1.39, 3.94]), which were verified by a dose-effect relationship in the restricted cubic spline model. In the cohort study, Cox and Log-rank regression showed that the elevated BDG concentrations are associated with a significantly higher risk of HP incidence than participants with lower BDG concentrations (HR T3 vs .T1 [95% CIs]: 2.72 [1.36, 5.43], p Log-rank = 0.0086). During 5 years, the globulin (GLB) and C-reactive protein (CRP) were always on the top in the highest category of BDG concentrations. Between low and high BDG concentration, the total trend of GLB concentration was falling and the total trend of CRP concentration was rising with the increase of years (all the p-values < 0.0001). Conclusion: In this study, IFI is associated with a higher risk of HP, with time sequence and related mechanisms requiring further investigation in the future.

Rapid and sensitive detection of zearalenone in corn using SERS-based lateral flow immunosensor.

Zearalenone (ZEN) is a universal mycotoxin contaminant in corn and its products. A surface-enhanced Raman scattering (SERS) based test strip was proposed for the detection of ZEN, which had the advantages of simplicity, rapidity, and high sensitivity. Core-shell Au@AgNPs with embedded reporter molecules (4-MBA) were synthesized as SERS nanoprobe, which exhibited excellent SERS signals and high stability. The detection range of ZEN for corn samples was 10-1000 µg/kg with the limit of detection (LOD) of 3.6 µg/kg, which is far below the recommended tolerable level (60 µg/kg). More importantly, the SERS method was verified by HPLC in the application on corn samples contaminated with ZEN, and the coincidence rates were in the range of 86.06%-111.23%, suggesting a high accuracy of the SERS assay. Therefore, the SERS-based test strip with an analysis time of less than 15 min is a promising tool for accurate and rapid detection of ZEN-field contamination.

Electrochemical Self-Assembled Gold Nanoparticle SERS Substrate Coupled with Diazotization for Sensitive Detection of Nitrite.

The accurate determination of nitrite in food samples is of great significance for ensuring people's health and safety. Herein, a rapid and low-cost detection method was developed for highly sensitive and selective detection of nitrite based on a surface-enhanced Raman scattering (SERS) sensor combined with electrochemical technology and diazo reaction. In this work, a gold nanoparticle (AuNP)/indium tin oxide (ITO) chip as a superior SERS substrate was obtained by electrochemical self-assembled AuNPs on ITO with the advantages of good uniformity, high reproducibility, and long-time stability. The azo compounds generated from the diazotization-coupling reaction between nitrite, 4-aminothiophenol (4-ATP), and N-(1-naphthyl) ethylenediamine dihydrochloride (NED) in acid condition were further assembled on the surface of AuNP/ITO. The detection of nitrite was realized using a portable Raman spectrometer based on the significant SERS enhancement of azo compounds assembled on the AuNP/ITO chip. Many experimental conditions were optimized such as the time of electrochemical self-assembly and the concentration of HAuCl4. Under the optimal conditions, the designed SERS sensor could detect nitride in a large linear range from 1.0 × 10-6 to 1.0 × 10-3 mol L-1 with a low limit of detection of 0.33 µmol L-1. Additionally, nitrite in real samples was further analyzed with a recovery of 95.1-109.7%. Therefore, the proposed SERS method has shown potential application in the detection of nitrite in complex food samples.

Three-dimensional morphological changes of potato slices during the drying process.

Hot air drying is a common method for drying potato slices. In this paper, the three-dimensional (3D) morphological changes incurred during hot air drying of potato slices were investigated. The effect of drying on the thickness and diameter of potato slices was of special interest. The results showed that the potato slices underwent stages of regular warping, collapse, and curling during the drying process. After classifying the numerical variation in characteristics into the standard deviation in mean height (SDMH) and the rate of change in mean height (RCMH) of potato slices, the RCMH was selected to describe the 3D morphological changes in the potato drying process. A critical point and a termination point for RCMH of potato slices in the drying process were observed. Samples varied widely after the critical point was reached. A logarithmic function model was used to assess differences in the RCMH at the critical point and the termination point. The R-squared (R2) value of 0.9 suggested a strong correlation between the parameters of the experiment and changes in slice thickness and diameter. The model proposed in this paper could accurately characterize the late-stage changes in potato slice qualities during hot air drying of potato slices.

Eggshell crack detection based on the transient impact analysis and cross-correlation method.

To explore the transient impact process for cracked eggshell detection, an equivalent mechanical model was built based on a self-designed automatic excitation device. Through analysis of power spectrum from dynamic force signal, it was found that the impact speed affects only the impaction energy. In contrast, the material of the impact head and the weight of the excitation rod determine the energy and the cut-off frequency of the impaction. When the weight of impact tup is less than 6.62 g, the cut-off frequency of excitation impact can cover the egg's inherent frequency. Then, an optimized experiment system was designed to acquire the response acoustic signals. The cross-correlation analysis and Bayes classification methods were carried out to detect the cracked eggshell. In the conducted experiments, a crack detection level of 97% and a false rejection level of 1% were achieved. From the findings, it can be concluded that the proposed method will assist in optimizing the impact device and simplifying the classification algorithm for an online detection system.

Development of Highly Sensitive Immunosensor for Detection of Staphylococcus aureus Based on AuPdPt Trimetallic Nanoparticles Functionalized Nanocomposite.

The rapid and sensitive detection of Staphylococcus aureus (S. aureus) is essential to ensure food safety and protect humans from foodborne diseases. In this study, a sensitive and facile electrochemical immunosensor using AuPdPt trimetallic nanoparticles functionalized multi-walled carbon nanotubes (MWCNTs-AuPdPt) as the signal amplification platform was designed for the label-free detection of S. aureus. The nanocomposite of MWCNTs-AuPdPt was prepared by an in situ growth method of loading AuPdPt trimetallic nanoparticles on the surface of MWCNTs. The synthesized MWCNTs-AuPdPt featured good conductivity and superior catalytic performance for hydrogen peroxide. The nanocomposite of MWCNTs-AuPdPt with good biocompatibility and high specific surface area was further functionalized by anti-S. aureus antibodies. The immobilized antibodies could efficiently capture S. aureus to the modified electrode by an immune reaction, which resulted in the change of catalytic current intensity to realize the sensitive detection of S. aureus. The designed immunosensor could detect S. aureus in a linear range from 1.1 × 102 to 1.1 × 107 CFU mL-1 with a low detection limit of 39 CFU mL-1. Additionally, the proposed immunosensor was successfully applied to determine S. aureus in actual samples with acceptable results. This strategy provided a promising platform for highly sensitive determination of S. aureus and other pathogens in food products.

Electrochemical immunosensor based on self-assembled gold nanorods for label-free and sensitive determination of Staphylococcus aureus.

An electrochemical immunosensor based on self-assembled gold nanorods on glassy carbon electrode was developed for label-free and sensitive detection of Staphylococcus aureus (S. aureus). The gold nanorods were firstly assembled on the electrode surface by using poly-(diallyldimethylammonium chloride) (PDDA) and poly-(styrenesulfonate) (PSS) as the linkers, followed by the functionlization of anti-S. aureus antibodies. The immobilized antibodies on self-assembled gold nanorods could efficiently capture S. aureus to the modified electrode by the specific immune reaction, which clearly blocked the electron transfer of electrochemical probes on the electrode surface due to the resistance of S. aureus. Atomic force microscopy and electrochemical impedance spectroscopy were used to verify the stepwise assembly of the immunosensor fabrication. The immunosensor could detect S. aureus in a linear range from 1.8 × 103 to 1.8 × 107 CFU mL-1 with a low detection limit of 2.4 × 102 CFU mL-1. Furthermore, the designed electrochemical immunosensor was successfully used to determine S. aureus in milk samples with acceptable results. The proposed immunosensor could be further expanded to sensitive detect other pathogens with the addition of specific antibodies.

Simultaneous detection of TNOS and P35S in transgenic soybean based on magnetic bicolor fluorescent probes.

A magnetic-separation-dual-targets fluorescent biosensor was fabricated to detect terminator nopaline synthase (TNOS) and promoter of cauliflower mosaic virus 35s (P35S) in transgenic soybean based on incorporation of bicolor CdTe quantum dots carried by silica nanospheres. In this protocol, the fixed probes for TNOS or P35S were magnetized firstly with Fe3O4@Au magnetic nanosphere by Au-S covalent bonding to achieve magnetized probes. Meanwhile, the capture probes for TNOS or P35S were functionalized with green or red fluorescent microspheres respectively to obtain fluorescently-labeled probes, which could emit relative strong green or red fluorescent signal. Two terminals of TNOS or P35S were recognized by magnetized probes and fluorescently-labeled probes respectively to form the sandwiched structures in the process of biosensor development subsequently, and it was separated by a magnet instantly. The fluorescence intensities of remnant supernatant were measured and analyzed accordingly to achieve simultaneous detection of TNOS and P35S. This biosensor exhibited a good dynamic range, low limit of detection and excellent selectivity in detecting transgenic soybean.