Rapid and stable detection of three main mycotoxins in rice using SERS optimized AgNPs@K30 coupled multivariate calibration.

Food safety is regarded as a crucial factor in both human health and economic progress. This study focuses on the fabrication of a label-free surface-enhanced Raman scattering (SERS) sensor for rapid sensing of three main mycotoxins (aflatoxin B1 (AFB1), ochratoxin A (OTA), ochratoxin B (OTB)) in rice using the optimized rough silver nanoparticles (AgNPs@K30) with enhancement factor (EF) 1.58 × 107 coupled multivariate calibration. Two variable selection chemometric calibration methods were comparatively applied. And genetic algorithm-partial least square achieved optimum correlation coefficient = 0.9797, 0.9779, and 0.9827, respectively for AFB1 ranging from 0.5 to 250 µg/Kg, for OTA and OTB 1 to 500 µg/Kg. The limit of detection (LOD) = 1.145, 1.133, and 1.180 µg/Kg, respectively, were determined according to principal component analysis-calibrated loading weight approach. And the great stability and reproducibility revealed the prepared SERS sensor has the potential to predict AFB1, OTA, and OTB in real rice samples.

Fraud detection in crude palm oil using SERS combined with chemometrics.

Edible crude palm oil (CPO) is a vital oil utilized in various industries, including food, pharmaceuticals, and domestic cooking. Unfortunately, reports of CPO adulteration with harmful Sudan dyes have surfaced over the years. Surface-enhanced Raman spectroscopy (SERS) and chemometrics were employed to detect Sudan dyes adulteration in CPO within 900 - 1800 cm- 1 Raman peak. The concentration of Sudan dyes detected in CPO samples ranged between 0.005 and 4 ppm. The principal component analysis (PCA) model detected Sudan II and Sudan IV in CPO with 99.88 and 99.90% accuracy. Linear discriminant analysis (LDA) and K-Nearest Neighbors (KNN) also recorded high detection rates of Sudan II and IV dyes in CPO. Sudan II and IV dyes could be detected at 0.0028 ppm and 0.0019 ppm by this sensor. The performance of the Au@Ag SERS sensor was comparable to that of HPLC. This study proved SERS and chemometrics can be used to authenticate edible CPO.

An upconversion nanosensor for rapid and sensitive detection of tetracycline in food based on magnetic-field-assisted separation.

Tetracycline, a broad-spectrum antibiotic, has been widely used in disease treatment and other fields. However, due to the unreasonable use, its residue remains in food which eventually harms human health. Here described an upconversion nanosensor for tetracycline detection based on magnetic separation and electrostatic adsorption. To identify tetracycline, tetracycline aptamer, and europium ions (Eu3+) were introduced in the system. According to the electrostatic adsorption principle, Eu3+ exposed core-shell UCNPs were bound to negative complex of magnetic nanoparticles (MNPs) and aptamer. In the presence of tetracycline, UCNPs separated with MNPs-aptamer and remained in the supernatant by an external magnetic field. Under optimal conditions, the linear detection range of tetracycline was 0.5-1000 ng·mL-1, and the detection limit was 0.17 ng·mL-1. It has been successfully applied to detect tetracycline in food samples. The constructed method provided broad prospects for tetracycline detection with the merits of simple operation, high sensitivity, excellent repeatability, and selectivity.

Simultaneous quantification of deoxymyoglobin and oxymyoglobin in pork by Raman spectroscopy coupled with multivariate calibration.

Because of the nutritional advantages and customer acceptance, it is vital to ensure pork meat quality. This study examined the quantification of myoglobin proportions (deoxymyoglobin and oxymyoglobin) by coupling Raman spectroscopy with efficient variables selection chemometrics. Prior to acquiring Raman spectroscopic data, the fractions of myoglobin were determined. Afterward, multivariate calibration methods like partial least square (PLS), competitive adaptive reweighted sampling (CARS-PLS), genetic algorithm-PLS (GA-PLS), and random frog-PLS (RF-PLS) were applied and evaluated. The models' performance was assessed using correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD). The RF-PLS model achieved optimal results for both deoxymyoglobin and oxymyoglobin, with Rp = 0.8936; RMSEP = 2.91 and RPD = 1.97 for the former and Rp = 0.9762; RMSEP = 1.23 and RPD = 4.47 for the latter, respectively. Therefore, this work demonstrated that Raman spectroscopy paired with RF-PLS could be employed for nondestructive, fast, and easy detection of deoxymyoglobin and oxymyoglobin.

Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis.

Two key parameters (acidity and peroxide content) for evaluation of the oxidation level in crude peanut oil have been studied. The titrimetric analysis was carried out for reference data collection. Then, near-infrared spectroscopy in combination with chemometric algorithms such as partial least square (PLS); bootstrapping soft shrinkage-PLS (BOSS-PLS); uninformative variable elimination-PLS (UVE-PLS), and competitive-adaptive reweighted sampling-PLS (CARS-PLS) were attempted and assessed. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to individually evaluate the performance of the models. Optimum results were noticed with CARS-PLS, 0.9517 ≤ Rc ≤ 0.9670, 0.9503 ≤ Rp ≤ 0.9637, 0.0874 ≤ RMSEP ≤ 0.5650, and 3.14 ≤ RPD ≤ 3.64. Therefore, this affirmed that the near-infrared spectroscopy coupled with CARS-PLS could be used as a simple, fast, and non-invasive technique for quantifying acid value and peroxide value in crude peanut oil.

Rapid detection and prediction of chloramphenicol in food employing label-free HAu/Ag NFs-SERS sensor coupled multivariate calibration.

Considering growing food safety issues, hollow Au/Ag nano-flower (HAu/Ag NFs) nanosensor has been synthesized for label-free and ultrasensitive detection of chloramphenicol (CP) via integrating the surface-enhanced Raman scattering (SERS) and multivariate calibration. As the anisotropic plasmonic nanomaterials, HAu/Ag NFs had numerous nano-chink on their surface, which offered huge hotspots for analytes. CP generated a strong SERS signal while adsorbed on the surface of HAu/Ag NFs and noted excellent linearity with 1st derivative-competitive adaptive reweighted sampling-partial least squares (CARS-PLS) in the range of 0.0001-1000 µg/mL among the four applied multivariate calibrations. Additionally, CARS-PLS generated the lowest prediction error (RMSEP) of 0.089 and 0.123 µg/mL for milk and water samples, respectively, and any CARS-PLS model could be used for both samples according to T-test results (P > 0.05). The intra- and interday recovery for both samples were in the range of 92.62-96.74% with CV < 10%, suggested the proposed method has excellent accuracy and precision.

Bioconversion of agro-food industrial wastes into value-added peptides by a Bacillus sp. Mutant through solid-state fermentation.

Advances in microbial enzyme technology offer a significant opportunity for developing low-energy bioconversion solutions for industrial wastes as inexpensive feedstocks for useful products. In this short communication, two agro-food industrial wastes, chicken feather powder (CFP) and okara, were converted into peptides by a Bacillus licheniformis mutant using solid-state fermentation (SSF). The optimum SSF conditions for okara to CFP ratio, inoculum size, and time were 0.7 (7:10), 15%, and 90 h, respectively, which produced 185.99 mg/g peptides, with 910.12 U/g keratinase activity and 85.03% antioxidant scavenging activity. Compared to okara, CFP with mutant strain showed 11.28% higher keratinase activity and produced higher amounts of peptides (5.51%).

Rapid detection of chlorpyrifos residue in rice using surface-enhanced Raman scattering coupled with chemometric algorithm.

Due to the continuous development and progress of society and more and more attention to the quality and safety of food, rapid testing of pesticides in food is of great significance. In this paper, surface-enhanced Raman spectroscopy (SERS) and chemometric algorithms were employed collectively to quantify chlorpyrifos (CP) residues in rice samples. The SERS spectra from different concentrations (0.01-1000 µg/mL) of CP were collected using AgNPs-deposited-ZnO nanoflower (NFs)-like nanoparticles (Ag@ZnO NFs) SERS sensor. Four quantitative chemometric models for CP were comparatively studied, and the competitive adaptive reweighted sampling-partial least squares model achieved the best prediction and practical applicability for predicting CP levels with a limit of detection of 0.01 µg/mL. The results of the student's t-test showed no significant difference between this method and high-performance liquid chromatography (HPLC), and good relative standard deviation (RSD) indicated that this method could be used for the detection of CP in rice.

Application of benchtop NIR spectroscopy coupled with multivariate analysis for rapid prediction of antioxidant properties of walnut (Juglans regia).

Benchtop near-infrared (NIR) spectroscopy coupled with multivariate analysis was used for the classification and prediction of antioxidant properties of walnut. Total phenolic content (TPC), total flavonoid content (TFC), ABTS assay and FRAP assay were performed spectrophotometrically. The synergy interval partial least square coupled competitive adaptive reweighted sampling (Si-CARS-PLS) was used for the prediction. A decent discrimination using principal component analysis (PCA) was observed by mean of spectroscopic and antioxidant properties data with total cumulative variance of 99.26% (PC1 = 95.07%, PC2 = 2.98%, PC3 = 1.21%) and 96.60% (PC1 = 64.28%, PC2 = 32.32%) respectively. The Si-CARS-PLS yielded optimal performance, RP = 0.9616, RPD = 3.807 for TPC, RP = 0.9657, RPD = 3.367 for TFC, RP = 0.9683, RPD = 2.728 for ABTS assay, and RP = 0.914, RPD = 2.669 for FRAP assay. These findings revealed that NIR integrated with Si-CARS-PLS could be used for the prediction of antioxidant properties of walnut.

Investigation of nonlinear relationship of surface enhanced Raman scattering signal for robust prediction of thiabendazole in apple.

Thiabendazole (TBZ) is extensively used in agriculture to control molds; residue of TBZ may pose a threat to humans. Herein, surface-enhanced Raman spectroscopy (SERS) coupled variable selected regression methods have been proposed as simple and rapid TBZ quantification technique. The nonlinear correlation between the TBZ and SERS data was first diagnosed by augmented partial residual plots method and calculated by runs test. Au@Ag NPs with strong enhancement factor (EF = 4.07 × 106) of Raman signal was used as SERS active material to collect spectra from TBZ. Subsequently, three nonlinear regression models were comparatively investigated and the competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) achieved a higher correlation coefficient (Rp2 = 0.9406) and the lower root-mean-square-error of prediction (RMSEP = 0.5233 mg/L). Finally, recoveries of TBZ in apple samples were 83.02-93.54% with relative standard deviation (RSD) value < 10%. Therefore, SERS coupled CARS-ELM could be employed as a rapid and sensitive approach for TBZ detection in Fuji apples.

Quantification of deltamethrin residues in wheat by Ag@ZnO NFs-based surface-enhanced Raman spectroscopy coupling chemometric models.

Deltamethrin, one of the most toxic pyrethroids, is commonly used to inhibit pests in wheat. However, the trace levels of deltamethrin in wheat is alarming to human health. In this study, surface-enhanced Raman spectroscopy (SERS)-active silver nanoparticles-plated-zinc oxide nanoflowers (Ag@ZnO NFs) nano-sensor were employed for rapid and sensitive quantification of deltamethrin in wheat. To sufficiently utilize the chemical-related information in SERS spectra, various spectral pretreatment and chemometric models were studied. The mean centering (MC) coupling successive projection algorithm-partial least squares regression (SPA-PLS) provided optimal predictive performance (correlation coefficient of prediction (Rp) = 0.9736 and residual predictive deviation (RPD) = 4.75). The proposed method achieved the limit of detection (LOD) = 0.16 µg·kg-1, the recovery of predicted results was in the range of 96.33-109.17% and the relative standard deviation (RSD) was < 5%. The overall results suggested that SERS based Ag@ZnO NFs combined with MC-SPA-PLS could be an easy and efficient method to quantify deltamethrin residue levels in wheat.

Landing microextraction sediment phase onto surface enhanced Raman scattering to enhance sensitivity and selectivity for chromium speciation in food and environmental samples.

The current study explores the first full mode liquid microextraction technique coupled with surface-enhanced Raman spectroscopy (SERS), and has been successfully applied for chromium speciation in food and environmental matrices. Herein, chromium as chlorochromate anion [CrO3Cl]- and the cationic rhodamine 6G [RG]+ dye has been extracted in organic phase as a complex ion associate [RG+.CrO3Cl-.nS]org at pH ≤ 1.0. Afterwards, the extracted phase was deposited on the surface of the nano-flower shaped silver nanoparticles substrate and the SERS response was monitored against the reagent blank at 1505 cm-1. Substrate characterizations, reaction mechanism assignment, stoichiometry, speciation, analytical applications, selectivity and validation were performed. The analytical procedure exhibits a detection limit of 0.03 µg L-1 under the optimized experimental conditions. The accuracy of the proposed strategy was validated by inductively coupled plasma optical emission spectrometry method using student's t- and F tests at 95% confidence.

A universal SERS aptasensor based on DTNB labeled GNTs/Ag core-shell nanotriangle and CS-Fe3O4 magnetic-bead trace detection of Aflatoxin B1.

A novel universal Surface-enhanced Raman Spectroscopy (SERS) based aptasensor platform for the trace detection of Aflatoxin B1 (AFB1), a common food contaminating mycotoxin, has been constructed, with the aid of the specific interaction between AFB1 and aptamers. The amino-terminal aptamer conjugated magnetic-bead (CS-Fe3O4) and the gold nanotriangles (GNTs)-DTNB@Ag-DTNB nanotriangles (GDADNTs) were used as the capturer and the reporter of AFB1, respectively. Under the optimized assay condition, the platform shows a distinguished sensitivity with the LOD as low as 0.54 pg/mL and the linear range from 0.001 to 10 ng/mL, a high stability of the SERS substrate activity remained three months at least, a decent reproducibility with RSD of ca. 5%, and a good selectivity to the general coexisted interferences. The distinguished sensitivity and selectivity for trace AFB1 detection has been achieved mainly due to the strong Raman enhancement effect of GNTs as the kernel for GDADNTs from the double-layer of the reporter molecules, the specificity of aptamer and superparamagnetic CS-Fe3O4 respectively. Furthermore, the proposed SERS aptasensor is universal to other trace molecules detection with the specific aptamers.

A magnetite/PMAA nanospheres-targeting SERS aptasensor for tetracycline sensing using mercapto molecules embedded core/shell nanoparticles for signal amplification.

Surface-enhanced Raman scattering (SERS) biosensors have promising potential in the field of antibiotics detection because of their ultrahigh detection sensitivity. This paper reports a rapid and sensitive SERS-based magnetic nanospheres-targeting strategy for sensing tetracycline (TTC) using aptamer-conjugated magnetite colloid nanocrystal clusters (MCNCs)-polymethacrylic acid (PMAA) magnetic nanospheres (MNs) as the recognition and the Au/PATP/SiO2 (APS) as the labels. Initially, MNs were fabricated and conjugated with the aptamers through condensation reaction. MNs possessed high saturation magnetization (Ms) value of 71.5emu/g and excellent biocompatibility, which facilitated the rapid and easy magnetic separation. Then, complementary DNA (cDNA) were loaded on the APS nanocarrier to produce a large amplification factor of Raman signals. The MNs-targeting aptasensor was thus fabricated by immobilizing the APS to the MNs' surfaces via the hybrid reaction between cDNA and aptamers. Sequel, TTC bound successfully to the aptamer upon its addition with the subsequent release of some cDNA-APS into the bulk solution. Under magnet attraction, the nanospheres were deposited together. Consequently, a display of strong SERS signals by supernatants of the resulting mixtures with increasing TTC concentrations was observed. The proposed aptasensor showed excellent performances for TTC detection along with wide linear range of 0.001-100ng/mL, low detection limit 0.001ng/mL, high sensitivity, and good selectivity to the general coexisted interferences.