Effects of different polysaccharide colloids on the structure and physicochemical properties of peanut protein and wheat gluten composite system under extrusion.

The structure and physicochemical properties of the complex system of peanut protein and gluten with different concentrations (0 %, 0.5 %, 1 %, and 2 %) of carboxymethyl cellulose (CMC) or sodium alginate (SA) under high-moisture extrusion were studied. The water absorption index and low-field nuclear magnetic resonance showed that adding 0.5 % SA could significantly improve the water uniformity of peanut protein extrudates, while the increase in water absorption was not significant. The texture properties showed that adding CMC or SA increased the hardness, vertical shearing force, and parallel shearing force of the system. Furthermore, adding 0.5 % SA increased approximately 33 % and 75.2 % of the tensile distance and strength of the system, respectively. The secondary structure showed that CMC or SA decreased the proportion of α-helix, ß-turn, and random coil, while increased ß-sheet proportion. The results of hydrophobicity, unextractable protein, and endogenous fluorescence revealed that CMC and SA reduced the surface hydrophobicity of the system and caused fluorescence quenching in the system. Additionally, it was found that CMC generally increased the free sulfhydryl group content, while SA exhibited the opposite effect.

Ultra-fast and ultra-efficient phenol removal from aqueous solution using a nano biocarbon adsorbent by RSM-CCD method: parameters, isotherm, kinetic, ANOVA.

The purpose of this research is to investigate the ability of peanut shell activated carbon (PSAC) to adsorb phenol from aqueous solutions. Phenolic wastewater in various industries and their release to the environment are environmental problems. Among the various separation methods, adsorption is an accepted method because of its efficiency, simplicity, cost-effectiveness, and possibility to use different adsorbent materials to achieve maximum adsorption efficiency. Response surface methodology (RSM) was used to minimize the required experiments, modeling, finding the optimal point, and variance analysis. Among the studied variables, pH, adsorbent dosage, and initial concentration are important. The results show that it is possible to completely remove at 300 ppm of phenol concentration and 5 min. Characterization of PSAC was done using Fourier transform infrared spectroscopy spectrum (FTIR), X-ray diffraction (XRD), transmission electron microscopy (TEM), Brunauer-Emmet-Teller (BET), and size analysis. By examining the isotherm models, it was found that the adsorption follows the Langmuir model. The maximum adsorption capacity was 250 mg g-1 based on the Langmuir model. The three combined features of complete removal, ultra-fast adsorption, and high adsorption capacity are the unique features of this nano biocarbon for phenol removal.

Peptidomics-based study of antihypertensive activity: discovery of novel ACE inhibiting peptides from peanut yogurt.

Studies have confirmed that yogurt has the activity of regulating blood pressure because it is rich in probiotic-fermented food-derived active peptides. There are also studies on angiotensin-converting enzyme inhibition (ACEI) peptide milk, but the bioactive molecules in it are still unclear. Therefore, in this study, we developed a peanut yogurt with ACEI activity, analyzed 1877 differential peptides and their antihypertensive pathways before and after fermentation using peptidomics, and identified three peptides (FLPYPY, QPPPSPPPFL and APFPEVFGK) with potential antihypertensive activity using molecular docking and chemical synthesis techniques. These results first elucidated the relationship between peanut yogurt peptides and antihypertensive function, demonstrated the benefits of peanut yogurt, and provided a theoretical basis for the application of probiotic fermented plant yogurt in health care.

Adsorptive removal of perfluorooctanoic acid from aqueous matrices using peanut husk-derived magnetic biochar: Statistical and artificial intelligence approaches, kinetics, isotherm, and thermodynamics.

Removal of perfluorooctanoic acid (PFOA) from water matrices is crucial owing to its pervasiveness and adverse ecological and human health effects. This study investigates the adsorptive removal of PFOA using magnetic biochar (MBC) derived from FeCl3-treated peanut husk at different temperatures (300, 600, and 900 °C). Preliminary experiments demonstrated that MBC600 exhibited superior performance, with its characterization confirming the presence of γ-Fe2O3. However, efficient PFOA removal from water matrices depends on determining the optimum combination of inputs in the treatment approaches. Therefore, optimization and predictive modeling of the PFOA adsorption were investigated using the response surface methodology (RSM) and the artificial intelligence (AI) models, respectively. The central composite design (CCD) of RSM was employed as the design matrix. Further, three AI models, viz. artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS) were selected to predict PFOA adsorption. The RSM-CCD model applied to optimize three input process parameters, namely, adsorbent dose (100-400 mg/L), pH (3-10), and contact time (20-60 min), showed a statistically significant (p < 0.05) effect on PFOA removal. Maximum PFOA removal of about 98.3% was attained at the optimized conditions: adsorbent dose: 400 mg/L, pH: 3.4, and contact time: 60 min. Non-linear analysis showed PFOA adsorption was best fitted by pseudo-second-order kinetics (R2 = 0.9997). PFOA adsorption followed Freundlich isotherm (R2 = 0.9951) with a maximum adsorption capacity of ∼307 mg/g. Thermodynamics and spectroscopic analyses revealed that PFOA adsorption is a spontaneous, exothermic, and physical phenomenon, with electrostatic interaction, hydrophobic interaction, and hydrogen bonding governing the process. A comparative analysis of the statistical and AI models for PFOA adsorption demonstrated high R2 (>0.99) for RSM-CCD, ANN, and ANFIS. This research demonstrates the applicability of the statistical and AI models for efficient prediction of PFOA adsorption from water matrices using MBC (MBC600).

Novel Environmentally Friendly RNAi Biopesticides: Targeting V-ATPase in Holotrichia parallela Larvae Using Layered Double Hydroxide Nanocomplexes.

RNA interference (RNAi)-based biopesticides offer an attractive avenue for pest control. Previous studies revealed high RNAi sensitivity in Holotrichia parallela larvae, showcasing its potential for grub control. In this study, we aimed to develop an environmentally friendly RNAi method for H. parallela larvae. The double-stranded RNA (dsRNA) of the V-ATPase-a gene (HpVAA) was loaded onto layered double hydroxide (LDH). The dsRNA/LDH nanocomplex exhibited increased environmental stability, and we investigated the absorption rate and permeability of dsRNA-nanoparticle complexes and explored the RNAi controlling effect. Silencing the HpVAA gene was found to darken the epidermis of H. parallela larvae, with growth cessation or death or mortality, disrupting the epidermis and midgut structure. Quantitative reverse transcription-polymerase chain reaction and confocal microscopy confirmed the effective absorption of the dsRNA/LDH nanocomplex by peanut plants, with distribution in roots, stems, and leaves. Nanomaterial-mediated RNAi silenced the target genes, leading to the death of pests. Therefore, these findings indicate the successful application of the nanomaterial-mediated RNAi system for underground pests, thus establishing a theoretical foundation for developing a green, safe, and efficient pest control strategy.

Bioactive compounds of peanut skin in prevention and adjunctive treatment of chronic non-communicable diseases.

The global prevalence of cancer continues to increase, so does its mortality. Strategies that can prevent/treat this condition are therefore required, especially low-cost and low-toxicity strategies. Bioactive compounds of plant origin have been presented as a good alternative. In this scenario, due to its abundant polyphenolic content (around 60 to 120 times greater than that of the grain), peanut skin by-products stand out as a sustainable source of food bioactives beneficial to human health. Investigated studies highlighted the importance of peanut skin for human health, its phytochemical composition, bioactivity and the potential for prevention and/or adjuvant therapy in cancer, through the advanced search for articles in the Virtual Health Library (VHL), Science direct and the Mourisco platform of the FioCruz Institute, from 2012 to 2022. Using the keywords, "peanut skin" AND "cancer" AND NOT "allergy", the words "peanut testa" and "peanut peel" were included replacing "peanut skin". 18 articles were selected from Plataforma Mourisco, 26 from Science Direct and 26 from VHL. Of these, 7 articles evaluated aspects of cancer prevention and/or treatment. Promising benefits were found in the prevention/treatment of chronic non-communicable diseases in the use of peanut and peanut skin extracts, such as cholesterolemia and glucose control, attenuation of oxidative stress and suppressive action on the proliferation and metabolism of cancer cells.

Characterization of Key Aroma Compounds and Main Contributing Amino Acids in Hot-Pressed Oil Prepared from Various Peanut Varieties.

The production of peanut oil in the industrial sector necessitates the utilization of diverse raw materials to generate consistent batches with stable flavor profiles, thereby leading to an increased focus on understanding the correlation between raw materials and flavor characteristics. In this study, sensory evaluations, headspace solid-phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC-MS), odor activity value (OAV) calculations, and correlation analysis were employed to investigate the flavors and main contributing amino acids of hot-pressed oils derived from different peanut varieties. The results confirmed that the levels of alcohols, aldehydes, and heterocyclic compounds in peanut oil varied among nine different peanut varieties under identical processing conditions. The OAVs of 25 key aroma compounds, such as methylthiol, 3-ethyl-2,5-dimethylpyrazine, and 2,3-glutarone, exceeded a value of 1. The sensory evaluations and flavor content analysis demonstrated that pyrazines significantly influenced the flavor profile of the peanut oil. The concentrations of 11 amino acids showed a strong correlation with the levels of pyrazines. Notably, phenylalanine, lysine, glutamic acid, arginine, and isoleucine demonstrated significant associations with both pyrazine and nut flavors. These findings will provide valuable insights for enhancing the sensory attributes of peanut oil and selecting optimal raw peanuts for its production.

Fabrication of an Antifouling Surface Plasmon Resonance Sensor with Stratified Zwitterionic Peptides for Highly Efficient Detection of Peanut Allergens in Biscuits.

Peanut allergen monitoring is currently an effective strategy to avoid allergic diseases, while food matrix interference is a critical challenge during detection. Here, we developed an antifouling surface plasmon resonance sensor (SPR) with stratified zwitterionic peptides, which provides both excellent antifouling and sensing properties. The antifouling performance was measured by the SPR, which showed that stratified peptide coatings showed much better protein resistance, reaching ultralow adsorption levels (<5 ng/cm2). Atomic force microscopy was used to further analyze the antifouling mechanism from a mechanical perspective, which demonstrated lower adsorption forces on hybrid peptide coatings, confirming the better antifouling performance of stratified surfaces. Moreover, the recognition of peanut allergens in biscuits was performed using an SPR with high efficiency and appropriate recovery results (98.2-112%), which verified the feasibility of this assay. Therefore, the fabrication of antifouling sensors with stratified zwitterionic peptides provides an efficient strategy for food safety inspection.

Sward characteristics, herbage accumulation and nutritional value of elephantgrass based mixed with or without pinto peanut.

Elephantgrass stands out for its high potential for forage production in different tropical and subtropical regions. In most properties, it is cultivated intensively with high doses of mineral fertilizers, mainly nitrogen, which makes production expensive and less sustainable. In this context, the mixtures of elephantgrass with forage legumes can make the system more efficient and with less environmental impact. Thus, the objective is to evaluate elephantgrass-based grazing systems,with or without a legume in terms of sward characteristics, herbage accumulation and nutritional value of pastures during one, agricultural year. Two grazing systems (treatments) were analyzed: (i) elephantgrass-based (EG) with mixed spontaneous-growing species (SGE) in the warm-season and ryegrass (R) in the cool-season; and (ii) EG + SGE + R + pinto peanut. The standardization criterion between the systems was the level of nitrogen fertilization (120 kg N/ha/year). The presence of pinto peanut positively affected the botanical composition of the pasture, with a reduction in SGE and dead material, and in the morphology of elephantgrass, with a greater proportion of leaf blades, and less stem + sheath and senescent material. In themixture with pinto peanut, there was an increase in herbage accumulation and greater nutritional value of forage.

Vis-NIR spectroscopic discriminant analysis of aflatoxin B1 excessive standard in peanut meal as feedstuff materials.

A fast, simple and reagent-free detection method for aflatoxin B1 (AFB1) is of great significance to food safety and human health. Visible and near-infrared (Vis-NIR) spectroscopy was applied to the discriminant analysis of AFB1 excessive standard of peanut meal as feedstuff materials. Two types of excessive standard discriminant models based on spectral quantitative analysis with partial least squares (PLS) and direct pattern recognition with partial least squares-discrimination analysis (PLS-DA) were established, respectively. Multi-parameter optimization of Norris derivative filtering (NDF) was used for spectral preprocessing; the two-stage wavelength screening method based on equidistant combination-wavelength step-by-step phase-out (EC-WSP) was used for wavelength optimization. A rigorous sample experimental design of calibration-prediction-validation was utilized. The calibration and prediction samples were used for modeling and parameter optimization, and the selected model was validated using the independent validation samples. For quantitative analysis-based, the positive, negative and total recognition-accuracy rates in validation (RARV+, RARV-, and RARV) were 84.8 %, 74.6 % and 79.8 %, respectively; but, the relative root mean square error of prediction was as high as 51.0 %. For pattern recognition-based, the RARV+, RARV-, and RARV were 93.3 %, 90.5 % and 91.9 %, respectively. Moreover, the number of wavelengths N was drastically reduced to 17, and the discrete wavelength combination was in NIR overtone frequency region. The results indicated that, the EC-WSP-PLS-DA model achieved significantly better discrimination effect. Thus demonstrated that Vis-NIR spectroscopy has feasibility for the excessive standard discrimination of aflatoxin B1 in feedstuff materials.

Residue changes, degradation, processing factors and their relation between physicochemical properties of pesticides in peanuts during multiproduct processing.

This study systematically investigates the residue changes, processing factors (PFs), and relation between the physicochemical properties of pesticides during peanut processing. Results revealed that peeling, washing, and boiling treatments removed partial or substantial pesticide residues from peanuts with PFs of 0.29-1.10 (most <1). By contrast, pesticides appeared to be partially concentrated during roasting, stir-frying, and deep-frying peanuts with PFs of 0.16-1.25. During oil pressing, 13 of the 28 pesticides were concentrated in the peanut oil (PF range: 1.06-2.01) and 25 of the pesticides were concentrated in the peanut meal (1.07-1.46). Physicochemical parameters such as octanol-water partition coefficient, degradation point, molecular weight, and melting point showed significant correlations with PFs during processing. Notably, log Kow exhibited strong positive correlations with the PFs of boiling, roasting, and oil pressing. Overall, this study describes the fate of pesticides during multiproduct processing, providing guidance to promote the healthy consumption of peanuts for human health.

Non-destructive SPE-UPLC-based Quantification of Aflatoxins and Stilbenoid Phytoalexins in Single Peanut (Arachis spp.) Seeds.

Aflatoxins are highly carcinogenic secondary metabolites of some fungal species, particularly Aspergillus flavus. Aflatoxins often contaminate economically important agricultural commodities, including peanuts, posing a high risk to human and animal health. Due to the narrow genetic base, peanut cultivars demonstrate limited resistance to fungal pathogens. Therefore, numerous wild peanut species with tolerance to Aspergillus have received substantial consideration by scientists as sources of disease resistance. Exploring plant germplasm for resistance to aflatoxins is difficult since aflatoxin accumulation does not follow a normal distribution, which dictates the need for the analyses of thousands of single peanut seeds. Sufficiently hydrated peanut (Arachis spp.) seeds, when infected by Aspergillus species, are capable of producing biologically active stilbenes (stilbenoids) that are considered defensive phytoalexins. Peanut stilbenes inhibit fungal development and aflatoxin production. Therefore, it is crucial to analyze the same seeds for peanut stilbenoids to explain the nature of seed resistance/susceptibility to the Aspergillus invasion. None of the published methods offer single-seed analyses for aflatoxins and/or stilbene phytoalexins. We attempted to fulfill the demand for such a method that is environment-friendly, uses inexpensive consumables, and is sensitive and selective. In addition, the method is non-destructive since it uses only half of the seed and leaves the other half containing the embryonic axis intact. Such a technique allows germination and growth of the peanut plant to full maturity from the same seed used for the aflatoxin and stilbenoid analysis. The integrated part of this method, the manual challenging of the seeds with Aspergillus, is a limiting step that requires more time and labor compared to other steps in the method. The method has been used for the exploration of wild Arachis germplasm to identify species resistant to Aspergillus and to determine and characterize novel sources of genetic resistance to this fungal pathogen.

Comparative analysis of the equilibrium, kinetics, and characterization of the mechanism of rapid adsorption of Congo red on nano-biosorbents based on agricultural waste in industrial effluents.

This study aims to remove Congo red dye from industrial effluent using economical agriculturally-based nano-biosorbents like magnetic orange peel, peanut shells, and tea waste. The nano-biosorbents were characterized by various analytical techniques like SEM, FT-IR, BET and XRD. The highest adsorption capacity was obtained under the following ideal conditions: pH = 6 (orange peel and peanut shells), pH = 3 (tea waste), and dosages of nano-biosorbents with varying timeframes of 50 min for tea waste and peanut shells and 30 min for orange peel. The study found that tea waste had the highest removal rate of 94% due to its high porosity and responsible functional groups, followed by peanut shells at 83% and orange peel at 68%. The Langmuir isotherm model was found to be the most suitable, with R2 values of 0.99 for tea waste, 0.92 for orange peel, and 0.71 for peanut shells. On the other hand, a pseudo-second-order kinetic model was very feasible, showing an R2 value of 0.99 for tea waste, 0.98 for peanut shells and 0.97 for orange peel. The significance of the current study lies in its practical application, enabling efficient waste management and water purification, thereby preserving a clean and safe environment.

Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system.

Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr â‰« Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35-74% of the variation in the BCF values of metals based on empirical prediction models.

Synergistic rosemary extract with TBHQ and citric acid improves oxidative stability and shelf life of peanut.

Lipid oxidation often accompanies the processing and storage of peanuts, which causes a serious waste of peanut resources. To solve the problem of being prone to oxidation in peanut processing, a ternary complex antioxidant based on rosemary extract (RE) was constructed to investigate its effect on the oxidative and thermal stability of peanuts, and the inhibition of peanut oxidation by compound antioxidants was revealed by dynamic Arrhenius formula and complexation theory. The results showed that there was a synergistic effect between RE and Tert-butyl hydroquinone (TBHQ), and the antioxidant effects of RE and TBHQ were 4.86 and 1.45 times higher when used in combination than when used alone, respectively. In addition, RE-TBHQ-CA (citric acid) effectively inhibited primary and secondary oxidation of peanuts with a shelf life 8.7 times longer than that of control peanuts. This study provides a novel antioxidant compounding idea, which has a positive effect on improving the quality of peanut and other nut products, prolonging the shelf life and reducing the waste of resources. PRACTICAL APPLICATION: Compounding a complex antioxidant that permits its use in peanuts. It was found that rosemary and TBHQ might have synergistic antioxidant effects. Meanwhile, this combination of RE-TBHQ-CA effectively inhibited the oxidation of peanut oils and prolonged the shelf life of peanuts. RE-TBHQ-CA is a highly efficient complex antioxidant that can reduce the amounts of antioxidants added while maintaining high antioxidant efficiency, which may be useful for the future preservation and storage of nut products as it positively affects the quality and shelf life of the product.

Quantitative detection of aflatoxin B1 in peanuts using Raman spectra and multivariate analysis methods.

Aflatoxin B1 (AFB1), among the identified aflatoxins, exhibits the highest content, possesses the most potent toxicity, and poses the gravest threat. It is commonly found in peanuts and their derivatives. This study employs Raman spectroscopy to monitor the AFB1 levels in moldy peanuts, providing a reliable theoretical basis for peanut storage management. Firstly, different degrees of moldy peanuts are spectrally characterized using a portable Raman spectrometer. Subsequently, a two-step hybrid strategy for feature selection is proposed, combining backward interval partial least squares (BiPLS) and variable combination population analysis (VCPA), aiming to simplify model complexity and enhance predictive accuracy. Finally, partial least squares (PLS) regression models are constructed based on different feature intervals and wavelength points. The research results reveal that the PLS regression model using the optimized feature intervals and wavelength points exhibits improved predictive capability and generalization performance. Notably, the BiPLS-VCPA-PLS model, established through the two-step optimization, selects nine wavelength variables, achieving a root mean square error of prediction (RMSEP) of 33.3147 µg∙kg-1, a correlation coefficient of the prediction set (RP) of 0.9558, and a relative percent deviation (RPD) of 3.4896. These findings demonstrate that the two-step feature optimization method, combining feature interval selection and feature wavelength selection, can more accurately identify optimal variables, thus enhancing detection efficiency and predictive precision.

A combined in vitro and in silico study of the inhibitory mechanism of angiotensin-converting enzyme with peanut peptides.

Food-derived peptides with low molecular weight, high bioavailability, and good absorptivity have been exploited as angiotensin-converting enzyme (ACE) inhibitors. In the present study, in-vitro inhibition kinetics of peanut peptides, in silico screening, validation of ACE inhibitory activity, molecular dynamics (MD) simulations, and HUVEC cells were performed to systematically identify the inhibitory mechanism of ACE interacting with peanut peptides. The results indicate that FPHPP, FPHY, and FPHFD peptides have good thermal, pH, and digestive stability. MD trajectories elucidate the dynamic correlation between peptides and ACE and verify the specific binding interaction. Noteworthily, FPHPP is the best inhibitor with a strongest binding affinity and significantly increases NO, SOD production, and AT2R expression, and decreases ROS, MDA, ET-1 levels, ACE, and AT1R accumulation in Ang II-injury HUVEC cells.

Spectral intelligent detection for aflatoxin B1 via contrastive learning based on Siamese network.

Aflatoxins, harmful substances found in peanuts, corn, and their derivatives, pose significant health risks. Addressing this, the presented research introduces an innovative MSGhostDNN model, merging contrastive learning with multi-scale convolutional networks for precise aflatoxin detection. The method significantly enhances feature discrimination, achieving an impressive 97.87% detection accuracy with a pre-trained model. By applying Grad-CAM, it further refines the model to identify key wavelengths, particularly 416 nm, and focuses on 40 key wavelengths for optimal performance with 97.46% accuracy. The study also incorporates a task dimensionality reduction approach for continuous learning, allowing effective ongoing aflatoxin spectrum monitoring in peanuts and corn. This approach not only boosts aflatoxin detection efficiency but also sets a precedent for rapid online detection of similar toxins, offering a promising solution to mitigate the health risks associated with aflatoxin exposure.

A facile dual-mode SERS/fluorescence aptasensor for AFB1 detection based on gold nanoparticles and magnetic nanoparticles.

Aflatoxin B1 (AFB1) is a virulent metabolite secreted by Aspergillus fungi, impacting crop quality and posing health risks to human. Herein, a dual-mode Raman/fluorescence aptasensor was constructed to detect AFB1. The aptasensor was assembled by gold nanoparticles (AuNPs) and magnetic nanoparticles (MNPs), while the surface-enhanced Raman scattering (SERS) and fluorescence resonance energy transfer (FRET) effects were both realized. AuNPs were modified with the Raman signal molecule 4-MBA and the complementary chain of AFB1 aptamer (cDNA). MNPs were modified with the fluorescence signal molecule Cy5 and the AFB1 aptamer (AFB1 apt). Through base pairing, AuNPs aggregated on the surface of MNPs, forming a satellite-like nanocomposite, boosting SERS signal via increased "hot spots" but reducing fluorescence signal due to the proximity of AuNPs to Cy5. Upon exposure to AFB1, AFB1 apt specifically bound to AFB1, causing AuNPs detachment from MNPs, weakening the SERS signal while restoring the fluorescence signal. AFB1 concentration displayed a good linear relationship with SERS/fluorescence signal in the range of 0.01 ng/mL-100 ng/mL, with a detection limit as low as 5.81 pg/mL. The use of aptamer assured the high selectivity toward AFB1. Furthermore, the spiked recovery in peanut samples ranged from 91.4 % to 95.6 %, indicating the applicability of real sample detection. Compared to single-signal sensor, this dual-signal sensor exhibited enhanced accuracy, robust anti-interference capability, and increased flexibility, promising for toxin detection in food safety applications.

Novel advanced materials and magnetic solid phase extraction as approaches in sample preparation to enhance the analysis of ochratoxin A in peanuts.

Ochratoxin A (OTA) is a mycotoxin that can contaminate a variety of agricultural commodities, including fruit juices and wines. The capability of a magnetic solid-phase extraction (MSPE) method with a magnetic metal-organic framework (MOF) material having a three-layer core-shell structure to improve the detection of OTA in food matrices using high performance liquid chromatography is described. Analysis of the material through X-ray diffraction (XRD) indicated the successful synthesis of the magnetic nanomaterial Fe3O4@SiO2@UiO66-NH2. Scanning electron microscopy (SEM) and Zetasizer lab indicated its nano-sized morphological features. The conditions affecting the magnetic solid-phase extraction procedure, such as material dosage, pH, composition and amount of eluent, desorption solution and desorption time were investigated to obtain the optimal extraction conditions. Under optimized conditions, the recoveries of spiked analytes at three different concentrations ranged from 95.83 to 101.5%, and the relative standard deviations were below 5%. Coupling with HPLC allowed the limit of detection to be 0.3 µg kg-1. This method is simple and specific, and can effectively avoid the influence of coexisting elements and improve the sensitivity of determination through fast MSPE of OTA. It has broad development prospects in OTA detection pre-treatment.