AFB1–AP Conjugate for Enzyme Immunoassay of Aflatoxin B1in Corn Samples

Quantitative analysis of aflatoxin B1 of peanut by optimized support vector machine models based on near-infrared spectral features

This study designs a chemometric framework for quantitatively evaluating aflatoxin B1 (AFB1) in peanuts based on near-infrared (NIR) spectroscopy technique. The NIR spectra of peanut samples exhibiting diverse fungal contamination levels were acquired using a portable NIR spectrometer. Subsequently, appropriate pre-processing techniques were employed for data refinement. To streamline the analysis, the iterative variable subset optimization (IVSO) technique was employed to conduct an initial screening of the pre-processed NIR spectra, eliminating numerous irrelevant variables. Building upon this screening process, the beluga whale optimization (BWO) algorithm was utilized to optimize the selected feature variables further. Subsequently, support vector machine (SVM) models were developed using the refined near-infrared spectral features to test AFB1 in peanuts quantitatively. The results indicate that the SVM model significantly improves detection performance and generalization proficiency, particularly after secondary optimization using BWO-IVSO. Among the different models considered, the SVM model established after BWO-IVSO optimization exhibited the most extraordinary level of generalization, with a root mean square error of prediction of 24.6322 μg∙kg-1, a correlation coefficient of 0.9761, and a relative percent deviation of 4.6999. Overall, this investigation highlights the effectiveness of the proposed NIR spectroscopy model based on BWO-IVSO-SVM for quantitatively analyzing AFB1 in peanuts. The study contributes valuable technical and methodological insights that can serve as a reference for rapidly determining mycotoxins in cereal crops.

Comparative Study of Time-Resolved Fluorescent Nanobeads, Quantum Dot Nanobeads and Quantum Dots as Labels in Fluorescence Immunochromatography for Detection of Aflatoxin B1 in Grains

Label selection is an essential procedure for improving the sensitivity of fluorescence immunochromatography assays (FICAs). Under optimum conditions, time-resolved fluorescent nanobeads (TRFN), quantum dots nanobeads (QB) and quantum dots (QD)-based immunochromatography assays (TRFN-FICA, QB-FICA and QD-FICA) were systematically and comprehensively compared for the quantitative detection of aflatoxin B₁ (AFB₁) in six grains (corn, soybeans, sorghum, wheat, rice and oat). All three FICAs can be applied as rapid, cost-effective and convenient qualitative tools for onsite screening of AFB₁; TRFN-FICA exhibits the best performance with the least immune reagent consumption, shortest immunoassay duration and lowest limit of detection (LOD). The LODs for TRFN-FICA, QB-FICA and QD-FICA are 0.04, 0.30 and 0.80 μg kg⁻¹ in six grains, respectively. Recoveries range from 83.64% to 125.61% at fortified concentrations of LOD, 2LOD and 4LOD, with the coefficient of variation less than 10.0%. Analysis of 60 field grain samples by three FICAs is in accordance with that of LC-MS/MS, and TRFN-FICA obtained the best fit. In conclusion, TRFN-FICA is more suitable for quantitative detection of AFB₁ in grains when the above factors are taken into consideration.

Label Free QCM Immunobiosensor for AFB1 Detection Using Monoclonal IgA Antibody as Recognition Element

This study introduces the use of an IgA isotype aflatoxin (AF) specific monoclonal antibody for the development of a highly sensitive Quartz Crystal Microbalance (QCM) immunobiosensor for the detection of AF in inhibitory immunoassay format. The higher molecular weight of IgA antibodies proved an advantage over commonly used IgG antibodies in label free immunobiosensor measurements. IgA and IgG antibodies with similar affinity for AF were used in the comparative studies. Sensor surface was prepared by covalent immobilization of AFB1, using self assembled monolayer (SAM) formed on gold coated Quartz Crystal, with 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxy succinimide (EDC/NHS) method using a diamine linker. Nonspecific binding to the surface was decreased by minimizing the duration of EDC/NHS activation. Sensor surface was chemically blocked after AF immobilization without any need for protein blocking. This protein free sensor chip endured harsh solutions with strong ionic detergent at high pH, which is required for the regeneration of the high affinity antibody-antigen interaction. According to the obtained results, the detection range with IgA antibodies was higher than IgG antibodies in QCM immunosensor developed for AFB1.

Mechanism of aflatoxin uptake in roots of intact groundnut (Arachis hypogaea L.) seedlings

Aflatoxins are one of the most potent toxic substances that occur naturally, which enter agricultural soils through the growth of aflatoxigenic fungi in rhizhosphere and nonrhizhosphere soils. Though several reports regarding the uptake of aflatoxin by plants are available, the mechanism of aflatoxin uptake remains unknown. This study characterized the aflatoxin uptake mechanism by in vitro hydroponic experiments under variable conditions. The uptake reached saturation after 48 h of incubation for AFB1 and B2 and 60 h for AFG1 and G2. A linear increase in uptake with increasing aflatoxin concentrations was observed, and it fits both linear and nonlinear regression. AFB1 uptake was directly proportional to transpiration rate, and blocking aquaporin activity using mercuric chloride revealed its involvement in the uptake. None of the metabolic inhibitors used to block active transport had any effect on aflatoxin uptake except for sodium azide. From the present study, it could be concluded that aflatoxin uptake by groundnut roots followed mainly a passive way and is facilitated through aquaporins. The involvement of active component should be studied in detail.