Rapid screening on aflatoxins’ presence in Pistachia vera nuts using diffuse reflectance infrared Fourier transform spectroscopy and chemometrics

Valasi, Lydia; Γεωργιαδου, Μαρια; Tarantilis, Petros Α.; Yanniotis, S.; Pappas, Christos S.

doi:10.1007/s13197-020-04549-5

Cited by 11 publications

(7 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The vibration mode observed in the wavenumber range of 1290-1270 cm −1 could have been due to the C-O-C anti-symmetrical stretching of aromatic acid ester. The unsaturated δ-lactone ring was absorbed at 1270-1060 cm −1 [23]. The region between 900 cm −1 -600 cm −1 generally arose from aromatic ring vibrations [24].…”

Section: Sr-ftir Results and Analysismentioning

confidence: 98%

Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies

Zhang

Jia

et al. 2022

Sensors

View full text Add to dashboard Cite

To study the dynamic changes of nutrient consumption and aflatoxin B1 (AFB1) accumulation in peanut kernels with fungal colonization, macro hyperspectral imaging technology combined with microscopic imaging was investigated. First, regression models to predict AFB1 contents from hyperspectral data ranging from 1000 to 2500 nm were developed and the results were compared before and after data normalization with Box-Cox transformation. The results indicated that the second-order derivative with a support vector regression (SVR) model using competitive adaptive reweighted sampling (CARS) achieved the best performance, with RC2 = 0.95 and RV2 = 0.93. Second, time-lapse microscopic images and spectroscopic data were captured and analyzed with scanning electron microscopy (SEM), transmission electron microscopy (TEM), and synchrotron radiation-Fourier transform infrared (SR-FTIR) microspectroscopy. The time-lapse data revealed the temporal patterns of nutrient loss and aflatoxin accumulation in peanut kernels. The combination of macro and micro imaging technologies proved to be an effective way to detect the interaction mechanism of toxigenic fungus infecting peanuts and to predict the accumulation of AFB1 quantitatively.

show abstract

Section: Sr-ftir Results and Analysismentioning

confidence: 98%

Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies

Zhang

Jia

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Additionally, the fingerprint of two carbonyl oxygen atoms in AFs showed increased peak intensity in the test samples at 1647.362 cm –1 as studied by a previous report. 74 Figure 3 indicates the molecular site for standard pure AFs at nearby 3035–2821, 1770–1721, and 1570–1481 cm –1 spectral regions; 75 for solvent methanol, at 3367.42 and 1934.85 cm –1 ; 76 and for Zn(Cur)OBt-methanol (control), at around 1654 cm –1 corresponding to stretching vibrations of ν(C=C) and ν(C=O) in the Cur–Zn(II) interaction complex, respectively; 77 ν(=C) and ν(C=O) were red shifted to 1647.36 cm –1 due to Zn(Cur)OBt-AFs interaction. Additionally, a blue shift in OH stretching and red shift in C–H bending are seen for Zn(Cur)OBt-AFs complex at 3256 and 1966 cm –1 , respectively, indicating the presence of AFs in the composite.…”

Section: Results and Discussionmentioning

confidence: 99%

Sensitive Metal Oxide-Clay Nanocomposite Colorimetric Sensor Development for Aflatoxin Detection in Foods: Corn and Almond

Khansili

Krishna

2021

ACS Omega

View full text Add to dashboard Cite

The work reports on zinc oxide bentonite nanocomposite (ZnOBt) chemical route synthesis, characterization, and investigation of curcumin (Cur) functionalization for a label-free colorimetric detection of total aflatoxins (AFs) in foods. XRD of ZnO nanoparticles (NPs) confirmed the wurtzite structure (2θ = 36.2°) and that of ZnOBt showed the intercalated interlayer composite phase. The Debye–Scherrer relation calculated the crystallite size as 20 nm (ZnO) and 24.4 nm (ZnOBt). Surface morphology by SEM exhibited flower-like hexagonal, rod-shaped ZnO NPs on the bentonite surface. Colorimetric reaction involved two-stage redox reactions between ZnOBt and dye Cur followed by AFs phenolic group and Zn(Cur)OBt. Cur gets oxidized at its diketone moiety in the presence of ZnOBt to form a red colored complex Zn(Cur)OBt, which further scavenge protons from AFs phenolic group, and gets oxidized to AFs-Zn(Cur)OBt (yellow). Binding of AFs-Zn(Cur)OBt is characterized by FT-IR ascribed to C–H bending (1966.615 cm –1 ), O–H stretching (3256.974 cm –1 ), and C=O stretching (1647.362 cm –1 ). 1 H NMR chemical shifts (δ) (ppm) showed an increase in proton at the aliphatic region (0 to 4.4) while removal of proton in ether at 4.4 to 6 regions. Job plot calculation using UV–Vis data resulted in a higher total AF binding coefficient of Zn(Cur)OBt ( K a = 3.77 × 10 6 mol –1 L) compared to Zn(Cur)O ( K a = 0.645 × 10 6 mol –1 L) as well as a molar ratio of 1:1 by the Benesi–Hildebrand plot equation. Corn and almond food samples showed the total AFs LOD of 2.74 and 4.34 ppb, respectively. The results are validated with standard LC/MS-MS in compliance with MRL value as per the regulatory standard (EU).The NP-based method is facile and rapid and hence can be utilized for onsite detection of total AFs in foods.

show abstract

“…Valas et al [ 24 ] used the Kubelka–Munk transform and first-order derivatives for the prediction of pistachios containing aflatoxin, and the discriminant analysis correctly separated 100% of the calibration and validation sets and 80% of the test set. Cebrián et al [ 25 ] developed a support vector machine-discriminant analysis (SVM-DA) model approach for the prediction of ochratoxin A (OTA) in dry-cured ham with a prediction sensitivity of 85%.…”

Section: Spectral Data Processing Technologymentioning

confidence: 99%

Research Progress of Applying Infrared Spectroscopy Technology for Detection of Toxic and Harmful Substances in Food

Tian

et al. 2022

Foods

View full text Add to dashboard Cite

In recent years, food safety incidents have been frequently reported. Food or raw materials themselves contain substances that may endanger human health and are called toxic and harmful substances in food, which can be divided into endogenous, exogenous toxic, and harmful substances and biological toxins. Therefore, realizing the rapid, efficient, and nondestructive testing of toxic and harmful substances in food is of great significance to ensure food safety and improve the ability of food safety supervision. Among the nondestructive detection methods, infrared spectroscopy technology has become a powerful solution for detecting toxic and harmful substances in food with its high efficiency, speed, easy operation, and low costs, while requiring less sample size and is nondestructive, and has been widely used in many fields. In this review, the concept and principle of IR spectroscopy in food are briefly introduced, including NIR and FTIR. Then, the main progress and contribution of IR spectroscopy are summarized, including the model’s establishment, technical application, and spectral optimization in grain, fruits, vegetables, and beverages. Moreover, the limitations and development prospects of detection are discussed. It is anticipated that infrared spectroscopy technology, in combination with other advanced technologies, will be widely used in the whole food safety field.

show abstract

Rapid screening on aflatoxins’ presence in Pistachia vera nuts using diffuse reflectance infrared Fourier transform spectroscopy and chemometrics

Cited by 11 publications

References 24 publications

Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies

Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies

Sensitive Metal Oxide-Clay Nanocomposite Colorimetric Sensor Development for Aflatoxin Detection in Foods: Corn and Almond

Research Progress of Applying Infrared Spectroscopy Technology for Detection of Toxic and Harmful Substances in Food

Contact Info

Product

Resources

About