Innovative Infrared Spectroscopic Technologies for the Prediction of Deoxynivalenol in Wheat.

Mycotoxin contamination in cereals is a global food safety concern. One of the most common mycotoxins in grains is deoxynivalenol (DON), a secondary metabolite produced by the fungi and . Exposure to DON can lead to adverse health effects in both humans and animals including vomiting, dizziness, and fever.

Antibacterial Properties of Copper Oxide Nanoparticles (Review).

The use of metal and metal oxide nanoparticles is frequently regarded as a potential solution to the issue of bacterial antibiotic resistance. Among the proposed range of nanoparticles with antibacterial properties, copper oxide nanoparticles are of particular interest. Although the antibacterial properties of copper have been known for a considerable period of time, studies on the effects of copper oxide nanomaterials with respect to biological systems have attracted considerable attention in recent years.

Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis.

The climate crisis further exacerbates the challenges for food production. For instance, the increasingly unpredictable growth of fungal species in the field can lead to an unprecedented high prevalence of several mycotoxins, including the most important toxic secondary metabolite produced by spp., i.

Laser-irradiating infrared attenuated total reflection spectroscopy of articular cartilage: Potential and challenges for diagnosing osteoarthritis.

Objective: A prototype infrared attenuated total reflection (IR-ATR) laser spectroscopic system designed for classification of human cartilage tissue according to its histological health status during arthroscopic surgery is presented. Prior to real-world applications, this so-called osteoarthritis (OA) scanner has been tested at conditions revealing the challenges associated with complex sample matrices and the accordingly obtained sparse spectral datasets.

Methods: studies on human knee cartilage samples at different contact pressures (i.

A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis.

The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.

Effects of Low-Frequency Randomly Polarized Electromagnetic Radiation, as Revealed upon Swelling of Polymer Membrane in Water with Different Isotopic Compositions.

Photoluminescence from the surface of Nafion polymer membrane upon swelling in water under irradiation by electromagnetic waves at a frequency of 100 MHz was studied. In these experiments, natural deionized (DI) water with a deuterium content of 157 ppm and deuterium-depleted water (DDW, deuterium content is 1 ppm) were explored. We have studied for the first time the effect of linearly and randomly polarized low-frequency electromagnetic radiation on the luminescence excitation.

Optimizing extraction solvents for deoxynivalenol analysis in maize infrared attenuated total reflection spectroscopy and chemometric methods.

Farmers, cereal suppliers and processors demand rapid techniques for the assessment of mould-associated contamination. Deoxynivalenol (DON) is among the most important toxins and related to human and animal diseases besides causing significant economic losses. Routine analytical techniques for the analysis of DON are either based on chromatographic or immunoanalytical techniques, which are time-consuming and frequently rely on hazardous consumables.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach.

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures.

Infrared Spectroscopy in Aqueous Solutions: Capabilities and Challenges.

Fourier-transform infrared (FTIR) spectroscopy provides rapid, reliable, quantitative, and qualitative analysis of samples in different aggregation states, i.e., gases, thin films, solids, liquids, etc.

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC).