In silico NIR spectroscopy - A review. Molecular fingerprint, interpretation of calibration models, understanding of matrix effects and instrumental difference.

https://doi.org/10.1016/j.fochx.2022.100430

Weight interpretation of artificial neural network model for analysis of rice (Oryza sativa L.) with near-infrared spectroscopy

Research progress and the application of near-infrared spectroscopy in protein structure and molecular interaction analysis

We aimed to develop an amino acid sequence-dependent analytical method using near-infrared (NIR) spectroscopy. The detailed analysis of the NIR spectra of eight different amino acid aqueous solutions (glycine, alanine, serine, glutamine, lysine, phenylalanine, tyrosine, and proline) revealed different spectral patterns characteristic of different amino acid residues in the 6200-5700 and 5000-4200 cm-1 regions, and the amino acids were identified based on the patterns. The spectra in the region of 5000-4500 cm-1 for tripeptide organic solutions that were composed of the aforementioned eight amino acids clearly showed the spectral differences depending on the amino acid species and amino acid sequences. Namely, tripeptide species were clearly differentiated from each other based on the spectral pattern of NIR bands due to the combinations of N-H stretching and amide II/III modes and those derived from the first overtones of amide II and amide I. The quantitative evaluation of changes in the concentrations of dipeptides and tripeptides composed of two different amino acids, glycine and proline was performed using partial least squares regression (PLSR) analysis and a combination of bands for amide modes. The calibration and validation results with high determination coefficients (R2 ≥ 0.99) were successfully obtained based on the amino acid sequences. The results not only revealed the usefulness of NIR spectroscopy as a process analytical technology (PAT) tool for synthesizing peptides in a micro flow reactor but also proposed a general method for quantitatively analyzing NIR spectra obtained in the course of chemical synthesis.

Development of an amino acid sequence-dependent analytical method for peptides using near-infrared spectroscopy.

Tebuthiuron is a selective herbicide for woody species and is commonly manufactured and sold as a granular formulation. This project investigated the use of infrared spectroscopy for the quality analysis of tebuthiuron granules, specifically the prediction of moisture content and tebuthiuron content. A comparison of different methods showed that near-infrared spectroscopy showed better results than mid-infrared spectroscopy, while a handheld NIR instrument (MicroNIR) showed slightly improved results over a benchtop NIR instrument (Antaris II FT-NIR Analyzer). The best-performing models gave an R2CV of 0.92 and RMSECV of 0.83% w/w for moisture content, and R2CV of 0.50 and RMSECV of 7.5 mg/g for tebuthiuron content. This analytical technique could be used to optimise the manufacturing process and reduce the costs of post-manufacturing quality assurance.

/pdf/infrared-spectroscopy-for-the-quality-control-of-a-granular-3epj9yip.pdf

Infrared Spectroscopy for the Quality Control of a Granular Tebuthiuron Formulation

Using near-infrared (NIR) spectroscopy, we aimed to develop a method of monitoring the increasing number of amide bonds with the elongation of the chain length of peptides. Because peptide synthesis can be monitored by evaluating the increasing number of amide bonds with dehydration occurring between amino acids, polyglycine, which has the simplest structure among polyamino acids, was studied, and the key bands whose absorption intensities increased with the elongation of the chain length, such as the bands attributed to glycine, diglycine, triglycine, and tetraglycine, were searched. The bands due to the combinations of the amide A and amide II/III modes in the region of 5000-4500 cm-1 were revealed to be good candidates for key bands, their second derivative intensities increased as the number of amide bonds increased, regardless of pH, solvent species, and the presence of protecting groups. The number of amide bonds was evaluated by a partial least square regression using the abovementioned combination bands, and a calibration model with a high determination coefficient (≥0.99) was constructed. These results not only have demonstrated the usefulness of NIR spectroscopy as a process analytical technology tool for the process of synthesizing the peptide in a microflow reactor but also have provided basic knowledge for analyzing amide bonds in the NIR spectra of proteins, polyamino acids, polypeptides, and polyamides.

Method of Monitoring the Number of Amide Bonds in Peptides Using Near-Infrared Spectroscopy

In a spectroscopic analysis device (1) according to the present invention, a control unit (40) acquires refractive index information regarding a sample (S) on the basis of information regarding a first spectroscopic spectrum in a first wavelength band in which only the resonance spectrum of surface plasmons is generated among spectroscopic spectra, uses the acquired refractive index information as a basis to determine the angle of incidence of radiated light (L1) radiated by a radiating unit (10) with respect to a membrane (M) such that the peak wavelength of the resonance spectrum and the peak wavelength of the absorption spectrum of the sample (S) match in a second spectroscopic spectrum in a second wavelength band in which the resonance spectrum and the absorption spectrum are generated among the spectroscopic spectra, and analyzes the state of the sample (S) from information regarding the second spectroscopic spectrum obtained on the basis of the determined angle of incidence.

Spectroscopic analysis device and spectroscopic analysis method

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Method of Monitoring the Number of Amide Bonds in Peptides Using Near-Infrared Spectroscopy

Spectroscopic analysis device and spectroscopic analysis method