Two-dimensional heterospectral correlation analysis of water and liquid oleic acid using an online near-infrared/mid-infrared dual-region spectrometer

Use of Near-Infrared-Mid-Infrared Dual-Wavelength Spectrometry to Obtain Two-Dimensional Difference Spectra of Sesame Oil as Inactive Drug Ingredient

The present study has investigated the transformation of sesame oil kept at low temperature during a definite period of time for refinement (called winterization) as an inactive drug ingredient by using two-dimensional difference spectra (2D-DS) analysis of spectra collected using a near-infrared (NIR) and mid-infrared (MIR) dual-wavelength spectrometer (NIR-MIR-DWS). The NIR and MIR spectra were measured nearly simultaneously from samples of sesame oil before and after winterization. The difference spectrum analysis of the obtained NIR-MIR data elucidated that, after the winterization process, the absorbances at peaks attributed to C=O, C=C, and OH groups decrease while the absorbances arising from the main chain (CH₂) increase. The result indicated the removal of lignan and the fatty acids with relatively short main chains. Moreover, sesame oil unwinterized was cooled from room temperature to near 1 ℃ and subsequently warmed to room temperature. And the cycle was repeated two times. Real-time monitoring during the cooling and warming processes were carried out using the NIR-MIR-DWS. The prediction results obtained from partial least square calibration model for the temperature suggests that there are subtle differences in the oil composition between the first cooling process and after the warming and cooling cycle. For the more detailed analysis, the 2D-DS method is proposed. The results of the analyses using 2D-DS revealed that the starting point of the transformation is around 15 ℃. It can be estimated that sesame oil is mainly transformed by the first cooling down. Moreover, it was implied that the structure of methylene (CH₂) was significantly related to the modifications in sesame oil with temperature change. A series of experimental results elucidated that the winterization of sesame oil removed its impurities and stabilized its conditions. These results are probably the first report on the effect of the winterization process on sesame oil.

Surface Structure of Acrylate Polymer Adhesives

Total internal reflection infrared (IR) absorption and visible-IR sum-frequency spectroscopies were used to study the role of acrylic acid in the evolution of surface structure in a poly(butyl acrylate)-based pressure-sensitive adhesive during the drying process. By monitoring these spectral responses and calculating the heterospectral correlation coefficients, we established that acrylic acid alters the nature of the molecular interactions at the surface. In the absence of acrylic acid, butyl acrylate orientation is driven by the packing of the polymer as the water evaporates. When acrylic acid is present, a rapid ordering of the copolymer takes place as a result of favorable hydrogen-bonding interactions with the surface.

Baseline Correction of Diffuse Reflection Near-Infrared Spectra Using Searching Region Standard Normal Variate (SRSNV)

An alternative baseline correction method for diffuse reflection near-infrared (NIR) spectra, searching region standard normal variate (SRSNV), was proposed. Standard normal variate (SNV) is an effective pretreatment method for baseline correction of diffuse reflection NIR spectra of powder and granular samples; however, its baseline correction performance depends on the NIR region used for SNV calculation. To search for an optimal NIR region for baseline correction using SNV, SRSNV employs moving window partial least squares regression (MWPLSR), and an optimal NIR region is identified based on the root mean square error (RMSE) of cross-validation of the partial least squares regression (PLSR) models with the first latent variable (LV). The performance of SRSNV was evaluated using diffuse reflection NIR spectra of mixture samples consisting of wheat flour and granular glucose (0-100% glucose at 5% intervals). From the obtained NIR spectra of the mixture in the 10 000-4000 cm(-1) region at 4 cm intervals (1501 spectral channels), a series of spectral windows consisting of 80 spectral channels was constructed, and then SNV spectra were calculated for each spectral window. Using these SNV spectra, a series of PLSR models with the first LV for glucose concentration was built. A plot of RMSE versus the spectral window position obtained using the PLSR models revealed that the 8680–8364 cm(-1) region was optimal for baseline correction using SNV. In the SNV spectra calculated using the 8680–8364 cm(-1) region (SRSNV spectra), a remarkable relative intensity change between a band due to wheat flour at 8500 cm(-1) and that due to glucose at 8364 cm(-1) was observed owing to successful baseline correction using SNV. A PLSR model with the first LV based on the SRSNV spectra yielded a determination coefficient (R2) of 0.999 and an RMSE of 0.70%, while a PLSR model with three LVs based on SNV spectra calculated in the full spectral region gave an R2 of 0.995 and an RMSE of 2.29%. Additional evaluation of SRSNV was carried out using diffuse reflection NIR spectra of marzipan and corn samples, and PLSR models based on SRSNV spectra showed good prediction results. These evaluation results indicate that SRSNV is effective in baseline correction of diffuse reflection NIR spectra and provides regression models with good prediction accuracy.

Moving-window two-dimensional heterospectral (MW2DHetero) correlation analysis and its application for the process monitoring of alcoholic fermentation

The technique of moving-window two-dimensional heterospectral (MW2DHetero) correlation spectroscopy is proposed. This computational method is based on the ideas of perturbation-correlation moving-window two-dimensional (PCMW2D) correlation spectroscopy and two-dimensional heterospectral correlation analysis. Not only small spectral variations, but also detailed bands assignments were captured using the analysis. This method was applied to near-infrared (NIR) spectra in the 10 000-4000 cm(-1) region and mid-infrared (mid-IR) spectra in the 5000-1200 cm(-1) region, which were simultaneously detected using a dual-region spectrometer. Near-infrared and mid-IR spectra collected during an alcoholic fermentation process using a solution containing glucose and fructose were reported. Slight time differences for the consumption of sugars compared with the production of ethanol were found between 50 and 150 min. It was concluded that these slight time differences are evidence for different consumption times between glucose and fructose during the fermentation process. The result proved a possibility of the selective monitoring of the simultaneous reaction processes between productive and consumptive components.