Takuma Genkawa

Two-Dimensional Heterospectral Correlation Analysis of Water and Liquid Oleic Acid Using an Online Near-Infrared/Mid-Infrared Dual-Region Spectrometer:

Two-dimensional (2D) near-infrared (NIR) and mid-infrared (mid-IR) heterospectral correlation analyses were used to characterize temperature-dependent spectral variations of water and liquid oleic acid (OA), utilizing a dataset obtained with an online NIR/mid-IR dual-region spectrometer. The spectrometer facilitated sequential acquisition of both NIR (10000–4000 cm−1) and mid-IR (5000–1200 cm−1) spectra, which compose the spectral dataset required for 2D NIR/mid-IR heterospectral correlation analysis. Both NIR and mid-IR spectra were obtained under the same conditions by using the same sample compartment, more quickly and easily than is possible when using existing spectrometers. Successful 2D NIR/mid-IR correlation analysis was performed with the data collected with this instrument to characterize the temperature dependence of the molecular structures of water and pure liquid OA. Temperature-induced NIR/mid-IR spectral changes for water and OA were analyzed in detail, and band assignments in the NIR and mid-IR regions were elucidated by 2D NIR/mid-IR heterospectral correlation analysis. The results of this study indicate that liquid water consists of two major species, strongly hydrogen-bonded species and weakly hydrogen-bonded species, as well as one minor species. Additionally, OA was found to form an intermolecularly hydrogen-bonded species in which a single hydrogen bond of the dimer was broken; a mid-IR band at 1724 cm−1 was assigned to this species. Moreover, 2D NIR/mid-IR heterospectral correlation analysis revealed that NIR bands at 4690 and 4644 cm−1 also arose from intermolecularly hydrogen-bonded species. These results demonstrate that 2D NIR/mid-IR heterospectral correlation analysis is useful not only for NIR band assignments, but also for molecular structure studies. The spectrometer we developed makes this analysis even more accessible.

Development of a near-infrared/mid-infrared dual-region spectrometer for online process analysis.

A near-infrared (NIR) and mid-infrared (mid-IR) dual-region spectrometer having two immersion probes, a transmission probe for NIR, and an attenuated total reflection (ATR) probe for mid-IR has been developed for highly reliable process monitoring and deep process understanding. This spectrometer facilitates sequential acquisition of both NIR (10 000–4000 cm−1) and mid-IR (5000–1200 cm−1) spectra by switching the light path leading to the probes without the need for probe replacement. The use of a single light source and a single beam splitter enables achievement of a permanent alignment of the optical system and sequential data acquisition. The transmission NIR and ATR mid-IR probes designed and developed in the present study facilitate the acquisition of NIR/mid-IR spectra with optimized absorption intensities in both regions by simply placing the probes into a sample solution. The performance of the developed spectrometer was demonstrated in monitoring the ethanol fermentation process. NIR/mid-IR spectra of the fermentation solution with multiplicative scatter correction (MSC) represent the relative changes in the concentrations of glucose and ethanol in both regions. Principal component analysis (PCA) was performed on the MSC-treated spectra in the regions 6300–5650 cm−1, 4850–4300 cm−1, and 3500–2880 cm−1 to detect the end-point of the fermentation as an example of process monitoring. For all the regions, the score plot of the first principal component (PC) indicates that the fermentation progresses with the fermentation time and stops after 210 minutes and thus the end-point of the fermentation exists at around 210 minutes. The loading plot indicates that all of the first PCs are the relative changes in the concentrations of glucose and ethanol. This result reveals that the same chemical changes are observed in both transmission NIR and ATR mid-IR spectra. Multiple and simultaneous analysis was also performed, and intensity change in light scattering relating the growth of yeasts was monitored by the NIR spectra.

Feasibility study of diffuse reflectance and transmittance near infrared spectroscopy for rapid analysis of ascorbic acid concentration in bilayer tablets using a high-speed polychromator-type spectrometer

The feasibility of real-time release testing of bilayer tablets was investigated using near infrared (NIR) spectroscopy. The newly developed polychromator-type NIR spectrometer was used to compare the diffuse reflectance (DR) and transmittance (Tr) NIR spectroscopic techniques. This spectrometer not only performs highly sensitive NIR measurements but also yields the NIR spectra of an intact tablet on a millisecond (ms) timescale; i.e. 500 ms for the DR-NIR measurements and 400 ms for the Tr-NIR measurements. The bilayer tablets were prepared with the first layer comprising 0–10% ascorbic acid (AsA), 20% corn starch, 5% talc, 30% microcrystalline cellulose and 45–35% lactose, and the second layer comprising 20% corn starch, 5% talc, 30% microcrystalline cellulose and 45% lactose; their DR-and Tr-NIR spectra were acquired from both sides of the tablet. With these spectra, the feasibility of DR- and Tr-NIR spectroscopy for the quantitative analysis of AsA in the bilayer tablets was compared. The DR- and Tr-NIR spectra of the bilayer tablets and their second-derivative spectra were studied. The AsA bands were not identified in the DR- and Tr-NIR spectra. However, the AsA bands at 995 nm and 1458 nm were observed in the second-derivative spectra. All the developed regression models predicted the AsA concentration, and regression vectors indicated that the prediction was based on the AsA bands. In addition, the model using the Tr-NIR spectra was able to predict the AsA concentration, even when the bilayer tablet was flipped.

Unveiling the Aggregation of Lycopene in Vitro and in Vivo: UV–Vis, Resonance Raman, and Raman Imaging Studies

The present study investigates the structure of lycopene aggregates both in vitro and in vivo using ultraviolet-visible (UV-vis) and Raman spectroscopies. The electronic absorption bands of the J- and H-aggregates in vitro shift to lower and higher energies, respectively, compared to that of the lycopene monomer. Along with these results, the frequencies of the ν1 Raman bands were shifted to lower and higher frequencies, respectively. By plotting the frequencies of the ν1 Raman band against the S0 → S2 transition energy, a linear relationship between the data set with different aggregation conformations can be obtained. Therefore, the band positions depending on the different conformations can be explained based on the idea that the effective conjugated C═C chain lengths within lycopene molecules are different due to the environmental effect (site-shift effect) caused by the aggregation conformation. Applying this knowledge to the in vivo measurement of a tomato fruit sample, the relationship between the aggregation conformation of lycopene and the spectral patterns observed in the UV-vis as well as Raman spectra in different parts of tomato fruits was discussed in detail. The results showed that the concentration of lycopene (particularly that of the J-aggregate) specifically increased, whereas that of chlorophyll decreased, with ripening. Furthermore, Raman imaging indicated that lycopene with different aggregate conformations was distributed inhomogeneously, even within one sample. The layer formation in tomato tissues with high concentrations of J- and H-aggregates was successfully visualized. In this manner, the presence of lycopene distributions with different aggregate conformations was unveiled in vivo.

A polychromator-type near-infrared spectrometer with a high-sensitivity and high-resolution photodiode array detector for pharmaceutical process monitoring on the millisecond time scale

In the fine chemicals industry, particularly in the pharmaceutical industry, advanced sensing technologies have recently begun being incorporated into the process line in order to improve safety and quality in accordance with process analytical technology. For estimating the quality of powders without preparation during drug formulation, near-infrared (NIR) spectroscopy has been considered the most promising sensing approach. In this study, we have developed a compact polychromator-type NIR spectrometer equipped with a photodiode (PD) array detector. This detector is consisting of 640 InGaAs-PD elements with 20-μm pitch. Some high-specification spectrometers, which use InGaAs-PD with 512 elements, have a wavelength resolution of about 1.56 nm when covering 900-1700 nm range. On the other hand, the newly developed detector, having the PD with one of the worlds highest density, enables wavelength resolution of below 1.25 nm. Moreover, thanks to the combination with a highly integrated charge amplifier array circuit, measurement speed of the detector is higher by two orders than that of existing PD array detectors. The developed spectrometer is small (120 mm × 220 mm × 200 mm) and light (6 kg), and it contains various key devices including the high-density and high-sensitivity PD array detector, NIR technology, and spectroscopy technology for a spectroscopic analyzer that has the required detection mechanism and high sensitivity for powder measurement, as well as a high-speed measuring function for blenders. Moreover, we have evaluated the characteristics of the developed NIR spectrometer, and the measurement of powder samples confirmed that it has high functionality.

Simple and rapid determination of free fatty acids in brown rice by FTIR spectroscopy in conjunction with a second-derivative treatment.

A simple and rapid method for the determination of free fatty acid (FFA) content in brown rice using Fourier transform infrared spectroscopy (FTIR) in conjunction with second-derivative treatment was proposed. Ground brown rice (10g) was soaked in toluene (20mL) for 30min, and the filtrate of the extract was placed in a 1mm CaF2 liquid cell. The transmittance spectrum of the filtrate was recorded using toluene for the background spectrum. The absorption band due to the CO stretching mode of FFAs was detected at 1710cm(-1), and the Savitzky-Golay second-derivative treatment was performed for band separation. A single linear regression model for FFA was developed using the 1710cm(-1) band in the second-derivative spectra of oleic acid in toluene (0.25-2.50gL(-1)), and the model displayed high prediction accuracy with a determination coefficient of 0.998 and a root mean square error of 0.03gL(-1).

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.

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.

Image Monitoring of Pharmaceutical Blending Processes and the Determination of an End Point by Using a Portable Near-Infrared Imaging Device Based on a Polychromator-Type Near-Infrared Spectrometer with a High-speed and High-Resolution Photo Diode Array Detector

In the present study we have developed a new version (ND-NIRs) of a polychromator-type near-infrared (NIR) spectrometer with a high-resolution photo diode array detector, which we built before (D-NIRs). The new version has four 5 W halogen lamps compared with the three lamps for the older version. The new version also has a condenser lens with a shorter focal point length. The increase in the number of the lamps and the shortening of the focal point of the condenser lens realize high signal-to-noise ratio and high-speed NIR imaging measurement. By using the ND-NIRs we carried out the in-line monitoring of pharmaceutical blending and determined an end point of the blending process. Moreover, to determinate a more accurate end point, a NIR image of the blending sample was acquired by means of a portable NIR imaging device based on ND-NIRs. The imaging result has demonstrated that the mixing time of 8 min is enough for homogeneous mixing. In this way the present study has demonstrated that ND-NIRs and the imaging system based on a ND-NIRs hold considerable promise for process analysis.

Use of the product of mean intensity ratio (PMIR) technique for discriminant analysis of lycopene-rich vegetable juice using a portable NIR-excited Raman spectrometer

In this study, a lycopene-content-based discriminant analysis was performed using a portable near-infrared-excited Raman spectrometer. In the vegetable-juice Raman spectra, the peak intensity of the lycopene band increased with increasing lycopene concentration, but scattering decreased the repeatability of the peak intensity. Consequently, developing a lycopene-concentration regression model using peak intensity is not straightforward. Therefore, a new method known as the product of mean intensity ratio (PMIR) analysis was developed to rapidly identify lycopene-rich samples on-site. In the PMIR analysis, Raman spectra are measured with short exposure times, confirming only the peaks of carotenoids with high concentrations, and thus the lycopene concentrations of vegetable juice samples could be determined successfully. Exposure times of 20ms and 100ms could detect lycopene concentrations of ≥5mg/100g and ≥2mg/100g with 93.2% and 97.7% accuracy, respectively; thus, lycopene-content-based discriminant analysis using the PMIR and a portable Raman spectrometer is feasible.