Short-wavelength Near-infrared Research Articles

Non-destructive prediction of translucent flesh disorder in intact mangosteen by short wavelength near infrared spectroscopy

A non-destructive measurement and data evaluation technique to predict an internal translucent flesh disorder in intact mangosteen fruit is proposed by using short wavelength near infrared (SW-NIR) transmittance spectroscopy. The optimum conditions of measurement were investigated for spectra acquisition at an integration time of 78 ms with a 200 W light source. The NIR absorption spectra of 193 mangosteen samples were obtained in the wavelength range from 640 to 980 nm on four sides of each sample. The best result from a discriminant analysis for leave-one-out cross-validation was 92.0% classification accuracy. The results showed that the hardening pericarp disorder influenced the accuracy of the classification. This study demonstrates that SW-NIR spectroscopy can be used to accurately predict translucent flesh disorder in intact mangosteens.

Non-destructive determination of metronidazole powder by using artificial neural networks on short-wavelength NIR spectroscopy

The present study aimed at providing a new method in sight into short-wavelength near-infrared (NIR) spectroscopy of in pharmaceutical quantitative analysis. To do that, 124 experimental samples of metronidazole powder were analyzed using artificial neural networks (ANNs) in the 780–1100 nm region of short-wavelength NIR spectra. In this paper, metronidazole was as active component and other two components (magnesium stearate and starch) were as excipients. Different preprocessing spectral data (first-derivative, second-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC)) were applied to establish the ANNs models of metronidazole powder. The degree of approximation, a new evaluation criterion of the networks was employed to prove the accuracy of the predicted results. The results presented here demonstrate that the short-wavelength NIR region is promising for the fast and reliable determination of major component in pharmaceutical analysis.

In-Line Monitoring of Several Pilot Scale Catalytic Reforming Units Using a Short-Wavelength near Infrared Analyser

This paper reports a novel application of in-line, short wavelength, near infrared (SW-NIR) spectroscopy to monitor eight pilot scale reforming units, for real-time determination of research octane number (RON) and aromatic compositions (benzene, toluene, xylene and total aromatics) of reforming gasoline, by an on-line SW-NIR system constructed by ourselves. Robust partial least squares calibration models for sample composition and measurement conditions were built using a global calibration set including off-line and in-line samples. Prediction results of the global models, over a six month period, for the eight units show excellent correlation with the corresponding reference data. The spectral pretreatment method of mean sample residual spectrum correction was used to remove spectral difference among multi-channels caused by small coupling differences among fibres and the multiplexer in the analyser. The prediction statistics showed consistency among the eight channels without any systematic errors. The applications of the NIR analyser can rapidly reflect the state of the process at a given time without any operator intervention. Moreover, the high stability and ruggedness of the CCD array-based on-line instrumentation guarantees easy and reliable operation.

Bruise detection in Pacific pink salmon (Oncorhynchus gorbuscha) by visible and short-wavelength near-infrared (SW-NIR) spectroscopy (600-1100 nm).

Visible and short-wavelength near-infrared (SW-NIR) spectroscopy (600-1100 nm) was used to detect bruises in intact, whole Pacific pink salmon (Oncorhynchus gorbuscha). The measurements were performed noninvasively through the skin and scales in the diffuse reflectance mode. Digital images of bruised and nonbruised regions of fish were captured after the fish samples were filleted. Image analysis was conducted using Adobe Photoshop 7.0 with relative gray values used as reference values in a partial least-squares (PLS) model. A PLS cross-validation model using six latent variables yielded a standard error of prediction (SEP = 0.05%, R = 0.83). Approximately 84% of all nonbruised spectra were correctly classified, whereas approximately 81% of all bruised spectra were correctly classified. These results suggest that visible and SW-NIR could be used to control the bruise defect of fish products during processing, thereby improving product consistency and quality.

Predicting sodium chloride content in commercial king ( Oncorhynchus tshawytscha) and chum ( O. keta) hot smoked salmon fillet portions by short-wavelength near-infrared (SW-NIR) spectroscopy

Partial least square (PLS) based short-wavelength near-infrared (SW-NIR) prediction models for salt content in commercial hot smoked fillet portions of king or Chinook ( Oncorhynchus tshawytscha) ( N=140; 212–468 g) and chum ( O. keta) salmon ( N=120; 137–356 g) were developed. Spectra were collected in the diffuse reflectance mode (600–1100 nm). The total salt content ranged from 1.66 to 5.95% w/w for king and 2.15 to 5.69% w/w for chum salmon. The moisture ranged from 50.7 to 71.6% w/w for king and 55.5 to 69.7% w/w for chum salmon. An optimal PLS model for salt required eight latent variables for king salmon ( R 2=0.83, SEP=0.32% w/w) and eight latent variables for chum salmon ( R 2=0.82, SEP=0.25% w/w).

Nondestructive Prediction of Moisture and Sodium Chloride in Cold Smoked Atlantic Salmon (Salmo salar)

ABSTRACT: Salt and moisture contents in cold‐smoked salmon were determined using short‐wavelength near‐infrared (SW‐NIR) reflectance spectroscopy (600 to 1100 nm). Partial least square (PLS) regression models yielded the best results among 3 linear regression methods tested. Back‐propagation neural networks (BPNN) exhibited a somewhat better capability to model salt and moisture concentrations (Salt: R2= 0.824, RMS = 0.55; Moisture: R2= 0.946, RMS = 2.44) than PLS (Salt: R2= 0.775, RMS = 0.63; Moisture: R2= 0.936, RMS = 2.65). Selection of samples from different axial locations on a fish did not affect the prediction error for salt or WPS but affected the prediction error for moisture.

Detection of sodium chloride in cured salmon roe by SW-NIR spectroscopy.

Salt and moisture content of cured salmon roe (ikura) was determined using short-wavelength-near-infrared (SW-NIR) reflectance spectroscopy (600-1100 nm). SW-NIR can be used to measure chloride species. Calibrations for salt in bulk samples of high-quality roe (R(2) = 0.904, SEP = 0.421%, RPD = 3.21) and average-quality roe (R(2) = 0.711, SEP = 1.13%, RPD = 1.81), crushed eggs (R(2) = 0.857, SEP = 0.509%, RPD = 2.62), and individual eggs (R(2) = 0.731, SEP = 0.698%, RPD = 1.98) were developed using partial least squares (PLS) regression models. The heterogeneous distribution of lipid and moisture in the individual eggs limit the sensitivity of this method; however, this method provides a rapid nondestructive method for high-value food products where destructive testing is expensive or impractical and for process control applications.

Estimating reaction rate constants from a two-step reaction: a comparison between two-way and three-way methods

In this paper, two different spectral datasets are used in order to estimate reaction rate constants using different algorithms. Dataset 1 consists of short-wavelength near-infrared (SW-NIR) spectra taken in time of the two-step epoxidation of 2,5-di-tert-butyl-1,4-benzoquinone using tert-butyl hydroperoxide and Triton B catalyst. This dataset showed moderate reproducibility. Dataset 2 consists of UV-VIS recorded spectra of the consecutive reaction of 3-chlorophenylhydrazonopropane dinitrile with 2-mercaptoethanol. This dataset showed good reproducibility. Two-way and three-way methods were used in order to estimate the reaction rate constants for both datasets. For the SW-NIR dataset the lowest standard deviations for the reaction rate constants were obtained with a two-way method. The lowest standard deviations for the reaction rate constant estimates for the UV-VIS dataset were obtained with a two-way method which uses spectral information that is known in advance. In this case the pure spectrum of two reacting absorbing species is known in advance and this information was used by the two-way method. For one two-way method and a few three-way methods which do not use spectral information that is known in advance, pure spectra of the reacting absorbing species of the UV-VIS dataset were estimated which showed excellent agreement with the recorded pure spectra. The pure spectra of the reacting absorbing species for the SW-NIR dataset were not estimated, because it was not possible to record the real pure spectra of these species. For both spectral datasets, quality assessment has been performed using a jackknife method. Copyright © 2000 John Wiley & Sons, Ltd.

Estimating reaction rate constants from a two-step reaction: a comparison between two-way and three-way methods

In this paper, two different spectral datasets are used in order to estimate reaction rate constants using different algorithms. Dataset 1 consists of short-wavelength near-infrared (SW-NIR) spectra taken in time of the two-step epoxidation of 2,5-di-tert-butyl-1,4-benzoquinone using tert-butyl hydroperoxide and Triton B catalyst. This dataset showed moderate reproducibility. Dataset 2 consists of UV-VIS recorded spectra of the consecutive reaction of 3-chlorophenylhydrazonopropane dinitrile with 2-mercaptoethanol. This dataset showed good reproducibility. Two-way and three-way methods were used in order to estimate the reaction rate constants for both datasets. For the SW-NIR dataset the lowest standard deviations for the reaction rate constants were obtained with a two-way method. The lowest standard deviations for the reaction rate constant estimates for the UV-VIS dataset were obtained with a two-way method which uses spectral information that is known in advance. In this case the pure spectrum of two reacting absorbing species is known in advance and this information was used by the two-way method. For one two-way method and a few three-way methods which do not use spectral information that is known in advance, pure spectra of the reacting absorbing species of the UV-VIS dataset were estimated which showed excellent agreement with the recorded pure spectra. The pure spectra of the reacting absorbing species for the SW-NIR dataset were not estimated, because it was not possible to record the real pure spectra of these species. For both spectral datasets, quality assessment has been performed using a jackknife method. Copyright © 2000 John Wiley & Sons, Ltd.

Rapid estimation of rate constants using on-line SW-NIR and trilinear models

In this paper, two algorithms are presented to estimate reaction rate constants from on-line short-wavelength near-infrared (SW-NIR) measurements. These can be applied in cases where the contribution of the different species in the mixture spectra is of exponentially decaying character. From a single two-dimensional dataset two two-way datasets are formed by splitting the original dataset such that there is a constant time lag between the two two-way datasets. Next, a trilinear structure is formed by stacking these two two-way datasets into a three-way array. In the first algorithm, based on the generalized rank annihilation method (GRAM), the trilinear structure is decomposed by solving a generalized eigenvalue problem (GEP). Because GRAM is sensitive to noise it leads to rough estimations of reaction rate constants. The second algorithm (LM–PAR) is an iterative algorithm, which consists of a combination of the Levenberg–Marquardt algorithm and alternating least squares steps of the parallel factor analysis (PARAFAC) model using the GRAM results as initial values. Simulations and an application to a real dataset showed that both algorithms can be applied to estimate reaction rate constants in case of extreme spectral overlap of different species involved in the reacting system.

Effects of ultraviolet exposure and near infrared laser tweezers on human spermatozoa.

Photostress has to be considered during optical micromanipulation of gametes. Ultraviolet light, including low-energy UVA (32-400 nm) radiation, as well as high-intensity near infrared (NIR) laser radiation may induce cell damage. A total number of 580 light-exposed sperm cells were studied in single-cell photostress experiments. Low-power (1.5 mW, 5.3 W/cm2) UVA exposure with 365 nm radiation of a standard mercury microscopy lamp to human spermatozoa resulted within 109 +/- 30 s in paralysis and within 310 +/- 110 s in cell death. Cytotoxic effects during cell manipulation with laser microbeams were found to be partly based on non-linear excitation phenomena, in particular two-photon absorption by endogenous cell chromophores. Two-photon absorption will be more intense in the case of pulsed laser microradiation, but occur also during micromanipulation with highly focused continuous wave (cw) microbeams used as laser tweezers ('optical traps'). In particular, short-wavelength NIR traps < 800 nm induce UVA-like biological effects (oxidative stress). For example, sperm trapping with 760 nm microbeams resulted in UVA-like autofluorescence modifications, paralysis within 35 +/- 20 s and cell death within 65 +/- 20 s. In contrast, laser microbeams at 800-1064 nm may act as relatively safe micromanipulation tools. In most optical traps multifrequency cw lasers are employed. Radiation of these lasers can magnify cytotoxic effects. Therefore, single-frequency laser operation should be preferred. In general, laser assisted cell micromanipulation requires a new understanding of microbeam-cell interaction, including aspects of non-linear optics.

A Brief Review of near Infrared in Petroleum Product Analysis

The use of infrared spectroscopy [including near infrared (NIR) spectroscopy] for the analysis of petroleum product analysis has become an essential component of hydrocarbon processing and refining since the mid-1940s. Early scientific literature identified absorption band positions for a variety of hydrocarbon functional groups from pure compounds to complex mixtures. The short wavelength NIR region (generally designated as 750–1100 nm), and the long-wavelength NIR region (1100–2500 nm) have been explored for their relative chemical information content with respect to hydrocarbon fuel mixtures. The functional groups of methyl, methylene, carbon–carbon, carbon–oxygen (including carbonyl), and aromatic (C–H) are measured directly using NIR spectroscopy. NIR spectroscopy combined with multivariate calibration has resulted in the reported analysis of numerous fuel components. The scientific literature has reported varied success for the measurement of RON (research octane number), MON (motor octane number), PON (pump octane number), cetane, cloud point, MTBE ( tert-Butyl methyl ether), RVP (Reid vapour pressure), ethanol, API, bromine number, lead, sulphur, aromatics, olefins and saturates content in such products as gasoline, diesel fuels, and jet fuels. This review paper summarises the foundational work using near-infrared for hydrocarbon fuels measurement beginning in 1938.

Noninvasive short-wavelength near-infrared spectroscopic method to estimate the crude lipid content in the muscle of intact rainbow trout

Short-wavelength near-infrared (SW-NIR) spectroscopy (700-1100 nm) was used to predict the crude lipid content of intact, whole rainbow trout (weight range 66.5-883 g). The measurements were performed noninvasively and in the diffuse reflectance mode by conveying the light to the intact, whole fish over an optical fiber bundle. The backscattered light was collected by a second fiber bundle, concentric to the first, and focused onto the entrance slit of the monochromator