bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Heterogeneous Wheat Samples Using near Infrared Spectroscopy
Authors: Lafargue Marie E. , Feinberg Max , Daudin Jean-Jacques , Rutledge Douglas N.
Published: May 2009

An homogeneity check using Near Infrared (NIR) Spectroscopy has been developed for agricultural and agro-food samples prepared for Proficiency Testing Schemes (PTS) at Bipea. To evaluate the homogeneity among samples, the procedure involves a comparison of NIR spectra, the determination of global homogeneity criteria and the use of control charts. To study the performance of the method, “heterogeneous” wheat samples were artificially prepared and several methods tested to detect them. Wheat samples were analysed by diffuse reflection in the 10,500 to 3800 cm−1 spectral range (or 952 to 2631 nm). To detect the “heterogeneous” samples among the “homogeneous” samples, a classical outlier detection (Grubbs' test) applied to quantitative results obtained with NIR calibrations (protein and moisture contents) was first performed. A second, qualitative, approach was also used, based on the processing of the spectra with: the calculations of “standard deviation spectra” and the “difference” spectra; the application of the Grubbs' test directly on spectra; and the computations of Euclidian distances. The results confirm that the NIR technique is well adapted and outstanding for checking homogeneity among samples prepared for PTS and that the processing of the whole spectra is more efficient than simply the processing of the protein and moisture contents (obtained from NIR calibrations). “Heterogeneous” wheat samples only slightly different in their protein and moisture contents compared to “Homogeneous” wheat samples could be detected (deviation among samples down to 0.03% of protein content and 0.08% of moisture content).
Sawmill Trial of At-Line Prediction of Recovered Lumber Stiffness by NIR Spectroscopy of Pinus Radiata Cants
Authors: Meder Roger , Thumm Armin , Marston David
Published: May 2009

Pinus radiata D. Don cants (100 or 200 mm thick × 4.8 m) from a commercial sawmill operation were assessed in the green state using near infrared (NIR) spectroscopy. Near infrared spectra were acquired along the centre line of one cant face and at 50 mm offsets to one side of the centre line. The cants were ripped to produce either 50 × 100 or 50 × 200 mm rough sawn boards, which were then kiln-dried and gauged to final dimensions. The long-span modulus of elasticity ( L MoE) on each board was determined using a four-point bending test and the corresponding NIR spectra of each board (the 50 mm edge from the cant) were regressed against the long-span MoE value using partial least squares modeling. The results are explained in terms of the potential for NIR to predict the potential upgrade to higher value products for timber recovered from the corewood zone of logs.
Exploring the Use of near Infrared Reflectance Spectroscopy to Study Physical Properties and Microelements in Soils
Authors: Moron A. , Cozzolino D.
Published: May 2009

Near infrared (NIR) reflectance spectroscopy was used to predict the content of silt, sand, clay, iron (Fe), copper (Cu), manganese (Mn) and zinc (Zn) in soil. A total of 332 samples from agricultural soils (0–15 cm depth) in Uruguay (South America) were used. The samples were scanned in a monochromator instrument (NIRSystems 6500, Silver Spring, MD, USA). Two mathematical treatments (first and second derivative) with SNVD (scatter normal variate and detrend) and without scatter correction were studied. Modified partial least squares (mPLS) was used to develop the calibration models. The coefficient of determination in calibration ( R2cal) and the standard error in calibration ( SEC) using the second derivative were 0.81 ( SEC: 5.1), 0.83 ( SEC: 5.3), 0.92 ( SEC: 2.6) for percent sand, silt and clay, respectively. The R2cal and standard error of cross-validation ( SECV) were for Cu 0.87 ( SEC: 0.7), for Fe 0.92 ( SEC: 21.7), for Mn 0.72 ( SEC: 83.0) and for Zn 0.72 ( SEC: 1.2) on mg kg−1 dry matter. It was concluded that NIR reflectance spectroscopy has a great potential as an analytical method for routine analysis of soil texture, Fe, Zn and Cu due the speed and low cost of analysis.
A Guide to Raw Material Analysis Using near Infrared Spectroscopy
Authors: Kemper Mark S. , Luchetta Leza M.
Published: May 2009

In this paper, we discuss the theory and principles behind the construction and validation of near infrared (NIR) spectroscopic libraries for raw material identification and qualification. The considerations we present for raw material library construction are based on precedents that appear in the literature and upon the experience of the authors. This treatise takes a holistic approach. The development of a raw material programme is delineated in a 12-step plan that will give the reader a comprehensive perspective. The limitations of commercial NIR libraries and the advantages of customised libraries are then briefly discussed. Finally, we describe the development and validation of a small raw materials library to illustrate the principles of library construction and validation.
Performance of a Portable near Infrared Instrument for Brix Value Determination of Intact Mango Fruit
Authors: Saranwong Innapa , Sornsrivichai Jinda , Kawano Sumio
Published: May 2009

The performance of a commercially-available, portable NIR instrument “FT20” for fruit quality evaluation was investigated using mango fruits. The calibration result for the FT20 was compared with the result for the Foss NIRSystems 6500. Partial least squares (PLS) regression was used to make the calibration equations. It was found that the calibration equation using spectral data obtained with the FT20 had similar accuracy to that using Foss NIRSystems 6500 spectra. The SEPs of calibration equations were 0.40 °Brix for both instruments.
Quantitative Analysis of Hydrogen Bonding in Poly(4-Vinylphenol) Blends Using near Infrared Spectroscopy
Authors: Cai Haijun , Brisson Josée
Published: May 2009

Quantitative evaluation of hydrogen bonding of poly(4-vinyl phenol)/poly(ethylene oxide) PVPh/PEO blends was conducted using Fourier transform near infrared (FT-NIR) spectroscopy. Absorption coefficients of the free ( aF), intra- (PVPh–PVPh) ( aA) and inter-associated (PVPh–PEO) hydroxyl groups ( aI) were estimated. Two sets of approximations were tested, including adopting a least-squares refinement method to calculate absorption coefficients from all NIR spectra or using a literature value for aF. Each set of absorption coefficients thus estimated were used to determine hydroxyl concentration for the free and hydrogen-bonded hydroxyl overtone bands in the blends. A comparison is made among the resultant concentrations of the free, intra- and inter-associated hydroxyl groups. The concentration of free hydroxyl groups markedly decreases with PEO percentage, and that of intra-associated hydroxyl remains almost constant. Concentration for the inter-associated hydroxyl groups in the blends increases very slowly above 0.2 PEO weight fraction. When concentration of OH groups is reported per PVPh chain, FT-NIR measurements show a broad maximum in the number of interchain hydrogen bonds. This result can be used to explain partially previous orientation behaviour observed for PVPh/PEO blends.
Calibration and Characterisation of Imaging Spectrographs
Authors: Polder Gerrit , van der Heijden Gerie W.A.M. , Keizer L.C. Paul , Young Ian T.
Published: May 2009

Spectrograph-based spectral imaging systems provide images with a large number of contiguous spectral channels per pixel. This paper describes the calibration and characterisation of such systems. The relation between pixel position and measured wavelength has been determined using three different wavelength calibration sources. Results indicate that for spectral calibration, a source with very narrow peaks, such as a HgAr source, is preferred to narrow band filters. A third-order polynomial model gives an appropriate fit for the pixel to wavelength mapping. The signal-to-noise ratio (SNR) is determined per wavelength. In the blue part of the spectrum, the SNR is lower than in the green and red part. This is due to a decreased quantum efficiency of the sensor, a smaller transmission coefficient of the spectrograph, as well as low output power of the illuminant. Increasing the amount of blue light, using an additional fluorescent tube with a special coating considerably increases the SNR. Furthermore, the spatial and spectral resolution of the system has been determined in relation to the wavelength. These can be used to choose appropriate binning factors to decrease the image size without losing information. In our case this could reduce the image size by a factor of 60 or more.
Analysis of Contaminants in Lubricant Oil by near Infrared Spectroscopy and Interval Partial Least-Squares
Authors: Paschoal Juliana , Barboza Fernando D. , Poppi Ronei J.
Published: May 2009

The feasibility of using near infrared (NIR) transmission spectroscopy for rapid and conclusive determination of contaminants in lubricant oil was investigated. The NIR spectrum in the region from 1300 to 1700 nm was used to predict gasoline and ethylene glycol concentrations present in lubricant oil. A graphically-oriented local multivariate calibration modelling procedure called interval partial least-squares (iPLS) was applied to find variable intervals that featured the lowest prediction error. When compared with the full spectrum PLS model, better results were obtained through the iPLS program. High correlation coefficients and low root mean square errors of cross-validation ( RMSECV) were obtained for gasoline ( R = 0.98, RMSECV = 0.38%, range = 0.2–8.0% w/w) and ethylene glycol determinations ( R = 0.97, RMSECV = 0.04%, range = 0.06 to 0.7% w/w), indicating that the proposed methodology can be used for contaminant determinations in lubricant oil.
Monitoring Carotenoid and Chlorophyll Pigments in Virgin Olive Oil by Visible-Near Infrared Transmittance Spectroscopy. On-Line Application
Authors: Márquez A. Jiménez
Published: May 2009

Visible-near infrared transmittance spectroscopy was used to determine total levels of chlorophyll and carotenoid in virgin olive oil. Calibration models were developed in the laboratory using partial least squares regression. An initial smoothing followed by a first derivative treatment was the best signal correction. The validation set gave a correlation coefficient and standard error of prediction of 0.985 and 0.66 mg kg−1 for carotene totals and 0.993 and 0.96 mg kg−1 for chlorophyll totals. These partial least squares models were used to monitor on-line levels of these compounds during virgin olive oil processing in olive oil mills. The results indicate similarity between both visible-near infrared transmittance spectroscopy and reference laboratory methods.
Effect of Resolution on the Wavelength Determination of a Putative Standard to Be Used for near Infrared Diffuse Reflection Spectra Measured on Grating Spectrometers
Authors: Yang Husheng , Isaksson Tomas , Jackson Richard S. , Griffiths Peter R.
Published: May 2009

Diffuse reflection (DR) Fourier transform near infrared spectra of a powdered mixture of Er2O3, Dy2O3, Ho2O3 and talc were measured at a constant resolution of at least 2 cm−1 on four different combinations of spectrometers and sampling accessories. The wavenumber scale of each of these spectra was corrected with lines in the vibration–rotation spectrum of water vapour so that the accuracy was better than 0.02 cm−1. DR spectra of the powdered sample were then calculated at constant-wavelength resolution to simulate spectra that would have been measured on a grating monochromator. The precision and accuracy of the bands in the spectrum of this sample were then estimated. It is believed that the accuracy of the reported positions of the bands in the spectrum of this putative wavelength standard is about ten times better than the corresponding values in the DR spectrum of a mixture of Er2O3, Dy2O3 and Ho2O3 that had previously been reported by the US National Institute of Standards and Technology.
Effect of Resolution on the Wavenumber Determination of a Putative Standard to Be Used for near Infrared Diffuse Reflection Spectra Measured on Fourier Transform near Infrared Spectrometers
Authors: Yang Husheng , Isaksson Tomas , Jackson Richard S. , Griffiths Peter R.
Published: May 2009

A mixture of powdered Er2O3, Dy2O3, Ho2O3 and talc has been proposed as a wavenumber standard for near infrared (NIR) diffuse reflection (DR) measurements. Previous measurements were made at a resolution of 2 cm−1 which is significantly less than the full-width at half-height of the peaks in the spectrum. Since many NIR DR spectra are measured at a much lower resolution, some of the peaks are observed to fuse and/or shift. In this paper, the behaviour of the band positions is studied as a function of resolution. The factors that allow some of the peaks to be useful as wavenumber standards for NIR DR measurements while others should not be used are discussed. The instrument should first be calibrated with certain lines in the vibration–rotation spectrum of water vapour. Because most of the lines in the water spectrum are located less than 1 cm−1 from their nearest neighbours, only two of the 3768 lines in the region between 5750 and 7990 cm−1 can be used for calibration and only then if the spectrum is converted to its second derivative and interpolated so that there are at least five data points per resolution element and the wavenumber of maximum absorption is found by fitting the line to a quartic function. For the spectrum of the putative wavenumber standard measured at a resolution of 3–10 cm−1, the band centre is best measured after baseline correction of the spectrum with a polynomial function, while lower resolution spectra are better converted to the second derivative. As might be expected, when choosing peaks as wavenumber standards for instruments operating at different resolutions, one should avoid bands that either become fused at resolutions close to the value being used or whose position varies rapidly with resolution. Peaks should be selected that, besides being in the wavenumber range of interest, can be measured with both high precision and high accuracy.
Near Infrared Technology for Precision Environmental Measurements: Part 2. Determination of Carbon in Green Grass Tissue
Authors: Morimoto Susumu , McClure W.F. , Crowell Benett , Stanfield Donald L.
Published: May 2009

Composting is one of the most desirable techniques for reducing waste volume. To make good compost, the correct proportions of the elements carbon and nitrogen (30: 1 ratio) are important. In this paper, carbon quantification of green grass tissue using near infrared (NIR) technology was studied. Separate studies were conducted for the short-wavelength region (SWR = 700–1100 nm, a range that includes part of the visible spectrum) and long-wavelength region (LWR = 1100–2500 nm). Several spectral pretreatments (such as SNV, derivatives etc.) were implemented to optimise the stepwise multiple linear regression (SMLR) and partial least squares (PLS) calibrations. PLS analysis was conducted for all pretreatments. Results showed that the 2nd derivative of standard normal variate (SNV) pretreatment for the LWR and the SNV pretreatment for the SWR gave the best predictions. To simplify the PLS models, a weight index (WI), was defined as the absolute value of product between the regression vector from PLS analysis and the average spectrum. A simple PLS calibration was developed using selected peak wavelengths of regression vector with a minimum WI. The simple PLS models gave better results than the full PLS calibrations. According to this analysis, the C–H stretching of the first overtone at 1860 nm and the C–H stretching of the third overtone at 874 nm were the key bands for the SWR and LWR, respectively. SMLR analysis was performed on the same spectral data used in the PLS analysis. SMLR calibrations were developed using the key band chosen in PLS analysis. Although the performance of the calibrations were not as good as the PLS calibrations, the SMLR model produced acceptable calibrations for both the SWR and LWR. The simple fact that NIR technology can be used to determine both carbon and nitrogen very quickly makes it an ideal technology for monitoring material going into a composting operation.
On-Tree Evaluation of Harvesting Quality of Mango Fruit Using a Hand-Held NIR Instrument
Authors: Saranwong Innapa , Sornsrivichai Jinda , Kawano Sumio
Published: May 2009

An on-site system was established for determining the maturity of hard green mangoes that are consumed later when ripened off the tree. A hand-held near infrared (NIR) instrument operating in the short wavelength region was used for spectral acquisition. The effect of sunlight on spectra measured outdoors was described and removed. The NIR measuring system developed was used for predicting dry matter (DM) and starch content in hard green mangoes prior to harvest. On the 2D-scatter plot between predicted DM and starch content, the fully-mature hard green mangoes, with excellent eating quality when ripe, could be completely separated from the immature ones, with unacceptable eating quality when ripe. The feasibility of in vivo monitoring of internal composition changes was demonstrated. It was concluded that the NIR system was sufficiently capable of determining maturity stages of hard green mangoes on trees. The system could be used as a tool for a grower to decide a proper harvesting date that will provide high-quality fresh fruit to consumers.
Near Infrared Spectra of Pellets and Thin Films of High-Density, Low-Density and Linear Low-Density Polyethylenes and Prediction of Their Physical Properties by Multivariate Data Analysis
Authors: Sato Harumi , Shimoyama Masahiko , Kamiya Taeko , Amari Toru , Šašiç Slobodan , Ninomiya Toshio , Siesler Heinz W. , Ozaki Yukihiro
Published: May 2009

The aim of the present study is to investigate in detail the near infrared (NIR) spectra of the three types of polyethylene, linear low-density polyethylene (LLDPE), low-density polyethylene (LDPE) and high-density polyethylene (HDPE), and to develop calibration models that predict their physical properties such as density, crystallinity and melting point. The effects of spectral resolution on the classification and the prediction of density for the three types of PE have been investigated. Furthermore, the NIR spectral differences among LLDPE, LDPE and HDPE have been explored in more detail using 2 cm−1 resolution. Principal component analysis (PCA) has been performed to differentiate the 18 samples of PE. They are classified into three groups, LLDPE, LDPE and HDPE, by a score plot of the PCA Factor 1 versus 3 based on the NIR spectra pretreated by multiplicative scatter correction (MSC). The 2 cm−1 spectral resolution yields a slightly better result for the classification. Partial least squares (PLS) regression has been applied to the NIR spectra after MSC to propose calibration models that predict the density, crystallinity and melting point of HDPE, LDPE and LLDPE. The correlation coefficient for the density was calculated to be 0.9898, 0.9928, 0.9925 and 0.9872 for the spectra obtained at 2, 4, 8 and 16 cm−1 resolutions, respectively, and the root mean square error of cross validation ( RMSECV) was found to be 0.0021, 0.0018, 0.0018 and 0.0023 g cm−3, respectively. It has been found that the correlation coefficient and RMSECV for the prediction of the density and crystallinity change little with the spectral resolution. However, for the prediction of melting point, the higher resolutions (2 and 4 cm−1 resolution) provide slightly better results than the lower resolutions. NIR transmission spectra of thin films of LLDPE, LDPE and HDPE have also been investigated, and calibration models for predicting their density have been developed for the film spectra.
Near Infrared Reflectance Spectroscopy as a Tool for the Determination of Dichloromethane Extractable Matter and Moisture Content in Combed Wool Slivers
Authors: Innocenti R. , Zoccola M.
Published: May 2009

In the wool textile field the quantitative determination of solvent extractable matter and moisture content is a crucial analysis for the evaluation of combed sliver quality. The test carried out includes the acquisition of a series of data about dichloromethane soluble matter (according to the International Wool Textile Organisation—IWTO 10–01 specification), and moisture content in combed wool slivers and the search for a correlation between these data and the near infrared spectra of samples. Combed wool slivers tested were of different origins and variable mean diameters and were obtained from different combing mills in the industrial district of Biella, the principal wool textile region of Italy. The spectrophotometer used was a FT-NIR system (Perkin-Elmer Spectrum IdentiCheck). Spectra were collected in the region from 3700 to 10,000 cm−1 in reflection mode. The extraction of greasy matter from wool tops was carried out with a continuous extraction technique on a 10 g wool sample with a total extraction time of about 3 hours in a soxhlet apparatus. The results express the weight (obtained by the mean of two determinations) of the dichloromethane soluble extract as a percentage of the dry weight of the de-greased sample. For the determination of dichloromethane extractable matter, 103 samples were used for calibration. Some wool samples were deliberately under-scoured and others were re-scoured in a combing mill in order to obtain a wide range of data, ranging from 1.15% to 0.21%. Spectra were analysed using Quant+ (Perkin-Elmer Software). The best results were obtained with the PLS1 (Partial Least Square) algorithm when considering the spectral region 9000–3800 cm−1 [Standard Error of Prediction ( SEP) = 0.1042, mean value ( M) = 0.6963%, Coefficient of Determination ( R2) = 0.85]. A cross-validation was used. The determination of moisture content in combed wool sliver was performed by drying wool (80 g for a single determination) in an oven to constant weight using forced air at 105 ± 2°C. 85 samples were used for the calibration. Deliberate variations in regain were induced by exposing the wool to a dry or moist atmosphere. In this way moisture contents ranging from 9% to 15% were obtained. NIR spectra were analysed using Quant+ Software. A cross-validation was used. The best results were obtained with the Principal Component Regression algorithm when considering the spectral region 9000–3800 cm−1. A SEP of 0.4954 ( M = 11.76%) and a R2 of 0.90 were found. A limited number of determinations of grease and moisture content were carried out using the models obtained and compared with values determined manually.
Measurement of Glass Transition Temperature, Residual Heat of Reaction and Mixing Ratio of Epoxy Resins Using near Infrared Spectroscopy: A Preliminary Study
Authors: Houmøller Lars Plejdrup , Laursen Peter Clemen
Published: May 2009

As a measure of the degree of curing of epoxy resins, the glass transition temperature, Tg, and the residual heat of reaction, Δ Hr, are often used. In this study, near infrared spectroscopy and multivariate calibration [partial least squares regression (PLSR)] have been used to monitor the two variables, using differential scanning calorimetry (DSC) as the reference method. The epoxy under study was a commercial system consisting of the resin, trimethylolpropanetriglycidylether, and the hardener, 3-aminomethyl-3,5,5,-trimethylcyclohexylamine. Using samples cured under different conditions, calibrations resulted in root mean square errors of cross-validation ( RMSECV) of 18 Jg−1 for Δ Hr (range for Δ Hr: 6.1–231.3 Jg−1) and 7.2°C for Tg (range for Tg: 41.5–98.8°C). Also, a PLSR model for mixing ratio of hardener and resin was obtained, resulting in a RMSECV of 0.0040 (range for mixing ratio: 0.180–0.380).
Prediction of Viability of Oriental Beechnuts, Fagus Orientalis, Using near Infrared Spectroscopy and Partial Least Squares Regression
Authors: Soltani Ali , Lestander Torbjörn Albert , Tigabu Mulualem , Odén Per Christer
Published: May 2009

Near infrared (NIR) spectroscopy, combined with multivariate calibration, was applied for determining viable and non-viable single oriental beechnuts. Initially, samples were sorted into viable and non-viable classes with X-ray and then NIR reflectance spectra were recorded on individual nuts using a fibre-optic probe. Calibration models were developed on raw and pretreated spectra with partial least squares (PLS) regression. Multiplicative signal correction (MSC) and orthogonal signal correction (OSC) were applied to remove systematic noise in the spectra. The resulting models separated viable and non-viable nuts in the test set with 100% accuracy. Moisture was the major source of spectral variation between viable and non-viable nuts, although lipid and protein moieties were also contributing factors for the separation of the two classes. We concluded that prediction models, based on fast and non-destructive NIR spectroscopy, have a high potential for the removal of non-viable nuts within oriental beechnut lots, thereby facilitating single nut sowing in the nursery.
Multivariate Modelling of Density, Strength and Stiffness from near Infrared Spectra for Mature, Juvenile and Pith Wood of Longleaf Pine (Pinus Palustris)
Authors: Via Brian K. , Shupe Todd F. , Groom Leslie H. , Stine Michael , So Chi-Leung
Published: May 2009

In manufacturing, monitoring the mechanical properties of wood with near infrared spectroscopy (NIR) is an attractive alternative to more conventional methods. However, no attention has been given to see if models differ between juvenile and mature wood. Additionally, it would be convenient if multiple linear regression (MLR) could perform well in the place of more complicated multivariate models. Therefore, the purpose of this paper was to model the strength, stiffness and density of mature and juvenile longleaf pine to NIR spectra with MLR and principal component regression (PCR). MLR performed almost as well as PCR when predicting density, modulus of rupture (MOR) and modulus of elasticity (MOE). Choosing wavelengths associated with wood chemistry and developing principal components gave better predictive models (PCR2) than when all NIR wavelengths were used (PCR1). Models developed from mature wood did not predict wood properties from juvenile wood adequately, suggesting that separate models are needed. However, for density prediction, the area under the spectral curve appeared to be insensitive to mature and juvenile wood differences. Five of the six wavelengths associated with MOE were also associated with MOR, perhaps accounting for how MOE and MOR might be related. For pith wood, MOE and MOR were poorly related to NIR spectra, while density was strongly correlated. This inability to predict mechanical properties in the pith-wood zone warrants attention for those manufacturers interested in using near infrared to stress rate lumber within a mill.
Non-Destructive near Infrared Spectroscopic Measurement of Antique Washi Calligraphic Scrolls
Authors: Yonenobu Hitoshi , Tsuchikawa Satoru , Oda Hirotaka
Published: May 2009

Degradation of antique washi paper was examined by non-destructive near infrared spectroscopy. Difference second derivative spectra of the modern minus antique samples were analysed for the absorption peaks due to the main chemical components of washi paper, i.e. cellulose and hemicellulose. The absorption peaks were decreased for amorphous and semi-crystalline regions of cellulose and for hemicellulose, showing the results consistent with conventional, destructive sugar analysis. It is concluded that near infrared spectroscopy is a useful technique for the non-destructive monitoring of the degradation of the chemical properties of washi paper.
Selection of near Infrared Wavelengths Using Genetic Algorithms for the Determination of Seed Moisture Content
Authors: Lestander Torbjörn A. , Leardi Riccardo , Geladi Paul
Published: May 2009

For fast measurements of single seeds using near infrared (NIR) spectra for the prediction of seed moisture content, it may be necessary to reduce the spectra from over 1000 wavelengths to just a few narrow bands. This reduction makes it possible to utilise a few parallel and simultaneous NIR sensor measurements in seed sorting instead of scanning a few NIR bands that are sequential in time. Three different approaches of genetic algorithms (GA) were used to select wavelengths within the range 400–2500 nm. The GA models were compared for two different datasets: single seeds and bulk seeds of Scots pine. It was shown that GA and interval partial least squares combined with GA allowed a meaningful reduction in spectral content without any loss in predictive quality. The three models selected three to six wavelength regions mainly around the peak of the combination of the first O–H stretching overtone and the O–H bending at 1190 nm and on the slopes of the first O–H stretching overtone at 1450 nm. For some of the GA models, the selected regions were subdivided into one to three more regions. In total six to eight narrow regions were used to simulate uniform density filters based on average absorbance within selected regions. The RMSEP values of the filter simulations were of at least the same quality as those for the whole wavelength range or the NIR range. The wavelength bands chosen for the single seeds were also applied for the bulk samples and vice versa with good result. The overall results illustrate the possibility of using GAs to select wavelengths in order to build filter spectrometers based on a few wavelength bands for the determination of seed moisture content.
Detection of Honey Adulteration by Addition of Fructose and Glucose Using near Infrared Transflectance Spectroscopy
Authors: Downey Gerard , Fouratier Vanessa , Kelly J. Daniel
Published: May 2009

Samples of artisanal honey produced in Ireland over a number of harvests have been obtained directly from producers. Adulterant solutions containing both fructose and glucose at ratios of 0.7: 1, 1.2: 1 and 2.3: 1 w/w were prepared. Honeys and adulterants were adjusted to a constant solids content. Visible and near infrared (400–2498 nm) transflectance spectra of the honeys were collected before and after adulteration at levels of 7, 14 and 21% w/w of each of the fructose-plus-glucose adulterant solutions. Chemometric analysis of the spectral collection by discriminant partial least squares regression (PLS1), k-nearest neighbours ( k-NN) and soft independent modelling of class analogy (SIMCA) have been performed with a view to discriminating between the unadulterated and adulterated honey samples. Discriminant partial least squares regression proved to be the most accurate of these three methods.
Variations of Large Spectral Sets; Two-Dimensional Correlation Analysis of Loadings Spectra of Principal Component Analysis
Authors: Liu Yongliang , Barton Franklin E. , Lyon Brenda G. , Chen Yud-Ren
Published: May 2009

This work attempted to interpret the principal component loadings spectra of principal component analysis on large spectral data sets with multi-variables using two-dimensional (2D) correlation analysis. Three examples of visible/near infrared (NIR) spectra of chicken muscles under different conditions were given and discussed. 2D analysis indicated that characteristic bands from loadings spectra are in good agreement with those from a small number of spectra induced by simple external perturbations. Although some advantages of 2D correlation analysis (such as sequential changes in intensity) were not available, it might still be useful for the understanding of large and complex spectral data sets with multi component variations.
Locally-Biased Regression
Authors: Fearn Tom , Davies Anthony M.C.
Published: May 2009

After a brief review of local calibration methods, a new and relatively simple method is proposed. Given a database of calibration samples, a global calibration based on all these samples and an unknown for which we wish to make a prediction, the method selects a subset of the calibration samples judged to be spectrally similar to the unknown and uses these to determine either a skew and bias or a simple bias correction to the global calibration. Spectral similarity is defined in a two-dimensional space, with one axis focussing on similarity with respect to the analyte value to be predicted, and the other on more general spectral similarity. The computations required to make a prediction are simple by the standards of local methods.
Illustration of Failure of Continuum Models of Diffuse Reflectance
Authors: Dahm Donald J. , Dahm Kevin D.
Published: May 2009

Continuous models are widely used to model diffuse reflection from particulate samples. They are embodied in various theories, including diffusion theory, the equation of radiation transfer, and Kubelka-Munk. Using a simple system, it is shown that such models do not simultaneously predict the fractions of incident light that are transmitted directly and diffusely. Discontinuous models do have the capability to do so, but have a variety of limitations as well.
204 Years of near Infrared Technology: 1800–2003
Authors: McClure W. Fred
Published: May 2009

Near infrared spectroscopy has come of age. Today, it takes its place along side other major analytical technologies. Though it has inherent problems, its advantages make it an appealing tool for solving all sorts of analytical problems, for all sorts of samples, found in numerous fields, including food, agriculture, chemical, pharmaceuticals, textiles, polymers, cosmetics and medical—just to mention a few. Healthy, strong and still growing, NIR spectroscopy is a source of thrills and chills for many, whether from new measurement technology, chemometrics or from understanding and being able to express “old” ideas in fresher, clearer ways.a Modern NIR instruments integrate numerous technologies for determining absorbances at specific wavelengths: Monochromator, Fourier Transform, Filters [including, narrow-band interference filters, tilting filters, Acousto Optical Tunable Filters (AOTF) and Liquid Crystal Tunable Filters (LCTF)], Hadamard, Diode Emitters and Diode Arrays. Software for developing calibrations, utilising some types of classical and/or modern multivariate methods, is available with every commercial instrument. In addition, software vendors, independent of manufacturers, have designed and are marketing advanced chemometric packages for carrying out a variety of multivariate tasks, including mathematical spectral pretreatment, calibration and prediction, plus the implementation of process control statistics. The plethora of instruments and software has provided a sound basis for developing all sorts of applications throughout numerous fields. As a result, there are today more than 25,000 citations in the NIR literature and, since 1960, Medline alone has logged 2341 citations with NIR implications for the medical community, all tributes to the strength and viability of this fascinating spectroscopy. This review is a look at the big picture of NIR spectroscopy. It covers the field of NIR from the beginning to present day—204 years (1800–2003)—in six sections: Introduction, Reviews, Books, Instrumentation, Applications and Conclusions: Past, Present and Future.
On-Line Monitoring of Kinetic and Sensory Parameters in Acetic Fermentation by near Infrared Spectroscopy
Authors: Garrido-Vidal Diego , Esteban-Díez Isabel , Pérez-del-Notario Nuria , González-Sáiz José-María , Pizarro Consuelo
Published: May 2009

The application of near infrared(NIR) spectroscopy to measure simultaneously the concentration both of substrates and products of acetic fermentation, i.e. ethanol, acetic acid and biomass concentration, is reported. All these three parameters are closely involved in the kinetics of the process. Monitoring of these variables is a valuable tool to model, optimise and control industrial processes. Furthermore, the NIR technique is also applied to measure the concentrations of ethyl acetate and acetoin, two compounds of decisive relevance for the sensory characterisation of commercial vinegar. The monitoring of these compounds is fundamental to the global optimisation of the process both in economic and sensorial terms. The analysed samples were taken directly from the industrial fermentors of a vinegar producer in La Rioja and their NIR spectra were measured in order to serve as the basis for the subsequent development of separate PLS regression models for each studied response. Several pre-processing methods, such as mean centring, autoscaling, derivation, SNV, MSC and OSC were applied to the data set, testing and comparing the quality of the respective calibration models constructed. The simplest model that provided the best results in terms of predictive ability was selected for each parameter. Thus, the NIR instrument was integrated into a pilot fermentation system to monitor the concentration of ethanol, acetic acid, ethyl acetate, acetoin and biomass (critical parameters to model and optimise the industrial process) by using the proposed regression models.
Quantitative In-Line Analysis in Supercritical CO2 Using Fibre-Optic NIR Spectroscopy and Multivariate Calibration: A Potential Method for Monitoring Continuous Flow Processes
Authors: Bürck J. , Wiegand G. , Roth S. , Mathieu H. , Krämer K.
Published: May 2009

A set-up for fibre-optical in-line near infrared spectroscopic monitoring of hydrocarbons in supercritical CO2 has been developed, which can be operated under flow-through conditions. It consists of a high-pressure optical cell, which is adapted to an FT-NIR spectrometer via a fibre-optic interface. NIR spectra of squalane in supercritical CO2 have been measured for varying concentration, temperature and pressure conditions. A partial least squares (PLS) regression model was developed with a calibration set of 36 samples spanning the 0–32 × 10−3 g cm−3 squalane concentration range and with CO2 densities between 0.62–0.86 g cm−3. Based on the corresponding absorbance data in the 4900–4200 cm−1 spectral range, squalane and CO2 were modelled with standard deviations of 0.24–10−3 and 3.8 × 10−3 g cm−3, respectively. Comparable standard deviations were obtained by validating the model with independent test samples. The developed calibration models allow for the in-line quantification of both constituents under varying temperature and pressure conditions from a single spectral measurement. The results obtained encourage the use of NIR spectroscopy/PLS calibration for fast in-line analysis of continuous flow extraction processes for the deoiling of metal parts based on supercritical CO2.
Transmission Measurements on Intact Apples Moving at High Speed
Authors: McGlone V. Andrew , Martinsen Paul J.
Published: May 2009

Two different near infared spectrometric systems, both based on readily available optical components, were investigated for direct transmission mode measurements on intact apples ( Malus domestica Borkh.) moving at high speed (500 mm s−1). One system was based on the principle of time-delayed integration spectroscopy(TDIS) in which light emanating from a moving object was electronically tracked as it moved through the field of view of the spectrometer. The other system, a large aperture spectrometer (LAS), was a more conventional design in which the light from the object is accumulated in a series of one-shot measurements as the fruit progresses through the field of view. The systems were each optimally configured, using the same core optic components, to detect the low levels of light diffusely transmitted through apples between 650 and 950 nm. Performance comparisons were made in the context of dry-matter predictions; an important metric for apple quality. Modelling and validation statistics ( R2, RMSEP) for dry-matter predictions were (0.87, 0.43%) and (0.81, 0.48%) for the LAS and TDIS systems, respectively. These accuracies are excellent and similar to what is normally achievable on the more common but slower interactance-type NIR fruit measurement systems. Hence, the results have demonstrated that use of a direct transmission mode is a viable option for high-speed fruit measurement, even for a very opaque fruit like apples.
Development of Wood Property Calibrations Using near Infrared Spectra Having Different Spectral Resolutions
Authors: Schimleck Laurence R. , Stürzenbecher Reinhard , Jones P. David , Evans Robert
Published: May 2009

A range of important wood properties can be predicted using calibrations obtained using SilviScan data and diffuse reflectance near infrared (NIR) spectra collected from wooden strips cut from increment cores. The ease of NIR measurements and the rapid provision of SilviScan data provides the opportunity to establish extremely large data sets, causing calibration problems. An option is to reduce the number of data points representing an individual NIR spectrum. NIR spectra were collected in 10 mm increments from the radial longitudinal face of 89 Pinus taeda L. (loblolly pine) breast height (1.30 m) wooden strips using a Foss NIRSystems 5000 [wavelength range 1100–2498 nm, spectral sampling interval (SSI) 2 nm]. Air-dry density, microfibril angle (MFA) and stiffness calibrations were obtained using SSIs ranging from 2 to 64 nm. Calibrations developed using NIR spectra having SSIs of 4 or 8 nm performed as well as those obtained at 2 nm. As resolution was decreased (SSI increased), the quality of the calibrations associated with the various wood properties was affected to different degrees. The MFA calibration was the most affected and air-dry density the least.
Estimation of Heat Capacity and Properties of Water by Spectrum Decomposition of the Second Overtone Band of OH Stretching Vibration
Authors: Abe Hideyuki
Published: May 2009

The temperature dependency of the second overtone band assigned to an OH stretching vibration of water has been investigated by means of spectrum decomposition. The absorption bands of water and ice were decomposed into five and three Gaussian components, respectively, which were assigned to the vibration motion of molecules with a different number of hydrogen bonds. We found that the specific heat capacity of water could be explained by the extrapolated values of the heat capacity of ice and the hydrogen bonding potential calculated from our spectrum decomposition analysis. Errors for the estimation ranged from 0.1% to 1.8% in the temperature range from 273 K to 371 K. We also found that the five spectral components of water could be classified into two groups, namely strongly and weakly hydrogen-bonded groups. The temperature dependency of an equilibrium constant between these two groups suggested that a fast rotational motion of molecules in the weakly hydrogen-bonded group would be stimulated. In addition, the relationship between the average number of hydrogen bonds and the thermal properties of water in a super-cooled region suggested that the existence of the weakly hydrogen-bonded group would be an essential factor for characterising liquid water; however, the melting and freezing temperatures of water would be governed exclusively by a hydrogen-bonding condition of the strongly hydrogen-bonded group.
In-Line near Infrared Spectroscopy for Use in Product and Process Monitoring in the Food Industry
Authors: Sahni Narinder Singh , Isaksson Tomas , Næs Tormod
Published: May 2009

The article describes a case study based on implementation of in-line near infrared (NIR) spectroscopy using fibre-optic transmittance probes. This study is based on an experimental design incorporating raw materials and process variables, a split-plot design. The results show that in-line NIR spectroscopy can be used for monitoring and predicting parameters related to both the input parameters (raw materials and process variables) and the final product quality (viscosity of the product) for emulsion-based products in the food industry. However, the results are dependent on the proper choice of validation of the calibration models. The article also proposes a way to update calibration models in situations when new changes not accounted for in the calibration model are experienced.
A New Genetic Algorithm Applied to the near Infrared Analysis of Gasolines
Authors: Boschetti Carlos E. , Olivieri Alejandro C.
Published: May 2009

A new genetic algorithm is presented for sensor selection, in order to predict the octane number and the content of benzene, toluene and total aromatics in gasolines, based on partial least squares multivariate calibration of near infrared spectral data. The algorithm separately labels each of the selected wavenumber ranges with a relative inclusion ranking. Relative prediction errors (% of root mean square error with respect to the mean calibration value) achieved after sensor selection are: octane number, 0.5%, benzene, 0.6%, toluene, 0.6%, and total aromatics, 1.1%. The results are compared with those provided by the spark-ignition engine fuel research method for octane number and by gas chromatography for the remaining parameters.
Least-Squares Support Vector Machines for Chemometrics: An Introduction and Evaluation
Authors: Cogdill R.P. , Dardenne P.
Published: May 2009

Support vector machines (SVM) are a relatively new technique for modelling multivariate, non-linear systems, which is rapidly gaining acceptance in many fields. There has been very little application or understanding of SVM methodology in chemometrics. The objectives of this paper are to introduce and explain SVM regression in a manner that will be familiar to the NIR and chemometrics community, and provide some practical comparisons between least-squares SVM regression and more traditional methods of multivariate data analysis. Least squares support vector machines (LS-SVM) were compared to partial least squares (PLS), LOCAL and artificial neural networks (ANN) for regression and classification using four, diverse datasets. LS-SVM was shown to be the most effective algorithm, and required the lowest number of calibration samples to achieve superior predictive performance.
Removal of Hydrogen Bonding Interferences in the near Infrared Spectroscopic Determination of Dicarboxylic Acids in Diols
Authors: Taylor Alan , McCabe Richard W.
Published: May 2009

Although several NIR spectroscopic methods exist for following the synthesis of polyesters, they are all used at the reaction temperature of between 240 and 260°C where reaction still proceeds, they also employ near equimolar concentrations of diacids and diols. A poor correlation, however, is obtained when analysing dilute diacid solutions in diols, this is attributed to hydrogen bonding between the carboxyl and hydroxyl groups. The removal of hydrogen bonding by addition of chloroform to the solution gave excellent correlation of the absorbance of the second overtone carbonyl bands with acid concentration.
Prediction of Colour and pH in Grapes Using a Diode Array Spectrophotometer (400–1100 nm)
Authors: Cozzolino D. , Esler M.B. , Dambergs R.G. , Cynkar W.U. , Boehm D.R. , Francis I.L. , Gishen M.
Published: May 2009

One hundred and twenty thawed samples of homogenised and whole frozen grape berries were analysed using a diode array spectrophotometer (400–1100 nm) (CORONA 45VISNIR, Carl Zeiss, Germany). The spectra and the analytical data were used to develop partial least squares calibrations to predict colour and pH in both presentation modes to the instrument. The visible (vis: 400–700 nm), near infrared (NIR: 700–1100 nm) and vis + NIR (400–1100 nm) regions were used to perform the calibrations. Cross validation models for colour and pH on homogenised samples gave a coefficient of determination in validation ( R2val) and the root mean square error of cross-validation ( RMSECV) of 0.92 and 0.07 mg g−1 for colour, and 0.90 and 0.04 for pH, respectively, using the vis region. Presentation of intact whole grape berries gave R2val and RMSECV values of 0.50 and 0.14 mg g−1 for colour, 0.60 and 0.08 for pH using the NIR region. It was concluded that homogenised samples gave the best calibration statistics. More research needs to be done to improve calibration on whole samples if the technology is to be used for rapid analysis for either on-farm or on-harvester applications.