bluuebunny/crossref_metadata_2025 huggingface dataset:
Near Infrared Spectroscopic Determination of Alcohols—Solving Non-Linearity with Linear and Non-Linear Methods
Authors: Li Yue , Brown Chris W. , Lo Su-Chin
Published: May 2009

The concentrations of methanol and ethanol in carbon tetrachloride solutions have been determined using near infrared (NIR) spectra in the region between 1100 and 2500 nm. Spectral non-linearities due to the effects of concentration and temperature on hydrogen bonding were observed. The feasibility of obtaining accurate predictions of MeOH concentrations was assessed by applying multilinear regression (MLR) techniques, full spectra statistical methods and artificial neural networks (ANN) to their NIR spectra. Principal Component Regression (PCR), Partial Least Squares (PLS) and ANN produced calibration models with decreasing relative standard errors of prediction ( RSEP) of 0.02%, 0.012% and 0.008%, respectively, compared with MLR methods based on selected wavelengths which yielded a RSEP of 0.04%. Modelling of ethanol spectra gave similar results. We conclude that using full spectra chemometric techniques and ANN methods can accurately predict alcohol concentrations in spite of non-linearities.
An Investigation into the Determination of the Maturity of Pawpaws (Carica Papaya) from NIR Transmission Spectra
Authors: Greensill C.V. , Newman D.S.
Published: May 2009

The transmission spectra for pawpaws ( Carica papaya) in various states of maturity ranging from immature green through to skin colour break were recorded over the wavelength range 500–1000 nm using a dual prism spectrometer with charge-coupled device detector designed and constructed at the authors' institute. Features observed in the spectra were compared against the visually-assessed maturity of the fruit to investigate spectral changes associated with the ripening process. An apparent spectral signature of maturity was noted with a distinct change in the relationship of wavelength of peak transmissions at 720 nm to 815 nm between the immature green and ripe fruit, respectively. These results will allow the level of maturity of pawpaws to be classified into at least four categories using only these wavelengths with the possibility of using a small portable instrument.
Use of Mean Square Prediction Error Analysis and Reproducibility Measures to Study near Infrared Calibration Equation Performance
Authors: Dhanoa M.S. , Lister S.J. , France J. , Barnes R.J.
Published: May 2009

Monitoring of calibration equation performance is essential if high quality of predicted analytical data is to be sustained. In this paper we outline and illustrate the use of some statistical methods which are well suited for post-prediction data scrutiny. Mean square prediction error is partitioned into three components, viz. mean bias, systematic bias and random error. Reproducibility measures such as concordance correlation ( rc), intraclass correlation ( r2) and correlation between difference and sum ( r(X – Y)(X + Y)) are also discussed. Other topics discussed include the maximisation of R2, type II regression (both variables with error model) and new graphical displays.
Chemometric Processing of Visible and near Infrared Reflectance Spectra for Species Identification in Selected Raw Homogenised Meats
Authors: McElhinney John , Downey Gerard , Fearn Tom
Published: May 2009

Visible and near infrared reflectance spectra (400–2498 nm) of 230 homogenised meat samples (chicken, turkey, pork, beef and lamb) were collected. Classification of the spectra into individual species was attempted using factorial discriminant analysis (FDA), soft independent modelling of class analogy (SIMCA), K-nearest neighbour analysis and discriminant partial least squares (PLS) regression. A variety of wavelength ranges and data pre-treatments were investigated for optimum accuracy. Particular difficulty was encountered in distinguishing between chicken and turkey; models were, therefore, initially developed using five separate meat classes and again using four groups, with chicken and turkey being amalgamated into a single class. In a four-group classification, the best models produced between 85 and 100% correct identifications. Using five groups, classification rates were generally lower. FDA and PLS discrimination generally produced the best accuracy rates. SIMCA exhibited the poorest classification performance.
Optical Matching of near Infrared Reflectance Monochromator Instruments for the Analysis of Ground and Whole Wheat
Authors: Osborne B.G. , Kotwal Z. , Wesley I.J. , Saunders L. , Dardenne P. , Shenk J.S.
Published: May 2009

Eight near infrared (NIR) reflectance monochromator instruments in Australia have been optically matched (standardised) in order that reflectance spectra can be obtained when the same sample is measured on any of the instruments which are as similar as reflectance spectra obtained by re-packing the same sample on one instrument. This means that data from the different instruments can be merged to produce calibrations based on a larger number of more diverse samples than would be available to any one laboratory, without the need for the actual samples to be moved around the country. In turn, the resulting spectral library and calibrations can be shared. Two methods of standardisation of this type of instrument have been previously reported for ground samples. One method utilises 30 sealed powdered samples of diverse types in order to correct for both slope and bias while the other requires only a single sealed sample to correct for bias. The results of standardisation, using the set of 30 samples and using a single ground wheat, confirms that the single sample standardisation works as well as that performed using the 30 samples. In addition, an extension of the single sample method using whole grain samples is reported. The results confirm that the single sample method can be successfully used to optically match NIR reflectance monochromator instruments of the same brand.
Near Infrared Reflectance Spectroscopy for the Analysis of Agricultural Soils
Authors: Reeves J.B. , McCarty G.W. , Meisinger J.J.
Published: May 2009

The objective of this work was to investigate the usefulness of near infrared (NIR) reflectance spectroscopy in determining: (i) various constituents (total N, total C, active N, biomass and mineralisable N, and pH), (ii) parameters (soil source, depth from which sample was obtained, type of tillage used) and (iii) rate of application of NH4NO3 fertiliser) of low organic matter soils. A NIRSystems model 6250 spectrometer was used to scan soil samples ( n = 179) obtained from experimental plots at two locations with three replicate plots under plow and no till practices at each location with three rates of NH4NO3 for each plot (2 × 3 × 2 × 3). For each of these, samples were taken from five depths for a total of 2 × 3 × 2 × 3 × 5 or 180 samples (one sample lost). The results demonstrated that NIR reflectance spectroscopy can be successfully used to determine some compositional parameters of low organic matter soils (particularly total C and total N). It is also apparent that for non-biological parameters (excluding soil type as reflected by source) such as the depth from which the sample was obtained, the rate of application of NH4NO3 fertiliser and the form of tillage used, that NIR reflectance spectroscopy is not very useful, unless a very limited set of samples is used (i.e. single tillage and location). For other determinations, such as pH, biomass N and active N, the results may be useful depending on the exact needs in question. Finally, from the results presented here, NIR reflectance spectroscopy was not successful in determining soil N mineralisable in 21 days.
Investigations into near Infrared Analysis as an Alternative to Traditional Procedures in Manure Nitrogen and Carbon Mineralisation Studies
Authors: Reeves James B. , Van Kessel Jo Ann S.
Published: May 2009

The objective of this investigation was to determine the feasibility of using near infrared (NIR) reflectance spectroscopy to determine nitrogen and carbon mineralisation rates and extents in dairy manures. Ground soil samples from studies in which manure was incubated with soil for various time periods (0 to 112 d) were scanned in the near infrared (1100 to 2498 nm) using a scanning monochromator equipped with a rotating sample cup. Control samples (soil alone) were also scanned and tested. Calibrations for ammonia, nitrate, total N (ammonia and nitrate) contents and carbon evolved as carbon dioxide were developed. Calibration values for ammonia and nitrate were determined on potassium chloride soil extracts using a Technicon autoanalyser. Carbon dioxide values were determined by titrating evolved carbon dioxide that was trapped using potassium hydroxide solution. All calibrations were developed using Partial Least Squares regression analysis. Results using 593 samples from several mineralisation experiments have shown that, while NIR reflectance spectroscopy calibrations for ammonia, nitrate, total N and evolved carbon dioxide may be possible, their development will require great care with respect to the samples to be covered by the calibration. While it appears that the source of the manure, with respect to the diet of the animal(s), was not a serious consideration, manure storage conditions prior to incubation had a strong influence on calibration results. In addition, separate calibrations appear to be needed for control and non-control samples. In summary, results presented here, indicate that NIR reflectance spectroscopy may have potential for analysing manure-amended and non-amended soils from mineralisation experiments, but further work is needed to determine its true potential.
Detection of Grain Weevils inside Single Wheat Kernels by a Very near Infrared Two-Wavelength Model
Authors: Ridgway Christopher , Chambers John , Cowe Ian A.
Published: May 2009

Near infrared reflectance spectroscopy in the very near infrared region (700 nm to 1100 nm) has been investigated for the detection of grain weevil larvae and pupae inside single wheat kernels. Using a total of 80 samples, simple, two-wavelength classification models have been identified, based on either log 1/ R (982 nm)–log 1/ R (1014 nm) or log 1/ R (972 nm)–log 1/ R (1032 nm). Both models correctly classified over 96% of samples as uninfested or infested. Detection performance equalled that obtained using the full-spectrum approach of principal components analysis. In a separate experiment, repeatedly scanning samples over time demonstrated detection of younger larvae as well as later developmental stages. This experiment confirmed that the observed spectral differences arise from the actions of the developing insect, rather than from any feature specific to kernels selected by adult females for egg-laying. The origins of the spectral differences are almost certainly decreasing grain starch, for log 1/ R (982 nm)–log 1/ R (1014 nm), or increasing grain moisture, for log 1/ R (972 nm)–log 1/ R (1032 nm), with infestation. These results indicate that the future incorporation of the wavelength pair, 982 nm and 1014 nm, as camera lens filters in a very near infrared imaging system, could lead to an inexpensive, rapid and reliable machine-vision method for detecting internal insects in grain.
Non-Destructive Determination of Soluble Solids in Papayas Using near Infrared Spectroscopy
Authors: Slaughter D.C. , Cavaletto C.G. , Gautz L.D. , Paull R.E.
Published: May 2009

A non-destructive optical method for determining the soluble solids content of fresh whole papayas ( Carica papaya L.) “Kapoho Solo” was investigated. The method, based upon near infrared spectrophotometric techniques, could predict the soluble solids content of papayas ( r2 = 0.84, SEC = 1.1°Brix, SEP = 1.1°Brix).
Sampling Reproducibility and Error Estimation in near Infrared Calibration of Lake Sediments for Water Quality Monitoring
Authors: Dåbakk Eigil , Nilsson Mats , Geladi Paul , Wold Svante , Renberg Ingemar
Published: May 2009

This study forms part of a wider project designed to develop methods for routine lake monitoring using near infrared (NIR) spectrometry of surface sediment samples. During calibration, linear relationships (y = Xb + f) between water chemistry variables (y) and the NIR spectra (X) were evaluated by regression analysis. The principal objectives of this study were to investigate sources of error, both in the X-data (i.e. the NIR spectra), due to natural variation, sediment sampling, subsequent sample handling and measurements and also in the estimation of y-data, here measured lake-water pH values for use in calibration. The error in the NIR spectral data was investigated in two different ways. First, lake-water pH was predicted by a PLS model derived from triplicate lake sediment spectra, and an ANOVA was carried out on the predicted pH. Using this strategy, the within-lake variance of NIR-predicted pH of each lake was found to be significantly lower than the between-lake variance at the p = 0.01 confidence level. In an alternative approach, lakes which were very similar, according to principal component analysis (PCA) score plots, were selected and PLS-DA (Partial Least Squares-Discriminant Analysis) was used to show that the triplicate sediment spectra from each lake were clearly resolved from spectra of other lakes. For 33 lakes, pH measurements of their waters allowed estimation of an arithmetic mean and variance in the y-data. This variance was pooled over all the lakes and compared to the total variance in the y-variable. For pH, the temporal within-lake variability, pooled over all lakes, accounted for only 1.7% of the between-lake variability. Thus, the sampling strategy and temporal resolution of measured lake-water pH allow accurate estimates of lake-water pH from NIR spectra.
Determination of Phase II Mushroom (Agaricus Bisporus) Compost Quality Parameters by near Infrared Spectroscopy
Authors: Sharma H.S.S. , Kilpatrick M. , Burns L.
Published: May 2009

The microbial and biochemical characteristics of compost prepared from wheat straw and chicken litter can determine the total yield of fruiting bodies of Agaricus bisporus. With the aim of identifying key substrate parameters and their relationship with mushroom yield, compost samples were obtained from four comparative trials carried out over a seven year period. The objective of this study was to assess the use of near infrared (NIR) reflectance spectroscopy for determining important characteristics of pasteurised compost. The samples were analysed for moisture content, microbial population, pH, conductivity, nitrogen, carbon and hydrogen, nitrogen, ash, ammonia, Na, Cu, Fe, acid detergent fibre, neutral detergent fibre, lignin and fibre fractions as determined by thermal analysis. Results from conventional analytical methods were correlated with NIR data and partial least squares regression analysis used to assess the information in the absorbance spectrum, which determines the concentration of the key parameters. Visible and NIR scans of the calibration samples made over the range of 400–2498 nm indicated that best calibrations could be developed using the 1100–2498 nm segment. NIR calibration equations for predicting NDM, ash, carbon, thermophilic population and fibre fractions have been successfully developed and then validated using independent samples.
Quality Characterisation of Crude Oils by Partial Least Square Calibration of NIR Spectral Profiles
Authors: Hidajat K. , Chong S.M.
Published: May 2009

The correlation of near infrared (NIR) spectral profiles of crude oils with total boiling point (TBP) assay and density has been studied. Fourteen partial least square (PLS) models were calibrated by a training set of 110 samples. The developed NIR methods have reproducibility limits equivalent to the American Society for Testing and Materials (ASTM) reference procedures. Predictive accuracy of the models was estimated from the root mean square error of prediction ( RMSEP) using cross validation. The correlation coefficients were better than 0.98 in these calibrations indicating good model structure. Such a rapid, reliable and inexpensive quantitative method, which is sufficient to assess the potential quality of the crude oil, especially the product yield, is essential in today's competitive refining environment.
A Preliminary Evaluation of near Infrared Spectroscopy for Assessing Physical and Chemical Characteristics of Flax Fibre
Authors: Faughey G.J. , Sharma H.S.S.
Published: May 2009

Near infrared (NIR) spectroscopy has been used extensively as a rapid tool for the evaluation of protein, fibre fractions and other parameters of feeds and forages. The relative proportions of organic components present in flax fibre will vary depending on variety, growing and retting (controlled rotting) conditions, mechanical and processing factors. The presence of the main fibre fractions, such as cellulose, hemicellulose, lignin, wax and others will determine the physical and chemical characteristics. Tests for fibre distribution, fineness and strength are currently assessed using tedious and long-winded methods. The aim of this investigation was to evaluate the use of NIR spectroscopy for developing calibrations for predicting important fibre parameters. In order to develop a model, a range of samples representing poor, medium and good quality fibres are included in the calibration and validation sample sets. Derivative thermogravimetric analysis (DTG) and airflow methods have shown that differences in fibre fineness can be modelled from NIR spectral data in the ranges 1800–2498nm and 1100–2498nm, respectively. Fibre strength measurements were correlated with the NIR 1800–2498nm spectral band. The determination of fibre components using acid and neutral detergent methods exhibited a poor correlation with NIR spectroscopy assessments on the same sample set. NIR spectroscopy has proved to be a useful tool for predicting fibre fineness and strength in flax, however, its success will be dependent on the accuracy of reference measurements currently employed for fibre testing.
Networking of near Infrared Spectroscopy Instruments for Rapeseed Analysis: A Comparison of Different Procedures
Authors: Tillmann Peter , Reinhardt Tilli-Charlotte , Paul Christian
Published: May 2009

A comparison of several procedures to establish a network of near infrared (NIR) spectroscopy instruments for analytical applications with rapeseed [moisture, protein, oil, glucosinolates (GSL), oleic acid (C18:1)] is presented. The procedures are (a) calibration transfer with bias adjustment, (b) standardisation with different products and different number of samples, (c) calibration with spectra of different instruments and (d) the use of a repeatability file for minimising instrument differences. The most successful procedure proved to be the use of a repeatability file of spectra of the network instruments after standardisation using rapeseed samples. Following this procedure the standard deviation of analyses in a network could be reduced by 50–66% compared to a direct calibration transfer. Calibrations for constituents with high absorptivity (e.g. moisture) could be transferred directly without a bias correction, while those for constituents with a low absorptivity (e.g. GSL) had to be transferred using a repeatability file and standardised instruments.
Tolerance of near Infrared Calibrations to Temperature Variations; A Practical Evaluation
Authors: Hansen W.G. , Wiedemann S.C.C. , Snieder M. , Wortel V.A.L.
Published: May 2009

Process samples of esters have been analysed by transmittance near infrared (NIR) at temperatures between 60 and 70°C (±0.2). Apart from density changes, these small temperature variations affect molecular associations by H-bonding. Partial Least Square (PLS) models based on the first OH overtone (1350–1500nm) have been made for hydroxyl value determination, including implicitly the temperature variable. The sensitivity of these NIR calibrations to temperature has been evaluated by an analysis of variance and the “Taguchi principle”, using both average model performance and model variance. An accurate and precise control of the sample temperature prior to scanning leads to the lowest prediction error. When temperature fluctuations can not be avoided, introduction of temperature variance in the calibration set can improve the model robustness; this strategy is only beneficial if temperature range, temperature distribution and number of PLS factors have been carefully optimised.
A Dynamical Method for Calculating the near Infrared Spectra of Molecules and Macromolecules
Authors: Wozny C.E. , Noid D.W. , Sumpter B.G.
Published: May 2009

The Semi-classical Spectral Method (SSM) may be used to calculate the overtone vibrational frequencies of near infrared (NIR) spectra for molecules and polymers. According to the theory, the transition frequency between two quantum states, n and m, may be found from the relation ωnm=(m–n)ω(n̄), where n̄ = (n+m)/2. The variable n̄ is a semi-classical eigenvalue associated with the action of a vibrational mode, and ω(n̄) is the vibrational frequency of a dynamical trajectory which has an action J=(n̄+½)ℏ in the mode of interest. Frequencies are calculated from a classical trajectory using the MUSIC frequency estimator. A normal mode analysis is not able to calculate overtone frequencies because that approach does not allow for a variable such as n̄. The accuracy and significance of the method is demonstrated by two examples. First, the method is applied to the Morse potential, which is an analytical function with exact solutions. Second, it is applied to a model of polyethylene in order to calculate the overtone spectra of the CH2 anti-symmetric and symmetric stretching vibrations.
Determination of Ammonium-N, Moisture, Total C and Total N in Dairy Manures Using a near Infrared Fibre-Optic Spectrometer
Authors: Reeves J.B. , Van Kessel J.S.
Published: May 2009

The objective of this study was to investigate the feasibility of using near infrared (400 to 2498 nm or sub-regions thereof) fibre-optic-based spectroscopy to estimate nutrient concentrations in dairy manures. One hundred and seven diverse manures, collected from dairy farms in the north-eastern United States (CT, MD, NY, PA, VA) were assayed by conventional means and spectroscopically for total C and N, ammonium-N and moisture. Samples were scanned (64 co-added scans) on a Foss-NIRSystems Model 6500 scanning monochromator equipped with a fibre-optic probe from 400 to 2498 nm, and on an Ocean Optics model S2000 CCD, fibre-optic probe spectrometer from 430 to 1100 nm (1000 scans/sample, integration time of 41 ms). Calibrations were developed using the one-out cross-validation procedure using Partial Least Squares Regression. Results demonstrated the following: 1) calibrations for ammonium-N, moisture and total C and N can be developed, but are not as accurate as those previously developed using a large sample cell (approximately 38 × 200mm) and vertical cell transport device (non-fibre-optic); 2) limitations (high noise in the 2000–2498 nm region) in the spectra produced by fibre-optic bundles are at least partially responsible for the reduced accuracy found with fibre-optic systems when compared to non-fibre-optic means of sample presentation; 3) spectra produced by fibre-optic systems appear to be more spectrally diverse than those for non-fibre-optic systems; 4) while determinations based on spectra covering the region from 400 to 2300 nm appear to be a viable alternative to manure Quick Tests already on the market, those using only the 400 to 1098 nm region are not; and 5) further work with larger data sets is needed to better determine the feasibility, limitations and requirements for developing accurate and robust calibrations for manure constituents using fibre-optic based spectrometers, regardless of the spectral region used.
Near Infrared Reflectance Spectroscopy for the Determination of Biological Activity in Agricultural Soils
Authors: Reeves J.B. , McCarty G.W. , Meisinger J.J.
Published: May 2009

The objective of this work was to investigate the usefulness of near infrared (NIR) reflectance spectroscopy in determining biological activity in agricultural soils. A Foss-NIRSystems model 6500 spectrometer, equipped with a spinning sample cup module, was used to scan 179 soil samples obtained from experimental plots at two locations with three replicate plots under plough and no-till practices at each location with three rates of NH4NO3 for each plot with samples taken from five depths for a total of 180 samples (one sample lost). Biological activity as measured by four enzymes (dehydrogenase, phosphatase, arylsulfatase and urease) and nitrification potential was determined by conventional methods and NIR reflectance spectroscopy. Investigations showed NIR reflectance spectroscopy to be capable of determining biological activity as reflected by the four enzymes and nitrification potential to at least some degree. With the best R2 in the range of 0.8, the results, while positive, were not as good as found previously for many other components (i.e. total C and N) in the same sample set. Efforts at simple discrimination into high, medium and low activities were not successful, and for the most part, calibrations based on subsets, such as samples from only one location, were not found to be an improvement. Correlation analysis indicated that measures of biologically-active nitrogen might be the basis for these determinations. Finally, while further research will be needed to define clearly the basis for, limitations to and usefulness of NIR reflectance spectroscopy in determining biological activity in soil samples, the results presented indicated that NIR reflectance spectroscopy might be useful for the rapid determination of such activity in cases where extreme accuracy is not required, such as spatial mapping.
Test of the Representative Layer Theory of Diffuse Reflectance Using Plane Parallel Samples
Authors: Dahm Donald J. , Dahm Kevin D. , Norris Karl H.
Published: May 2009

Equations of Benford used in the Representative Layer Theory are able to describe spectroscopic remission from layered plane parallel samples (plastic sheets) quite effectively. Losses due to reflection directly back in the direction of the incident beam are a major cause of discrepancies. Non-compositional variation and experimental errors tended to produce linear changes in the absorption coefficient, with the remission coefficient being more drastically affected. The remission coefficients obtained experimentally, in general, vary inversely to the absorption coefficient, although, as predicted by theory, front surface reflectance causes a direct variation. In transflectance, the log(1/ R) spectrum of the thinnest samples is the one that is most like the absorption coefficient curve, but the shape of the Kubelka–Munk (absorption/remission) spectra are less affected by sample thickness, especially in the absence of surface reflection.
A Study on the Universality of a Calibration with Sample Temperature Compensation
Authors: Abe Hideyuki , Iyo Chie , Kawano Sumio
Published: May 2009

The applicability and universality of a sample combination method to develop a calibration with sample temperature compensation [ J. Near Infrared Spectrosc. 3, 211 (1995)] was investigated from mathematical and theoretical points of view. From a theoretical analysis it is clear that the development of the calibration will be successful when two conditions are satisfied. One condition is that the vectors whose elements are constituent values should be orthogonal to the vector whose elements are the dot product of spectral change and calibration coefficients. The other is that the inverse vectors of the spectrum related to chemical components should be orthogonal to the vector of spectral change. The first condition is always satisfied when we make a calibration following this method, but whether the second condition is satisfied or not is completely dependent on the regression algorithm. From a mathematical analysis, we concluded that simple multiple linear regression is not completely adequate to develop a calibration with temperature compensation.
A Multivariate NIR Study of Skin Alterations in Diabetic Patients as Compared to Control Subjects
Authors: Geladi Paul , Nyström Josefina , Eriksson Jan W. , Nilsson Anders , Lithner Folke , Lindholm-Sethson Britta
Published: May 2009

A group of 15 diabetic persons with different degrees of diabetes complications, including skin changes, was studied by Fourier Transform Near Infrared (FT-NIR) spectroscopy. Skin reflectance spectra were measured with a fibre-optic probe in four locations (sites): hand, arm, leg and foot. For reference, a group of 28 healthy controls was also measured. Multivariate analysis of the NIR spectra obtained shows a high potential for classification and discrimination of the skin conditions. Valuable indications for future experiments can be observed.
Parabolic Concentration of Diffusely Transmitted near Infrared Radiation in an Acousto-Optic Tunable Filter Spectrometer
Authors: Eilert A.J. , Sweat J.A. , Wetzel D.L.
Published: May 2009

The research model near infrared (NIR) spectrometer described in this paper, worthy of quantitative use and suited for industrial applications, is the result of stepwise refinement of the acousto-optic tunable filter (AOTF)-based monochromator and other optical components. A sensitive and rapid response extended-range indium gallium arsenide (InGaAs) detector (covering the 1100–2500 nm range) was selected to match the high speed of acousto-optic TFS electronic wavelength switching. Excellent quantitative performance has been demonstrated in comparison with commercial grating monochromator and Fourier transform (FT)-NIR instruments for multi-component liquids, films, pumped fluids and even supercritical fluids. Software-controlled wavelength switching, data acquisition and programmed or interactive time averaging at each wavelength demonstrated analytically-enhanced performance. Throughput is not limited by slits, and exposure of the sample to white light, as with a diode array or an FT instrument, is avoided. Although focusing optics between sample and detector were found to work well for concentrating radiation on a small surface area InGaAs detector, detector size limited performance in the case of optically difficult samples because of the low solid angle of collection. Use of an experimental non-focusing multistage parabolic concentrator immediately after the sample vessel and before the 1 mm2 detector was found to offer an advantage for highly scattering specimens. Although the reflection optics of the locally fabricated concentrator directed a lower intensity of light transmitted by clear specimens than from the standard lens arrangement, successful analysis was extended to include highly scattering samples. The percentage of incident radiation attenuated via scatter was reduced, and for scatter beyond a point, the absolute intensity of radiation falling on the detector was greater, even though the absolute maximum of non-scattered intensity was less, thus establishing proof of principle. We anticipate that further improvement could be attained for highly scattering samples with a commercial optics manufacturer's version of the homemade concentrator.
Fourier Transform near Infrared Spectroscopy Applied to Analysis of Chocolate
Authors: Tarkošová Jolana , Čopíková Jana
Published: May 2009

Fourier transform near infrared (FT-NIR) spectroscopy was used to establish calibration equations with the aim of determining sucrose, lactose, fat and moisture in chocolate. The possibility of using FT-NIR spectroscopy for evaluating rheological properties (viscosity and yield) of chocolate was also investigated. The concentrations of individual components and the values of viscosity and yield obtained by standard methods were used as reference values. The spectra of 96 chocolate samples were recorded in reflectance mode in the range of 910–2500 nm using an FT-NIR Nicolet Avatar 360N spectrometer equipped with the UpDRIFT accessory. The first or second derivative transformation of the original NIR spectra gave the best accuracy. A partial least squares (PLS) algorithm was used to create calibration models relating reference values to spectral data. The models were validated using cross-validation. The validation results proved that fat, sucrose and lactose can be predicted with sufficient accuracy, while predicted values for moisture, viscosity and yield are less reliable.
Detection of Parasitised Fly Puparia Using near Infrared Spectroscopy
Authors: Dowell Floyd E. , Broce Alberto B. , Xie Feng , Throne James E. , Baker James E.
Published: May 2009

Near infrared (NIR) spectroscopy was used to identify house fly ( Musca domestica L.) puparia that contained viable parasitoids. Results derived from a partial least squares analysis of NIR spectra showed that about 80–90% of puparia containing parasitoids could be identified correctly. Difference spectra and beta coefficients indicated that absorption differences between parasitised and unparasitised puparia may have been due to moisture content and/or differences in composition of chitin or lipid components. Detection of viable hymenopterous parasitoids within puparia could assist commercial insectaries in delivering known quantities of parasitised puparia for biological control of house flies and other filth flies and in rapidly determining levels of parasitisation of these flies in confined livestock and poultry operations.
Three-Way Modelling of a Batch Organic Synthesis Process Monitored by near Infrared Spectroscopy
Authors: Geladi Paul , Åberg Peter
Published: May 2009

Multivariate monitoring by near infrared (NIR) spectroscopy of an organic synthesis as a batch process gives three-way data of the type batch number × NIR wavelength × time. The data can be analysed by three-way decomposition methods such as parallel factor analysis (PARAFAC). The batch process is the synthesis of an ester carried out by students in the laboratory. The synthesis is monitored by fibre-optic probe NIR measurement every ten minutes. The NIR spectra obtained have no distinct peaks and simply doing curve resolution on them is very difficult, but it is shown that pretreatment of the NIR spectra can lead to a good PARAFAC model and a chemical interpretation of the unique loadings obtained. The interpretation of the spectral loadings is carried out by comparison with pure chemical spectra. The data set is available from the authors.
In-Line Determination of Moisture in Margarine, Using near Infrared Diffuse Transmittance
Authors: Isaksson T. , Nærbø G. , Rukke E.O. , Sahni N.S.
Published: May 2009

In a pilot plant study, 36 batches of margarine were produced, with a moisture range of 14.28–21.91 weight-%. The margarine was measured in- and off-line using a near infrared (NIR) instrument and an off-line laboratory reference method. For the in-line measurements, diffuse transmittance fibre-optic probes were used. For the off-line measurements, sample cups were used. Partial least square regression of multiplicative scatter corrected NIR spectra, in the 780–1100 nm region, gave prediction errors, expressed as root mean square error of cross-validation ( RMSECV) of 0.13 weight-% moisture for the in-line measurements. The corresponding validation correlation coefficient ( R) was 0.998. The corresponding RMSECV and R values for the off-line measurements were 0.14 and 0.997, respectively. The prediction error results are considered to be very good. It can be concluded that in- and off-line NIR determination of moisture in margarine gave very good prediction results and could be used in production.
Methylmethacrylate On-Line Polymerisation Monitoring by Light-Fibre Fourier Transform near Infrared Transmission Spectroscopy and Fourier Transform Mid Infrared/Attenuated Total Reflection Spectroscopy
Authors: Olinga A. , Winzen R. , Rehage H. , Siesler H.W.
Published: May 2009

Growing legal requirements in terms of the identity and quality control of chemical products increasingly require the use of analytical techniques which can be applied solvent- and destruction-free or which can be directly implemented in a process to provide real-time information. With the vibrational spectroscopic techniques of mid-infrared (MIR), near infrared (NIR) and Raman spectroscopy in combination with special probes and chemometric evaluation procedures, such tools have become available and are gaining increasing importance for industrial process monitoring. The present communication reports the results obtained by on-line light-fibre coupled Fourier transform near infrared (FT-NIR) transmission spectroscopy and Fourier transform mid infrared (FT-MIR) spectroscopy in the attenuated total reflection (ATR) mode to monitor the solution polymerisation of methylmethacrylate.
Quantitative Analysis of Agricultural Soils Using near Infrared Reflectance Spectroscopy and a Fibre-Optic Probe
Authors: Reeves J.B. , McCarty G.W.
Published: May 2009

The objective of this work was to investigate the usefulness of near infrared (NIR) reflectance spectroscopy in conjunction with a fibre-optic probe for determining various constituents (total N, organic C, active N, biomass and mineralisable N and pH) in agricultural soils. A NIRSystems model 6500 spectrometer equipped with a fibre-optic reflectance probe was used to scan soil samples ( n = 180) obtained from experimental plots at two locations with three replicate plots under plow and no till practices at each location with three rates of NH4NO3 for each plot (2 × 3 × 2 × 3 = 36). For each of these, samples were taken from five depths for a total of 2 × 3 × 2 × 3 × 5 or 180 samples. Optimal calibrations were achieved using first derivative spectra, and only data from 1100 to 2300 nm, with every 20 data points averaged from 1900 to 2300 nm. Compared to results achieved using a spinning cup, the use of the probe resulted in more concentration outliers (up to 6% with probe and none with the spinning cup), the reason for which is unknown. Otherwise, the final calibration results were quite similar to those achieved using a spinning cup to obtain spectra, with calibration (outliers removed) R2 and RMSD/Mean of 0.96, 6.6; 0.95, 6.5; 0.88, 15.3; and 0.80, 19.3; for organic C, total N, active N and biomass N, respectively. The R2 and RMSD for pH were 0.80 and 4.5 pH units, respectively. In summary, the work presented here demonstrated that NIR spectroscopy, based on data obtained using a fibre-optic probe, can be successfully used to determine compositional parameters of agricultural soils (particularly organic C and total N). However, there appeared to be a greater problem with outliers when using a fibre-optic probe than was true when obtaining spectra using a spinning cup.
Simultaneous Measurement of Carbon and Nitrogen Content of Compost Using near Infrared Spectroscopy
Authors: Suehara Ken-Ichiro , Nakano Yasuhisa , Yano Takuo
Published: May 2009

Near infrared (NIR) spectroscopy was used to determine the carbon and nitrogen content of compost during compost fermentation of tofu (soybean-curd) refuse. Reflectance measurements in the wavelength range between 400 and 2500 nm were made at 2 nm intervals. The NIR absorption of the carbon components was observed at two wavelengths, 1584 and 1024 nm in the second derivative spectrum. The NIR absorption of nitrogen components was observed at two wavelengths, 2174 and 900 nm in the second derivative spectrum. To formulate a calibration equation, a multiple linear regression analysis was carried out between the NIR spectral data and the carbon and nitrogen content in the calibration sample set (sample number, n = 60) obtained using a Pregie–Dumas combustion method. The values of the multiple correlation coefficient were 0.988 and 0.984, respectively. To validate the calibration equations obtained, the carbon and nitrogen content in the prediction sample set ( n = 48), not used for formulating the calibration equation, were calculated using the calibration equations and compared with the values obtained using the Pregie–Dumas combustion method. Good agreement was observed between the results of the Pregie–Dumas combustion method and the NIR method. The values of the simple correlation coefficient were 0.986 and 0.972, respectively. The study indicates that NIR is a useful method for process management of the compost fermentation of tofu refuse.
The Transfer of Fatty Acid Calibration Equations Using Four Sets of Unsealed Liquid Standardisation Samples
Authors: García-Olmo Juan , Garrido-Varo Ana , De Pedro Emiliano
Published: May 2009

A database of 352 near infrared (NIR) spectral data from Iberian pig liquid fat was used for the prediction of palmitic, stearic, oleic and linoleic fatty acids content. The results showed the excellent accuracy of NIR equations with coefficients of determination ( r2) reaching values close to 1 and standard error of cross-validation ( SECV) values similar to the standard error in the reference method ( SEL). The possibility of transferring the calibrations developed in one instrument to another NIR instrument, following the Shenk and Westerhaus standardisation algorithm, was examined. Two monochromator instruments were optically matched using four different standardisation sets of unsealed samples (Set A: one sample of Iberian pig liquid fat with a similar fatty acids composition to the average of the calibration set; Set B: 20 samples of Iberian pig liquid fat covering the range in optical density and fatty acid composition of the calibration set; Set C: oleic acid; Set D: linoleic acid. The standardisation completed with Set A and Set B produced spectra on the satellite instrument which resembled spectra scanned on the master instrument. The standard error of the differences ( SED) between the values predicted by the master and the satellite after standardisation were similar to, or even lower than, the standard error of prediction ( SEP) values for the same samples scanned on the master instrument.
The Impact of Instrument Engineering Parameters on Spectral Reproducibility across Filter Instruments
Authors: Siska Juraj J. , Hurburgh Charles R. , Siska Peter P.
Published: May 2009

This paper explores the role of instrument engineering parameters in master–slave optical differences. Engineering parameters with significant ( p = 0.05) impact were classified into three groups according to the magnitude of their influence (analysis of variance mean squares) on optical differences. The only parameter with high influence was preamplifier gain. Filter area, filter bandwidth, detector temperature, idle filter wheel temperature, sample temperature and optics unit differences exerted medium impact. There were seven properties with low but still significant impact. Software was developed to aid users and manufacturers in selecting optical standardisation and in diagnosing instrument differences.
Stiffness Prediction of Radiata Pine Clearwood Test Pieces Using near Infrared Spectroscopy
Authors: Thumm Armin , Meder Roger
Published: May 2009

Near infrared (NIR) spectroscopy has been used to predict the modulus of elasticity (stiffness) of samples taken from knot-free sapwood specimens of radiata pine ( Pinus radiata D. Don). The method shows the potential of using NIR spectroscopy for assessment of lumber stiffness. A model based on NIR spectra taken on the radial face of 404 samples of radiata pine clearwood was established to predict stiffness. Samples were moved past the detector at a rate of 900 mm min−1. This model then was used to predict the stiffness of a further 80 samples and the results show an error in prediction of 14% of the mean measured value.
NIR Spectroscopy and Partial Least Squares Regression for the Determination of Phosphate Content and Viscosity Behaviour of Potato Starch
Authors: Thygesen L.G. , Engelsen S.B. , Madsen M.H. , Sørensen O.B.
Published: May 2009

A set of 97 potato starch samples with a phosphate content corresponding to a phosphorus content between 0.029 and 0.11 g per 100 g dry matter was analysed using a Rapid Visco Analyzer (RVA) and near infrared (NIR) spectroscopy, (700–2498 nm). NIR-based prediction of phosphate content was possible with a root mean square error of cross-validation ( RMSECV) of 0.006% using PLSR (partial least squares regression). However, the NIR/PLSR model relied on weak spectral signals, and was highly sensitive to sample preparation. The best prediction of phosphate content from the RVA viscograms was a linear regression model based on the RVA variable Breakdown, which gave a RMSECV of 0.008%. NIR/PLSR prediction of the RVA variables Peak viscosity and Breakdown was successful, probably because they were highly related to phosphate content in the present data. Prediction of the other RVA variables from NIR/PLSR was mediocre (Through, Final Viscosity) or not possible (Setback, Peak time, Pasting temperature).
Optimising Multivariate Calibration by Robustness Criteria
Authors: Wortel V.A.L. , Hansen W.G. , Wiedemann S.C.C.
Published: May 2009

Regular maintenance of (multivariate) near infrared (NIR) calibration models is a crucial but time-consuming step to ensure a successful NIR application in industry. Naturally, robustness of these models is essential to minimise both maintenance time and cost. In this paper, a method combining Taguchi philosophy, experimental design and artificially-derived spectra, is proposed to evaluate and improve the robustness of NIR calibrations. This approach is based upon a typical industrial NIR application, the determination of hydroxyl value of ester products. Experiments have been designed to investigate which parameters (control and signal) influence the performance of the calibration. Two calibration models have been selected for the robustness investigation. One benchmark model was based on general criteria applied for NIR calibration and another based on Taguchi's criteria. Artificially-derived spectra were produced by adding severe fluctuations of simulated wavelength shifts into original spectra for both models, then, the models' performance was evaluated six months after the calibration. The model selected based on Taguchi's criteria, is clearly more tolerant to wavelength shifts and less sensitive for overfitting in comparison with the “benchmark” model.
Near Infrared Reflectance Spectroscopy for Online Particle Size Analysis of Powders and Ground Materials
Authors: Pasikatan Melchor C. , Steele James L. , Spillman Charles K. , Haque Ekramul
Published: May 2009

The cross-sensitivity of near infrared (NIR) reflectance to the particle size of powders or ground materials has long been documented but not fully exploited for particle size estimation. Diffuse reflectance of a powder sample is dependent on light scattering within its layers, and a powder's absorption and scattering coefficient are related to its particle size. This is the basis of NIR reflectance–particle size calibrations. The availability of fibre optic probes and the speed of NIR spectrometers make them suitable for remote and online sensing of particle size, in addition to providing chemical information of a powder sample. The basics of NIR reflectance spectroscopy relevant to particle size determination and its relation to sample preparations, methods of presentation, reference methods, calibration development and validation are reviewed in this paper.