bluuebunny/crossref_metadata_2025 huggingface dataset:
Directional Characteristics of near Infrared Light in the Process of Radiation and Transmission from Wood
Authors: Tsuchikawa Satoru , Torii Misato , Tsutsumi Shigeaki
Published: May 2009

In this report, a newly designed apparatus, that is, a near infrared auto-goniophotometer, was introduced to acquire detailed optical information about biological material having a cellular structure like wood. Such information allows us to analyse the three-dimensional physical condition of a sample and confirm the suitability of proposed optical models. The directional characteristics could be found on the basis of the intensity of reflected or transmitted light at each observation angle. In these experiments, Sitka spruce ( Picea sitchensis Carr.) with various thicknesses were used. Results of these measurements showed the directional characteristics which were affected significantly by the illumination conditions and sample thickness. Particularly, these varied characteristically with the wavelength of the incident light. This result supports the validity of the proposed optical models which vary with wavelength. Throughout these analyses, the relationships between the physical aspects of a sample and the emitted light from it is being clarified.
Effect of Random Noise on the Performance of NIR Calibrations
Authors: Lu Jing , McClure W.F. , Barton F.E. , Himmelsbach D.S.
Published: May 2009

The proliferation of applications for near infrared (NIR) spectroscopy has been fostered by advances in instrumentation and statistics. NIR analytical instrumentation is becoming more stable and reliable. Chemometrics is playing an important role in qualitative and quantitative NIR spectra analysis. The objective of this study was to evaluate the performances of four commonly used calibration models: (1) stepwise multiple linear regression (SMLR); (2) classical least-squares (CLS); (3) principal component regression (PCR); and (4) partial least-squares (PLS) in NIR spectroscopy analysis when random noise is present in the optical data. A conceptually simple procedure for comparing the performance of the four calibration methods in the presence of different levels of random noise in spectra data has been introduced here. This procedure, using the computer simulation data and real spectra of tobacco, has provided useful information for understanding the effects of random noise on the performance of multivariate calibration methods. Both numerical and graphical results will be shown.
Prediction of Wheat Bread-Baking Functionality in Whole Kernels, Using near Infrared Reflectance Spectroscopy
Authors: Pawlinsky Twylla , Williams Phil
Published: May 2009

Efficiency of prediction of wheat strength by “wet chemistry” prediction tests is summarised. Inter-relationships among these tests, and recognised criteria of wheat strength (physico-chemical properties and baking data) are reviewed. Calibrations for predicting both “prediction-type” and data from recognised test procedures have been developed for use with whole wheat. The relative efficiencies of near infrared and established wet chemistry methods for the prediction of wheat strength for use in plant-breeding are discussed. For screening large numbers of lines for several strength parameters, near infrared methods are more practicable.
Mid and near Infrared Study of Carbohydrates by Canonical Correlation Analysis
Authors: Robert P. , Devaux M.F. , Qannari A. , Safar M.
Published: May 2009

Multivariate data treatments were applied to mid and near infrared spectra of glucose, fructose and sucrose solutions in order to specify near infrared frequencies that characterise each carbohydrate. As a first step, the mid and near infrared regions were separately studied by performing Principal Component Analyses. While glucose, fructose and sucrose could be clearly identified on the similarity maps derived from the mid infrared spectra, only the total sugar content of the solutions was observed when using the near infrared region. Characteristic wavelengths of the total sugar content were found at 2118, 2270 and 2324 nm. In a second step, the mid and near infrared regions were jointly studied by a Canonical Correlation Analysis. As the assignments of frequencies are generally well known in the mid infrared region, it should be useful to study the relationships between the two infrared regions. Thus, the canonical patterns obtained from the near infrared spectra revealed wavelengths that characterised each carbohydrate. The OH and CH combination bands were observed at: 2088 and 2332 nm for glucose, 2134 and 2252 nm for fructose, 2058 and 2278 nm for sucrose. Although a precise assignment of the near infrared bands to chemical groups within the molecules was not possible, the present work showed that near infrared spectra of carbohydrates presented specific features.
Near Infrared Spectroscopy of Fuel Contaminated Sand and Soil. I. Preliminary Results and Calibration Study
Authors: Zwanziger Heinz W. , Förster Heidrun
Published: May 2009

Regional areas may be contaminated by the past activities of the chemical and oil industries and of the military. Therefore, the present study was undertaken to test the possibilities of near infrared (NIR) reflectance spectroscopy for direct detection and determination of oil and fuel contaminations. If reliable results are obtained NIR reflectance spectroscopy could be a valuable part of land remediation processes. Preliminary investigations showed that it is possible to distinguish samples of stone chippings, sand, cultivated soil, humus and potting soil by multivariate data analysis. After spiking with gasoline, diesel, motor oil and synthetic hydrocarbon mixtures (BTEX) sand rather than cultivated soil shows obvious spectral absorptions due to contaminations higher than 1% (w/w). The influence of particle size fractions has been investigated in detail using dry sand sieved to < 500 μm (fine), 500–800 μm (medium) and >800 μm (coarse). Contaminations in fine and medium fractions often can be modelled with only one intensity at sufficiently low calibration error, SEC. With coarse fractions SEC is three times higher. Models based on derivative spectra have no significant advantage. In general, mean centring results in more pronounced error minima than multiplicative scatter correction (MSC). Partial least squares (PLS) models can be fitted to obtain any wanted SEC even by cross-validation. For comparable SEC, PLS models in general do not need more factors if samples become more inhomogeneous. Data pre-processing techniques such as Kubelka–Munk transformation, Saunderson correction, MSC and combinations thereof have been tested. Adequate sample variation of the diffuse reflectance fraction of detected light according to the Saunderson model could improve the performance of calibration models. The best values for standard error of prediction, SEP, are obtained if calibration models are derived from sets of spectra of sieved samples and used for contamination prediction of natural samples, and not vice versa. Spectra of contaminated soil and humus need cleverer spectral selection and pre-processing for better performance of calibration models.
Characterisation of Soils by the near Infrared Technique
Authors: Salgó A. , Nagy J. , Tarnóy J. , Marth P. , Pálmai O. , Szabó-Kele G.
Published: May 2009

There are physical, physico-chemical and chemical parameters which can be used as a basis for the characterisations of soils. Some of these characterisation methods are slow, laborious and show very empiric character. Near infrared (NIR) reflectance spectroscopic methods were used for substitution of conventional soil analysis procedures. Seven different soil characteristics (humus, calcium carbonate, total nitrogen, dead water content, yarn test by Arany, mechanical composition, hygroscopic water content) were measured by NIR using Hungarian and ISO standards as reference methods. It was concluded that the humus content, which measures the total organic content of soil can be predicted from NIR spectra with good accuracy ( SEP = 0.3%). There are two parameters (mechanical composition and hygroscopicity) which showed significant correlation with the changes in the status of water in soil and they were detectable with acceptable accuracy based on their NIR spectra. The other four parameters were not predictable either due to the lack of spectroscopic information or to the poor quality of reference methods. The developed method was very sensitive to the physical status of samples and an accurate standard sample preparation was needed. Spectral libraries were developed and validated for a quick and non-destructive qualification and selection of soil samples.
NIR and other Luminometric Methods to Monitor the Primary Clotting Phase of Milk
Authors: Giangiacomo R. , Lizzano R. , Barzaghi S. , Cattaneo T.M.P. , Barros A.S.
Published: May 2009

The rapid routine method currently used to monitor the ability of milk to coagulate does not provide information on the primary clotting phase. The purpose of this work was to assess if the principal critical events related to the primary clotting phase could be detected by NIR and by other methods based on the interaction of light and material (fluorescence spectroscopy, tristimulus colorimetry) that provide a quick response. Six different coagulation tests were carried out. Reconstituted skim milk powder was used as standard substrate and the same liquid calf rennet solution was added. Milk NIR spectra were collected at 35°C using an InfrAlyzer 500 (Bran+Luebbe). Spectra were taken every 70 seconds, from rennet addition up to about 10 minutes after clotting time. Data were processed by IDAS-PC software to find the most discriminant wavelengths in highlighting spectral differences. For fluorescence tests, the primary clotting phase was monitored collecting samples at different times and stopping the enzymatic reaction at 0°C in an ice-bath. Spectrofluorimetric titrations were carried out by using ANS as hydrophobic probe and a Luminescence Spectrometer LS-B. Protein Surface Hydrophobycity (PSH) values were calculated. The ANS relative distribution was also monitored after ultracentrifugation at 0°C. In this case ANS was added to milk before rennet addition. Colorimetric assays were carried out by using a tristimulus colorimetry and data collected at the same time as NIR spectra. Differences in luminosity values were calculated. The clotting time was calculated using both a Formagraph Instrument and by visual observation of coagulation. NIR data show two critical events during the primary clotting phase, confirmed by the other techniques used. The first appears a few minutes before clotting. The second, in accordance with the visual observation of coagulation, detects the clotting point, before Formagraph in corrispondence of micellar aggregation. Interesting results are obtained by plotting selected NIR 2nd derivative absorbance values against time; this establishes a trend of coagulation, which is also detectedby the other techniques. The interrelationship among the different techniques is discussed and spectral data are interpreted in terms of water bonds and/or different amounts of free water due to the formation of new products and/or protein structure rearrangements.
Estimating the Food Processing Characteristics of Pulses by near Infrared Spectroscopy, Using Ground or Whole Samples
Authors: Flinn P.C. , Black R.G. , Iyer L. , Brouwer J.B. , Meares C.
Published: May 2009

The use of near infrared spectroscopy (NIR) was investigated for its ability to predict a range of chemical constituents (protein, moisture, fat, ash, total dietary fibre) and functional properties (100 seed weight, hydration capacity, hull percentage, dehulling efficiency, colour, cooking quality) of field peas and chickpeas. NIR calibrations were developed using 165 samples of field peas and 151 samples of chickpeas which had been spectrally selected from larger populations encompassing two seasons. For both species, calibration accuracy was generally better on ground than whole samples for chemical composition, but better on whole than ground samples for physical or functional properties. For most properties measured, accuracy of NIR calibrations was either satisfactory or promising, but successful implementation in a breeding programme will depend on further evaluation using independent samples, broadening the sample populations or improvements in the reference methods.
The Use of near Infrared Reflectance Spectroscopy to Predict the Insoluble Dietary Fibre Fraction of Cereal Products
Authors: Kays Sandra E. , Barton Franklin E.
Published: May 2009

The insoluble and soluble fractions of dietary fibre have different human physiological effects and their presence in foods is of interest to consumers, the medical community and the cereal product industry. The development of a model, using near infrared (NIR) reflectance spectroscopy, to predict insoluble dietary fibre in a wide range of dry-milled cereal products and grains is described. The products included breakfast cereals, crackers, brans, pastas and flours. Insoluble dietary fibre was measured by the AOAC enzymatic–gravimetric procedure (AOAC 991.43). The range in insoluble dietary fibre was 0–48%. Near infrared reflectance spectra were obtained with a scanning monochromator and data analysed with a commercial analysis program. A calibration ( n = 90) was developed for prediction of insoluble dietary fibre using preprocessed spectra and modified partial least squares regression. The standard error of cross validation and R2 were 1.34% and 0.99, respectively. The model was tested with independent validation samples ( n = 32) and the resulting standard error of performance and r2 were 1.13% insoluble dietary fibre and 0.99, respectively. The results show that NIR spectroscopy can be used to predict the insoluble dietary fibre content in a wide variety of processed and unprocessed cereal products.
Discrimination between Glutinous and Non-Glutinous Rice by Vibrational Spectroscopy. I: Comparison of FT-NIR DRIFT, PAS and Raman Spectroscopy
Authors: Ootake Yoshisato , Kokot Serge
Published: May 2009

Rice is a major cereal crop in Japan and in Asia. Its taste is determined by such factors as protein and water content as well as stickiness. It has been well established that protein and water content can be estimated by near infrared spectroscopic measurements. However, the measurement of amylose content, which is closely related to rice stickiness, at present, must be carried out by wet chemical methods. Vibrational spectroscopic techniques are possible alternative approaches for the determination of amylose content in rice and, in this paper, we report on the initial steps for the development of methodology for this purpose, namely on the comparison of FT-NIR DRIFT (Diffuse Reflectance Infrared Fourier Transform Spectroscopy), PAS (Photo-Acoustic spectroscopy) and FT-Raman spectroscopy for the discrimination of glutinous and non-glutinous rice. Perkin-Elmer System 2000 FTIR (equipped with DRIFT and PAS accessories) and System 2000 NIR FT-Raman spectrometers were used to collect spectra from ground samples of seven glutinous and 12 non-glutinous rice. When SIMCA (Soft Independent Modelling of Class Analogy) was used to classify raw spectral data, the best discrimination was achieved with the FT-Raman results followed by those from the PAS measurements. FT-Raman spectra of some samples of non-glutinous rice showed strong fluorescence effects. When these samples were excluded from analysis, modelling and classification improved.
Discrimination between Glutinous and Non-Glutinous Rice by Vibrational Spectroscopy. II: Effects of Spectral Pre-Treatment on the Classification of the Two Types of Rice
Authors: Ootake Yoshisato , Kokot Serge
Published: May 2009

To measure the amylose content of rice, discrimination between glutinous and non-glutinous rice by vibrational spectroscopy was performed. It was previously demonstrated that classification of raw spectra by the SIMCA method showed the FT-Raman technique provided the best discrimination of classes. In this paper, the effects of spectral pre-treatments such as differentiation and multiplicative scatter correction (MSC) on classification of the rice samples are presented. For FT-NIR DRIFT measurements, differences in classification following different pre-treatments were relatively small but the best classification was obtained with the 2nd derivative pre-treatment, although precision was generally poor. With the PAS spectral sampling method, the classification was better after MSC pre-treatment of raw spectra than either after conversion to the 1st derivative or 2nd derivative. For FT-Raman, the best result was obtained with the MSC pre-treatment. The different effects of pre-treatment on the classification of spectra of the two types of rice probably reflect the information contained in the width of the absorbance bands, because the spectra were collected at 4 cm−1 step with 8 cm−1 resolution. Since the differentiation procedure follows the moving average, very small bands would be eliminated in the process, and would not contribute to the classification analysis. It was noted that effects of fluorescence in the FT-Raman spectra were not removed, even after the MSC pre-treatment.
Classification of High Acid Fruits by Partial Least Squares Using the near Infrared Transmittance Spectra of Intact Satsuma Mandarins
Authors: Miyamoto Kumi , Kawauchi Miyuki , Fukuda Toshitaka
Published: May 2009

The feasibility of on-line measurement of citric acid content using NIR transmittance spectroscopy was investigated. The citric acid content was determined by titration with NaOH. The second derivative absorption values of transmittance spectra through the fruit equator were autoscaled by mean-centring and weighing by 1/S. Dev. The data were analysed by PLS1 using the UNSCRAMBLER software. The spectra of peeled fruits measured by a NIRSystems Model 6250 were analysed, and the model composed of 12 factors provided the highest accuracy; R = 0.93, Bias = −0.013% and SEP = 0.146%. In the next step, the citric acid content in intact satsuma mandarins was regressed by the same method using an on-line instrument. The model composed of five factors explained 68.2% of total Y variation. The accuracy of prediction result was rather low; R = 0.83, Bias = 0.024% and SEP = 0.147%. But, it was possible to classify non-destructively the high acid fruits with about a 20% error rate. The absorption bands of citric acid contributed heavily to this PLS model.
High Precision Measurements: From the Laboratory to the Plant
Authors: Cinier Régis , Guilment Jean
Published: May 2009

FT-NIR spectroscopy allows scientists to develop high-precision quantitative methods in a laboratory environment. These methods are a lot more precise and reproducible than the current methods developed with techniques such as UV/visible spectroscopy, chromatography or potentiometric titration. However, the higher the precision the more difficult will be the calibration development and instrument transfer processes. Depending on the precision required, different parameters start to influence the results. One of the first parameters to take into account is the temperature but with increasing the precision increases the evaporation of solvent, sample homogeneity, the number of calibration samples, the appearance of bubbles and variation of the pathlength start to influence the results. The calibration set can be built in the laboratory. In this case the % SEP is always better than the reproducibility obtained when the method is transferred to the production area. However, precision could be improved when the number of scans was increased. However, this number has to remain reasonable to retain near infrared's advantage of rapid response. In this paper, examples relating to several solutions in water will show the different stages we followed to obtain a 0.025% repeatability, having in mind the need to transfer the method to the plant (quality control lab).
Near Infrared Analysis of Dried Human Serum for Determining Human Serum Urea Concentration
Authors: Hall Jeffrey W. , Pollard Alan
Published: May 2009

We determined the human serum urea concentration from the near infrared spectrum of dried sera to assess whether the removal of water could provide an improvement over the direct analysis of unmodified samples. The results ( r = 0.989, SEP = 1.0 mmol L−1) obtained by the analysis of dried sera by using multiple linear least-squares regression were comparable to the results ( r = 0.993, SEP = 0.8 mmol L−1) obtained by the analysis of unmodified serum by using Partial Least-Squares regression.1 While the NIR determination of serum urea concentration in dried specimens simplifies the regression analysis it requires more technical competence and is more time-consuming.
Prediction of Gasoline Properties with near Infrared Spectroscopy
Authors: Bohács Gy. , Ovádi Z. , Salgó A.
Published: May 2009

The test measurements used for the analysis of gasoline quality are mostly complicated standard procedures which are time consuming and which require special equipment, large volume of samples and specialists. The standard test methods could be partly replaced with non-destructive near infrared (NIR) spectroscopic measurements which are fast and less expensive. The aim of this paper is to present a feasible procedure for the prediction of quality parameters of gasoline from its NIR spectrum in a large and very diverse sample set. 350 commercially available gasoline samples were collected from July 1996. The samples covered summer and winter grades of normal, super and superplus unleaded gasolines with minimum RON requirements of 91, 95 and 98, respectively. These fuels covered a wide range of samples from very different sources including Hungarian and foreign refineries and pumps. An InfraPrime Lab Analyser (Bran+Luebbe) with high quality optical fibres in combination with multivariate calibration (PLSR) was used to determine 12 different chemical and physical properties of gasolines including reseach octane number (RON), motor octane number (MON), benzene, methyl-tertier-buthyl-ether (MTBE), sulphur content, distillation characteristics, Reid vapour pressure (RVP) and density at 15°C. The developed NIR methods predicted four important gasoline properties (RON, MON, benzene and MTBE content) with reproducibilities equivalent to the standard test procedures. The standard errors of prediction were 0.34 for RON, 0.30 for MON, 0.13%(vv−1) for benzene and 0.21%(vv−1) for MTBE content. The correlation coefficients were better than 0.970 in these calibrations. Calibrations developed for other gasoline properties showed poor correlation coefficients and allowed each parameter to be predicted only with higher standard error than the reference values. The NIR methods described are suitable for routine selection measurements in large series of gasoline samples.
Clinical Chemistry and near Infrared Spectroscopy: Technology for Non-Invasive Glucose Monitoring
Authors: Heise H.M. , Bittner A. , Marbach R.
Published: May 2009

Non-invasive assays for blood glucose can be based on near infrared spectrometry of skin tissue using the diffuse reflectance technique. Using a straightforward spectral variable selection based on choices from the optimum partial least-squares (PLS) regression vector yields better results than using PLS calibration models with full spectrum evaluation previously reported. The pairs of variables are selected from the maxima and minima of the regression weights, respectively, in decreasing order. Substantial improvements in the prediction performance of such calibration models, compared to previous calibrations based on full spectrum evaluation, are obtained. Another aspect is the reduced number of spectral variables needed for robust calibration modeling. In addition, evidence is provided for the physical effect, as manifested by the spectral glucose absorptivities, underlying the individual single-person calibration models. Their regression vector structure shows very similar features as calculated for a glucose calibration experiment based on random human plasma samples. Novel techniques are presented for probing the intravascular fluid space using time-resolved near infrared spectroscopy of oral mucosa. The pulsatile blood spectrum can be derived from these diffuse reflectance lip spectra by Fourier analysis. Future applications and prospects for non-invasive blood analysis are discussed.
The Application of the DESIR Technique to the Analysis of Beer
Authors: Chandley P.
Published: May 2009

The Dry Extract Spectroscopy by Infrared Reflection (DESIR) technique was used to predict bitterness, total soluble nitrogen and free amino nitrogen concentrations in beer. Spectra were recorded of the extracts of 65 beers and calibration was attempted using multiple linear and partial least squares regression on raw, derivative and transformed data. High correlations and low errors of prediction were obtained using the DESIR technique for the analysis of free amino nitrogen and total soluble nitrogen. However, poor correlations were observed between NIR spectral data and bitterness values. The technique was shown to be a rapid, repeatable and accurate alternative to traditional methods.
Focusing near Infrared Spectroscopy on the Business Objectives of Modern Pharmaceutical Production
Authors: Axon T.G. , Brown R. , Hammond S.V. , Maris S.J. , Ting F.
Published: May 2009

The early use of near infrared (NIR) spectroscopy in the pharmaceutical industry was for raw material identification, later moving on to some conventional “calibrations” for various ingredients in a variety of sample types. The approach throughout this development process has always been “conventional” with one measurement by NIR directly replacing some other slower method, be it Mid-IR identification, or determinations by Karl Fischer, high performance liquid chromatography (HPLC)etc. A significant change in approach was demonstrated by Plugge and Van der Vlies1 in 1993, where a qualitative system was used to provide “quantitative like” answers for potency of a drug substance. Following on from that key paper, there has been a realisation that the qualitative analysis ability of NIR, has the potential to be a powerful tool for process investigation, control and validation. The final step has been to develop “model free” approaches, that consider individual data sets as unique systems, and present the opportunity for NIR to escape the shackles of “calibration” in one form or another. The use of qualitative, or model free, approaches to NIR spectroscopy provides an effective tool for satisfying many of the demands of modern pharmaceutical production. “Straight through production,” “right first time,” “short cycle time” and “total quality management” philosophies can be realised. Eventually the prospect of parametric release may be materialised with a strong contribution from NIR spectroscopy. This paper will illustrate the above points with some real life examles.
Cardiovascular Near-Infrared Imaging
Authors: Cassis L.A. , Yates J. , Symons W.C. , Lodder R.A.
Published: May 2009

This research uses near-infrared spectrometric imaging to nondestructively locate and determine Low-Density Lipoprotein (LDL) cholesterol that may serve as an in vivo marker for vulnerable atherosclerotic plaques. Vulnerable plaques are plaques prone, in the presence of an appropriate trigger, to events such as ulceration, rupture, erosion, or thrombus that can lead to an acute syndrome. A Nd:YAG-pumped KTP/OPO tunable near-infrared (NIR) laser system is used as a light source for the fiber-optic catheters employed in this research. The BEST algorithm is used to construct chemical-composition images of the intima of the aorta in test subjects in vivo. The long-term goal of these studies is to use NIR laser spectrometric assays of plaque performed with cardiac catheters in vivo to facilitate assignment of patients to specific drug or surgical interventions selected to match their individual vulnerable plaque characteristics.
Absorption and Scatter Corrections for Transflectance Measurements in Nonhomogeneous Fiber Samples
Authors: Taylor R.A.
Published: May 2009

A new fiber optic sensor was developed to measure the mass of optically thin cotton samples by integrating light transmission and reflectance signals. High speed measurements of cotton strength requires an accurate determination of the specimen mass without use of laborious cut-and-weigh methods. A previous high speed sensor measured changes in visible light transmission which required secondary measurements of fiber fineness to adjust the data for light scattering. Fiber orientation also affected scattering which required a precise control on specimen preparation. The new sensor measures fiber specimen transflectance using near infrared light. Because cellulose (the basic compound in cotton) exhibits strong absorption bands, its concentration can be accurately measured using near infrared absorbance. In this report we show that an integratinq sensor gave the best measurement of cotton fiber mass. Additionally, we demonstrated its accuracy over a wide range of fiber orientations using a novel fiber specimen tension experiment.
Identification of Rice Variety Using near Infrared Spectroscopy
Authors: Kwon Y.K. , Cho R.K.
Published: May 2009

Current techniques for the discrimination of varieties of rice is known not to be objective because of having to depend on the naked eye of a well trained inspector. DNA fingerprint methods, based on the genetic character of rice, has been shown to be inappropriate for on-site application because the method needs a lot of labour and skilled expertise.

In order to solve these problems, many researchers have tried to develop a non-destructive method which possesses speed and functionality for the inspection centre of the government. Rice consumers want tot confirm cultivation origin and its variety because they believe price or eating score has a high correlation according to them. Sometimes illegal utilisation of rice has been reported and the variety name has been mismatched with the actual rice variety due to the non-establishment of objective techniques for discrimination of rice origin and variety.

On the basis of this situation, we investigated the possibility of developing a non-destructive discriminant method for the domestic rice variety in this research.

At the 8th IDRC held at Chambersburg in 1996 we reported that an image processing technique using a CCD camera could discriminate the variety of rice with high accuracy in the case of quite different shaped rice but the accuracy reached 90% for similarly shaped rice.

At the prsent conference, near infrared spectroscopy, which can offer internal characters of a single rice kernel, giving useful information for identifying rice variety, was introduced. We have developed several tools for measuing the NIR spectra of whole, polished rice. The spectra using a single grain cell with grinding facilities was more effective than the others in accuracy of identification after principal component analysis.

In conclusion, near infrared spectroscopy can be used to identify rice varieties even though even though accuracy of identification needs to be improved.
New Observation of Nondestructive Evaluation for Sweetness in Apple Fruit Using near Infrared Spectroscopy
Authors: Cho Rae Kwang , Sohn Mi Ryeong , Kwon Young Kil
Published: May 2009

The study was carried out to investigate the factors effects on brix and possibility of non-destructive evaluation for sweetness in apples by near infrared (NIR) spectroscopy. Correlation coefficients ( R) between brix and total sugar contents was 0.66 and R between brix and moisture contents was 0.8. But no clear relationship between brix and free sugar contents(0.30 for fructose, 0.34 for glucose, 0.39 for sucrose and 0.65 for sorbitol) was found. Brix was effected on not only total sugar but also moisture contents. MLR analysis for free and total sugar contents of apple, multiple correlation coefficients ( R) and standard error of prediction ( SEP) were 0.75 and 0.86% for fructose, 0.84 and 0.26% for glucose, 0.86 and 0.33% for sucrose, 0.93 and 0.18% for sorbitol and 0.84 and 0.81% for total sugar. MLR analysis for sweetness score, which was calculated with sweetness index(sucrose 1.0 as standard), R and SEP were 0.8 and 0.82% in range 12.83–17.63. In conclusion, the sweetness score of apple fruits can be determine by NIR spectroscopy.
Near Infrared Calibrations for Goat's Milk Components: Protein, Total Casein, αs-, β- and k-caseins, Fat and Lactose
Authors: Díaz-Carrillo E. , Muñoz-Serrano A. , Alonso-Moraga A. , Serradilla-Manrique J.M.
Published: May 2009

A fast and inexpensive method to quantify the main constituents of goat's milk using near infrared (NIR) spectroscopy, is proposed. Since the efficiency of milk-to-cheese transformation depends on the total amount of casein, as well as on the relative proportions of the different types of caseins, it is desirable to quantify not only protein, fat and lactose, as is normally done routinely in the cheese industry and milk recording schemes, but also total casein, αs-, β- and k-caseins. Quantities of these main components have been measured in milk samples of three Spanish breeds of goats, using traditional chemical, electrophoretical and densitometric laboratory methods in order to produce NIR calibrations for total protein, total casein, casein fractions (αs-, β- and k-caseins), fat and lactose. Low standard errors and high coefficients of determinations have been obtained for the calibrations and validations. Goat's milk spectra are described, and the contribution of different components to the observed pattern is discussed. Due to the low cost, facility and rapidity of the analyses after the spectrophotometer has been calibrated for each milk component, the use of near infrared spectroscopy becomes a suitable tool to analyse large numbers of samples and, therefore, very suitable for dairy goat recording schemes.
Spectral Comparison of Ruminant Feeds Originating from Mediterranean Regions
Authors: Lister S.J. , Dhanoa M.S. , Ebenezer W. , Lopez S. , France J.
Published: May 2009

The potential of near infrared (NIR) spectroscopy and multivariate statistical techniques for the identification of new feed resources for ruminants was examined. Fifty diverse Mediterranean feeds including cereal fodder, legume fodder, vetch fodder, permanent meadow hay, cereal straw, legume straw, sugar beet root by-products, concentrates and agricultural by-products were used in this study. Principal component analysis and hierarchical cluster analysis were used to examine the distribution and inter-relationships between the different feeds. Overlap was observed between the different categories of feeds and several concentrate samples and by-products appeared at the extremes of the population. Spectral regions characteristic of fats and oils were associated with the discrimination. NIR spectra may be used to highlight differences and differentiate between different ruminant feeds. Qualitative analysis allows for comparison of samples on the basis of their spectral chemistry alone.
Prediction of the Neuro-Toxin Beta-N-Oxalyl-Amino-L-Alanine in Lathyrus Species, Using near Infrared Reflectance Spectroscopy
Authors: El-Haramein F. Jaby , Moneim A. Abd-El , Nakkoul H. , Williams P.C.
Published: May 2009

Grasspea or chickling vetch ( Lathyrus spp.) is a common food legume, widely grown and eaten in northern India, Bangladesh, Pakistan, Nepal and Ethiopia. It contains the neurotoxin beta-N-oxalyl-amino-L-alanine (BOAA), which can cause the disease known as “neuro-lathyrism”, an irreversible paralysis of the lower limbs, if BOAA-rich seeds form a large proportion of the diet. Lathyrus is a drought-tolerant crop, and ICARDA seeks to breed high-yielding lines that are low in BOAA. Conventional methods for determination of BOAA are time-consuming, expensive, and not practicable for screening large numbers of genotypes. Near infrared (NIR) reflectance spectroscopy offers a rapid, inexpensive method of analysis. Application of NIR reflectance spectroscopy to the prediction of BOAA in Lathyrus has been achieved by developing NIR reflectance spectroscopy equations involving 88 samples, which represented three species: L. sativus, L. cicera and L. ochrus. Both intact and ground seeds were studied. Content of BOAA ranged from 0.09 to 0.83%. Seeds of L. cicera were significantly lower than those of the other two species. The best results were obtained from whole seeds, using multiple linear regression. The standard error of prediction of 0.05% and coefficient of determination ( r2) of 0.94 are considered quite adequate for use in the Lathyrus breeding programme.
Application of near Infrared Spectroscopy in the Sugar Industry
Authors: Salgó A. , Nagy J. , Mikó É. , Boros I.
Published: May 2009

Raw materials, technological processes, intermediers and by-products of sugar industry have been characterized by near infrared (NIR) spectroscopy. Various sample preparation and spectroscopic methods were compared in order to optimize the measurement conditions of different types of samples. Sugar beet quality parameters were investigated in raw and deep frozen brei form and it was concluded that dry matter and sugar content of samples can be detected with good accuracy (SD = 0.3 – 0.4%) using standard thawing method and special sample holder. Inspite of big sample set (N = 200) with broad variation in alpha-amino nitrogen it was not found acceptable correlation between spectroscopic data and alpha-amino nitrogen content of sugar beet. Raw and purified (filtered, saturated) thin and thick juices and diluted massecuites were investigated using transmission method respectively. Brix value (dry matter) and sugar content, as well as colour of juices were measured with acceptable accuracy but the calibration of purity value showed high standard error. Selected and combined calibrations were developed for six different technological intermediers in three different factories. Chemical composition of molasses (Brix, sugar content, purity) were also measued by NIR using an optimalized sample preparation method. It was concluded that some of the conventional analysis methods (ICUMSA) can be substituted with NIR measurements where a significant reduction was observed in dangerous reagents (lead acetate) and labour-costs.
Assessment of the Pulpwood Quality of Standing Trees Using near Infrared Spectroscopy
Authors: Schimleck L. R. , Michell A. J. , Raymond C. A. , Muneri A.
Published: May 2009

In Australia, considerable effort has been directed at improving the pulp yield of plantation grown trees through tree breeding programs. However, an improvement in pulp yield relies on the assessment of large numbers of trees. Traditional methods of assessment are expensive, time consuming and destructive, inhibiting their use. Cores can be extracted non-destructively from standing trees using TRECOR, a handheld motor driven drill. The cores are milled, their near-infrared spectra obtained and pulp yield estimated using an appropriate calibration model. The height at which the core is taken is very important. It must represent the whole tree and sampling must be easy and practical.

The longitudinal and radial (within-tree) variation of pulp yield for 15 Eucalyptus nitens trees was examined using near-infrared (NIR) spectroscopy. The trees were taken from three families (five trees per family) selected for giving high, medium and low pulp yields respectively. Three trees (one from each family) were examined in detail. Maps of within-tree variation of pulp yield were developed. Pulp yield was found to be highly variable within individual trees and between trees of the same family. The yield of samples from 10% of tree height (approximately 2.2 m) gave the best correlation with whole-tree yield. Samples from 5% of tree height (approximately 1.1 m) gave a slightly lower correlation but provided a more convenient sampling height.

Ten Eucalyptus globulus and ten E. nitens trees growing on five sites in Australia were used to examine the longitudinal variation of pulp yield. Trees from sites in Tasmania, Western Australia and Victoria were sampled. The optimal sampling height for E. globulus was 1.1 m. No single sampling height could be recommended for E. nitens due to large site effects.
Application of near Infrared Spectroscopy for the Quantification of Quality Parameters in Selected Vegetables and Essential Oil Plants
Authors: Schulz H. , Drews H.-H. , Quilitzsch R. , Krüger H.
Published: May 2009

The use of near-infrared (NIR) spectroscopy for the prediction of the essential oil content and composition in various umbelliferae genotypes was investigated. Furthermore an NIR method was developed for the quantification of total carotenoids and sugars present in different carrot varieties. Applying partial least square algorithm very good calibration statistics ( SECV, R2) were obtained for the prediction of the essential oil content in fennel (0.47, 0.83), caraway (0.29, 0.93), dill (0.30, 0.96) and coriander (0.29, 0.93). Satisfactory calibration results were received for the NIR determination of total carotenoids (1.54, 0.80) and of saccharose(0.74, 0.76) in carrots. The performed study demonstrates that NIR can be used to rapidly and accurately predict secondary metabolites such as carotenoids, anethole, fenchone, estragole, limonene and carvone occurring in vegetables and in fruits of various essential oil plants.
Factors Affecting the Measurement of Hardness by near Infrared Reflectance Spectroscopy of Ground Wheat
Authors: Brown G.L. , Curtis P.S. , Osborne B.G.
Published: May 2009

An intercomparison of the AACC hardness score based on measurement of reflectance at 1680nm and 2230nm has shown that its repeatability and reproducibility are proportional to the score. A linear relationship between hardness score and grain moisture content was confirmed for hard but not for soft wheat varieties. For both hard and soft varieties, the hardness score was found to increase with increasing grain protein content but this effect was not consistent across two different growing seasons.
Qualitative Analysis for Automated Process Control
Authors: Länzlinger M. , Zilian A.
Published: May 2009

Many industrial processes use in-process analytics to achieve reproducibly high product quality. During a batch distillation, for example, the quality of the product goes through an optimum and the main fraction can be collected when the concentration of all by-products drops below a critical value. The NIR spectra we obtain from such distillations show a systematic change with product quality. A quantitative model would require tens of samples for each by-product. We find that changes of concentrations of many by-products are highly correlated and there is only little variability in the data. This is not enough to extract the linearly independent contributions of each by-product. Therefore a qualitative analysis is made.
A near Infrared Spectroscopic Sensor for the Monitoring of Brewing Processes
Authors: Eberl R. , Parthey B. , Wilke J.
Published: May 2009

The use of near infrared (NIR) analysis in the on-line process control of beer production (brewing) is exemplary reviewed. The real-time monitoring of both the mashing and fermentation processes appears to be an interesting but still unsolved problem, mainly due to the high and varying content of solid particles in the respective fluids. Intrinsic sensors, based on the effect of Attenuated Total Reflection, offer a possibility for even in-line measurements in such cases. U-shaped intrinsic sensors were fabricated of fused silica rods with a diameter of 3 mm and coupled to a NIR spectrometer via two fibre bundles. The sensor spectra turned out to be similar to transmission spectra of an optical pathlength of about twenty micrometers, confirming theoretical values obtained by an extended raytracing calculation. Spectra of brewing fluids were taken during the mashing and fermentation process, respectively, and evaluated by PLS. The sensor performance allows to monitor the progress of both processes in terms of the sugar and the ethanol production, respectively. However, further work is necessary to realise a proper industrial sensor.
Intrinsic near Infrared Sensor for the Determination of the Drainage Behaviour of Aqueous Detergent Solutions
Authors: Eberl R , Wilke J
Published: May 2009

Surfactants, detergents or tensides are synonyms for substances that, even at low concentrations, can drastically alter the interfacial properties of a multiphase system. Their main application fields—among many others—are cleaning processes in households, trade and industry. A certain substance-specific concentration (c.m.c.) is generally considered to be optimal for these applications. However, the fast and inexpensive determination of tenside concentrations is still a difficult task. Our approach to this problem is based on the fact that the draining behaviour of aqueous solutions on hard surfaces depends strongly on the actual concentration of detergents. Near the critical micelle concentration a stable fluid film remains on the wetted surface. The use of optic-intrinsic sensors in the NIR allows the detection of these changes in a straightforward manner by monitoring the sensor response after retrieving the sensor from the sample liquid. A potential application of this sensor principle is expected for controlling the detergent addition mainly in large-scale cleaning devices. This would be of both economical and ecological advantage.
A Novel, Rapid Scan Spectrophotometer for near Infrared Spectroscopy
Authors: Schmidt Werner
Published: May 2009

An innovative rapid scan monochromator so far routinely utilized in the visible wavelength range has been shown to be adaptable to the near infrared spectral region, as well. The number of optical and mechanical components is reduced to a minimum resulting in excellent light-throughput, a low stray-light level, low cost, compactness and rigidity. The spectrometer has been designed to allow all kinds of spectral measurements such as absorption, transmission, fluorescence and reflection in a single beam mode. A computer-program allowing data acquisition, control and calibration functions as well as real time averaging and life display of spectra on the computer screen has been developed.
Detection of Inorganic Wood Preservatives on Timber by near Infrared Spectroscopy
Authors: Feldhoff Roger , Huth-Fehre Thomas , Cammann Karl
Published: May 2009

The recycling of waste wood causes great problems due to the variety of toxic wood preservatives, varnishes and paints used. The fast and reliable distinction and sorting of treated and untreated wood on demolition sites could open new ways of wood recycling, e. g. for the production of chip boards. For this purpose, prepared wood samples treated with inorganic wood preservatives (arsenic, boron, copper salts) were investigated by near infrared-spectroscopy. In most cases, treated wood samples could be distinguished from untreated ones. Furthermore the type of wood preservative could be identified. The observed spectral features are electronic absorption bands and changes in the OH–band due to interaction with salt molecules.