• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1051-1051
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• 2001

In 1989, at the 2nd ICNIRS Meeting in Tsukuba, I projected certain directions for NIR technology would take in the future. Among those projections were: (1) An inrush of companies producing FT-NIR instruments. (2) Hybrid NIR Systems (3) Hand-held NIR Technology. All three thrusts have resulted in numerous commercial offerings over the last 12 years Hand-held technology for all fields is growing at an astonishing rate. To date, NIR work at North Carolina State University has produced four (4) hand-held NIR units for: (1) Nicotine and Moisture in tobacco, (2) Vanillin and Moisture in Vanilla Beans, (3) Protein, Moisture and Nitrogen in plant tissue, (4) Chlorophyll and Moisture in Growing Plants: A NIR Spectrometer for Developing Countries. This paper will discuss these developments, including design and performance data.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1127-1127
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• 2001

The transfer of predictive models using various chemometric techniques has been reported for FTNIR and scanning-grating based NIR instruments with respect relatively dry samples (<10% water). Some of the currently used transfer techniques include slope and bias correction (SBC), direct standardization (DS), piecewise direct standardization (PDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT) and application of neural networks. In a previous study (Greensill et at., 2001) on calibration transfer for wet samples (intact melons) across silicon diode array instrumentation, we reported on the performance of various techniques (SBC, DS, PDS, double window PDS (DWPDS), OSC, FIR, WT, a simple photometric response correction and wavelength interpolative method and a model updating method) in terms of RMSEP and Fearns criterion for comparison of RMSEP. In the current study, we compare these melon transfer results to a similar study employing pairs of spectrometers for non-invasive prediction of soluble solid content of peaches.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2102-2102
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• 2001

Near infrared, diffuse reflectance spectroscopy has shown significant potential for in vitro and in vivo assessment of metabolic status. However, the complexity of living samples can lead to ambiguous results. This presentation will focus on methods that provide controls for scattering and absorption estimation in tissue. For robust estimations, normalization procedures will be shown which can greatly improve interpretability of results. Normalization based on time, location and spectral property will be shown with data from models, tissue phantoms and in vivo measurements. In particular, interpretation of NIR spectra associated with major respiratory constituents will be examined. Measurement of constituents such as hemoglobin, myoglobin, tissue edema, and lactate will be shown. Results suggest that NIR may provide a valuable tool for physiological monitoring in critical care research and practice.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1011-1011
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• 2001

In general, NIR reflectance spectra (whether recorded using log(1/R) or the Kubelka-Munk function) are not linear functions of the concentration of the absorbers which we are measuring. There are several causes for this non-linearity, the most commonly cited one being front surface reflection. However, non-linearity also arises from the effects of particle size, sample thickness, void fraction, and experimental arrangement. In this talk, we will attempt to isolate the effects of the various causes, and show the effects of each, using both theoretical calculations and actual data. The listener should then be able to assess where we stand in our quest to produce “linear” data through pre-processing and/or alternate collection schemes.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1628-1628
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• 2001

Near infrared (NIR) spectroscopy is a powerful technique for non-destructive analysis that can be obtained in a wide range of environments. Recently, NIR measurements have been utilized as probe for quantitative analysis in agricultural, industrial, and medical sciences. In addition, it is also possible to make practical application on NIR for molecular structural analysis. In this work, Fourier transform near infrared (FT-NIR) measurements were carried out to utilize extensively in the relative amounts of different secondary structures were employed, such as Iysozyme, concanavalin A, silk fibroin and so on. Several broad NIR bands due to the protein absorption were observed between 4000 and $5000\;^{-1}$. In order to obtain more structural information from these featureless bands, second derivative and Fourier-self-deconvolution procedures were performed. Significant band separation was observed near the feature at $4610\;^{-1}$ ,. Particularly the peak intensity at $4525\;^{-1}$ shows a characteristic change with thermal denaturation of fibroin. The structural information can be also obtained by mid-IR and CD spectral. Correlation of NIR spectra with protein structure is discussed.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1525-1525
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• 2001

Non-destructive determination of soluble solids(Brix) in harvested fruits using near infrared(hereafter, NIR) spectroscopy has been reported by many researchers. We have just reported on non-destructive estimation of Brix in harvested melons using a NIR Systems Model 6500 spectrophotometer(Ito et al., 2000). There is a melon cultivar that is difficult to judge the harvest time from the external appearance. If we can determine Brix in growing fruits non-destructively in the field, immature fruits will not be harvested. A portable m spectrophotometer for field use has been just developed by Kubota Corporation. The spectral data of growing melons were measured by the portable spectrophotometer. A commercial program was used for multiple linear regression analysis. Brix in growing melons could be estimated by a multiple regression equation calibrated with harvested melons. Absorbances of 906 and 874 nm were included as the independent variables in the multiple regression equation, and these wavelengths are key wavelengths for non-destructive Brix determination.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1288-1288
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• 2001

X-ray powder diffraction (XRD) is utilized for determination of polymorphism in crystalline organic materials. Though convenient to use in a laboratory setting, XRD is not easily adapted to in situ monitoring of synthetic chemical production applications. Near-Infrared spectroscopy (NIR) can be adapted to in situ manufacturing schemes by use of a source/detector probe. Conversely, NIR is unable to conclusively define the existence of polymorphism in crystalline materials. By combining the two techniques, a novel simultaneous NIR/XRD instrument has been developed. During material's analysis, results from XRD allow for defining the polymorphic phase present, and NIR data are collected as a fingerprint for each of the observed polymorphs. These NIR fingerprints will allow for the development of a library, which can be referenced during the use of a NIR probe in manufacturing settings.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1282-1282
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• 2001

Near Infrared (NIR) spectra has long been used in industry to monitor rates of reactions via calculation of analyte concentrations. However, the kinetic information is inherent in the data through spectral ratios. Two-dimensional correlation spectroscopy (2D-COS) is a spectral method that is based on changes (e.g. concentration) in time and is therefore uniquely suited for reaction monitoring. This method is especially useful in the understanding of how the reaction(s) proceeds. We will show the application of 2D-COS to synthetic kinetic data from different reaction orders to illustrate the method. We will then show application to real reactions of various orders. Finally, we will illustrate how 2D-COS will be of specific interest to developing optimized industrial reactions.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1275-1275
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• 2001

The pH value of grass silages is one important parameter to determine the quality of the forages. In an attempt to use NIRS spectra taken for other quality parameter of grass silage it has been shown that a good correlation between NIR spectra of the dried forage and pH value of the fresh forage could be determined. Further investigations revealed that the B coefficients of the pH value calibration were almost the same as the B coefficients of the sugar calibration multiplied with -1. And indead the pH value - in the fresh sample material - of the calibration set is strongly correlated with the sugar concentration - in the dried sample material. It is concluded that next to scientific tools in research the scientist and the user of NTRS equippment has to scrutinze his own work. Examples are given. NIRS is a powerfull technique, but pitfalls are present in surplus.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1521-1521
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• 2001

The objective of the research being presented was to construct and calibrate a spectrometer for the analysis of single kernels of corn. In light of the difficulties associated with capturing the spatial variability in composition of corn kernels by single-beam spectrometry, a hyperspectral imaging spectrometer was constructed with the intention that it would be used to analyze single kernels of corn for the prediction of moisture and oil content. The spectrometer operated in the range of 750- 1090 nanometers. After evaluating four methods of standardizing the output from the spectrometer, calibrations were made to predict whole-kernel moisture and oil content from the hyperspectral image data. A genetic algorithm was employed to reduce the number of wavelengths imaged and to optimize the calibrations. The final standard errors of prediction during cross-validation (SEPCV) were 1.22% and 1.25% for moisture and oil content, respectively. It was determined, by analysis of variance, that the accuracy and precision of single-kernel corn analysis by hyperspectral imaging is superior to the single kernel reference chemistry method (as tested).