• YAKHAK HOEJI
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• v.47 no.5
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• pp.261-265
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• 2003

Near-infrared (NIR) system was used to determine rapidly and simply indomethacin in buffer solution for a dissolution test of tablets and capsules. Indomethacin standards were prepared ranging from 10 to 50 ppm using the mixture of phosphate buffer (pH 7.2) and water (1 : 4). The near-infrared (NIR) transmittance spectra of indomethacin standard solutions were collected by using a quartz cell in 1 mm and 2 mm pathlength. Partial least square regression (PLSR) was explored to develop calibration models over the spectral range 1100∼1700 nm. The model using 1 mm quartz cell was better than that using 2 mm quartz cell. The PLSR models developed gave standard error of prediction (SEP) of 0.858 ppm. In order to validate the developed calibration model, routine analysis was performed using another standard solutions. The NIR routine analysis showed good correlation with actual values. Standard error of prediction (SEP) is 1.414 ppm for 7 indomethacin samples in routine analysis and its error was permeable in the regulation of Korean Pharmacopoeia (VII). These results show the potential use of the real time monitoring for indomethacin during a dissolution test.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3122-3122
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• 2001

Documented quality control plays a vital role I the production of technical “Depth filter” sheets used in industries such as Beverage and pharmaceutical. Depth filter sheets which can be up to several millimeters thick are stacker in plate and frame filter systems. They are the core of stainless steel filter systems which can be up to several meters high. FT-NIR Spectroscopy has many potential applications in the whole production line of filter sheets. Raw materials such as different types of cellulose pads, white powdery fillers (e.g. Kieelgur, Perlite) or liquid chemicals such as wet-strength agents we, with the help of NIR, easy to identify. NIR can also determine physical parameters such as particle size, essential for the filtration behavior. FT-NIR can be used for the quality parameters of the final product. Moisture and permeability can be determined, and with the help of the speed of this NIR method it is possible to correct possible faults quickly in the production process. Waste production can be minimized which is good for both the product profitability and the environment. Further tests have shown that it is also possible to use NIR on-line in the production area, to check the concentrations and the homogeneity of the paper suspension consisting of cellulose fibres, fillers and additives.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1124-1124
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• 2001

CARNAC is a procedure for obtaining quantitative analysis of a sample by comparison of the NIR spectra of the unknown sample with a database of a large number of samples with NIR spectral and compositional data. The method depends on the compression of the NIR database followed by a modification of the compressed data which emphasizes the required analyte. The method identifies a few very similar samples and the value of the required analyte is calculated from a weighed average of the analyte values for the selected similar samples. The method was originally described at Chambersburg IDRC in 1986 and in the Proceedings of the FT Conference of 1987. This contribution will describe recent work on utilising new methods for both compression and modification.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1257-1257
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• 2001

Fourier transform near infrared (FT-NIR) spectroscopy was used as a rapid method to measure the $^{o}Brix$ content and to discriminate between different must samples in terms of their fee amino nitrogen (FAN) values. FT-NIR spectroscopy was also used as a rapid method to discriminate between Chardonnay wine samples in terms of the status of the male-lactic fermentation (MLF). This was done by monitoring the conversion of malic to lactic acid and thereby determining whether MLF has started, is underway or has been completed followed by classification of the samples. Furthermore, FT-NIR spectroscopy was applied as a rapid method to discriminate between table wine samples in terms of the ethyl carbamate (EC) content. EC in wine can pose a health threat and need to be monitored by determining the EC content in relation to the regulatory limits set by the authorities. For each of the above mentioned parameters, $QUANT+^{TM}$ methods were built and calibrations derived and it was found that a very strong correlation existed in the sample set for the FT-NIR spectroscopic predictions of $^{o}Brix$ (r = 0.99, SECV = 0.306), but the correlations for the FAN (r = 0.61, SECV = 272.1), malic acid (r = 0.58, SECV = 1.06), lactic acid (r = 0.51, SECV = 1.14) and EC predictions (r = 0.47, SECV = 3.67) were not as good. Soft Independent Modeling by Class Analogy (SIMCA) diagnostics and validation was applied as a sophisticated discrimination method. The must samples could be classified in terms of their FAN values when SIMCA was applied, obtaining results with recognition rates exceeding 80%. When SIMCA diagnostics and validation were applied to determine the progress of conversion of malic to lactic acid and the EC content, again results with recognition rates exceeding 80% were obtained. The evaluation of the applicability of FT-NIR spectroscopy measurement of FAN, $^{o}Brix$ values, malic acid, lactic acid and EC content in must and wine shows considerable promise. FT-NIR spectroscopy has the potential to reduce the analytical times considerably in a range of measurements commonly used during the wine making process. Where conventional FT-NIR calibrations are not effective, SIMCA methods can be used as a discriminative method for rapid classification of samples. SIMCA can replace expensive, time-consuming, quantitative analytical methods, if not completely, at least to some extent, because in many processes it is only needed to know whether a specific cut off point has been reach or not or whether a sample belongs to a certain class or not.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1151-1151
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• 2001

The international coffee trade is conducted almost exclusively with green coffee. The main coffee producing countries include Brazil, Columbia, Indonesia, Mexico and the Ivory Coast. About 99 % of the coffee grown throughout the world belong to two coffee plant varieties that are commonly known as Arabica and Robusta. The quality of green coffee can be assessed according to several ISO standards (1,2,3,4,5). However, no official international standards for the authenticity of green coffee have been issued. It is important to know the country of origin of the coffee for the purposes of fair international trade. The geographic origin of the coffee is often stated on the label of coffee products such as speciality roasted and soluble coffees. Near Infrared Spectroscopy (NIR) is an accepted technique for quantitative analysis of various parameters in routine QC analysis of food products. It would appear to be a promising candidate as a tool for identification of green coffee origin and numerous feasibility studies have appeared in the literature on its use for soluble, roasted and green coffee variety identification as well as identification of arabica or robusta coffees. NIR spectrophotometers when configured in the reflectance mode are able to perform a complete profile of the NIR spectrum on whole beans. The data can then be interpreted by discriminant chemometrics data analysis. This is the approach used in the present study.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4104-4104
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• 2001

Milk somatic cell count (SCC) is a recognized indicator of cow health and milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm to measure SCC content of cow milk was investigated. A total of 196 milk samples from 7 Holstein cows were collected for 28 days, consecutively, and analyzed for fat, protein, lactose and SCC. Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in a wavelength range from 1100 to 2500 nm. The calibration for logSCC was performed using partial least square (PLS) regression and different spectral data pretreatment. The best accuracy of determination was found for equation, obtained using smoothed absorbance data and 10 PLS factors. The standard error of calibration was 0.361, calibration coefficient of multiple correlation 0.868, standard error of prediction for independent validation set of samples 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. The accuracy of logSCC determination by NIR spectroscopy would allow health screening of cows, and differentiation between healthy and mastitic milk samples. When the spectral information was studied it has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. In the case of mastitis, when the disease occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1258-1258
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• 2001

Estimation of sugar and reducing sugar content in molasses is very important task in sugar refineries. Conventional methods of determination of sugar content in molasses samples are highly time consuming and employ hazardous chemicals. Due to the physical properties of molasses, probability of error in conventional analytical techniques is high. These methods have proven to be inefficient for a process control in any sugar industry. Hence development of a rapid, inexpensive, physical and also accurate method for sugar determination in molasses will be highly useful. Near Infrared spectroscopy is being widely used worldwide as an analytical technique in food industry. The technique offers the advantage of being non-destructive and rapid. The present paper highlights the potential of near infrared reflectance spectroscopy as a rapid and automated analytical technique for determination of sugar and reducing sugar content in molasses. A number of molasses samples were collected during and after the sugar season from Havana Sugar Industry, Havana. The samples were chosen so as to obtain a wide range of concentration of sugar and reducing sugars. This was done in order to achieve a good calibration curve with widely spread data points. These samples were scanned in the region of 1100 - 2500 nm in diffuse reflectance mode. An indigenous ELICO NIR spectrophotometer, modified according to the requirements of sugar industry was used for this purpose. Each sample was also analyzed simultaneously by standard chemical methods. Chemical values were taken as reference for near infrared analysis. In order to obtain the most accurate calibration for the set of samples, various mathematical treatments were employed. Partial Least Square method was found to be most suitable for the analysis. A comparison is made between the actual values (chemical values) and the predicted values (NIR values). The actual values agree very well with the predicted values showing the accuracy of the technique. The validity of the technique is checked by predicting the concentration of sugar in unknown molasses samples using the calibration curve. The present investigation assesses the feasibility of the technique for on-line monitoring of sugars present in molasses in sugar industries.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4112-4112
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• 2001

The feasibility of NIR spectroscopy as a quick and nondestructive method for quality control of uniformity of coating thickness of pharmaceutical tablets was investigated. Near infrared spectra of a set of pharmaceutical tablets with varying coating thickness were measured with a diffuse reflectance fiber optic probe connected to a Broker IFS 28/N FT-NIR spectrometer. The challenging issues encountered in this study included: 1. The similarity of the formulation of the core and coating materials, 2. The lack of sufficient calibration samples and 3. The non-linear relationship between the NIR spectral intensity and coating: thickness. A peak at 7184 $cm^{-1}$ was identified that differed for the coating material and the core material when M spectra were collected at 2 $cm^{-1}$ resolution (0.4 nm at 7184 $cm^{-1}$). The study showed that the coating thickness can be analyzed by polynomial fitting of the peak area of the selected peak, while least squares calibration of the same data failed due to the lack of availability of sufficient calibration samples. Samples of coal powder and solid pieces of coal were analyzed by FT-NIR diffuse reflectance spectroscopy with the goal of predicting their ash content, percentage of volatile components, and energy content. The measurements were performed on a Broker Vector 22N spectrometer with a fiber optic probe. A partial least squares model was constructed for each of the parameters of interest for solid and powdered sample forms separately. Calibration models varied in size from 4 to 10 PLS ranks. Correlation coefficients for these models ranged from 86.6 to 95.0%, with root-mean-square errors of cross validation comparable to the corresponding reference measurement methods. The use of FT-NIR diffuse reflectance measurement techniques was found to be a significant improvement over existing measurement methodologies in terms of speed and ease of use, while maintaining the desired accuracy for all parameters and sample forms.(Figure Omitted).

• Food Science of Animal Resources
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• v.40 no.1
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• pp.96-105
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• 2020

The appearance of white striations over breast meat is an emerging and growing problem. The main purpose of this study was to employ the reflectance of visible-near infrared (VIS/NIR) spectroscopy to differentiate between normal and white striped turkey breasts. Accordingly, 34 turkey breast fillets were selected representing a different level of white striping (WS) defects (normal, moderate and severe). The findings of VIS/NIR were analyzed by principal component (PC1) analysis (PCA). It was found that the first PC1 for VIS, NIR and VIS/NIR region explained 98%, 97%, and 96% of the total variation, respectively. PCA showed high performance to differentiate normal meat from abnormal meat (moderate and severe WS). In conclusion, the results of this research showed that VIS/NIR spectroscopy was satisfactory to differentiate normal from severe WS turkey fillets by using several quality traits.

• Journal of The Korean Society of Grassland and Forage Science
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• v.9 no.3
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• pp.163-167
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• 1989

Near infrared reflectance spectroscopy (NIRS) analysis of commercial farm alfalfa hay for crude prowin (CP), neutral detergent fiber(NDF), and acid detergent fiber(ADF) was compared with wet chemistry results. There were no differences between NIRS and wet chemistry results in CP and ADF content, but there were differences (P <.05) between NIRS and wet chemistry results for sample No.2, 4, 5 in NDF content.