• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.2
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• pp.88-93
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• 2003

NIR spectroscopic analysis was used for the measurement of deproteinization and deacetylation to apply the merits of NIR spectroscopic analysis to the quality management in the process of chitin and chitosan production. In measuring squid pen and red snow crab shell, which are raw materials of chitin and chitosan by NIR there were typical peaks in 1200 nm, 1510 nm, 2050 nm and 2180 nm. Squid pen had somewhat higher peak than red snow crab shell. In producing chitin, amount of protein was decreased. Measuring it by NIR, reduction of protein caused by deproteinization was identified in producing chitin. Chitosan is a derivative material made from chitin by processing the deacetylation. During this processing, acetyl groups were removed and amide bends were appeared. From NIR spectra, peaks at 1530 nm and 2030 nm indicated amide II peak of chitosan, and these peaks were used for identifying the differences of structure between chitin and chitosan. The error in measurement of nonidentified sample was below $1\%$ and the error in the standard curve was below 0.006. These errors were very low and the accuracy of NIR was considered to be superior to the existing methods.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• Journal of the Korean Wood Science and Technology
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• v.43 no.3
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• pp.304-310
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• 2015

The moisture content of sawdust must be measured accurately and controlled appropriately during storage and transportation because biological degradation could be caused by improper moisture. In this study, to measure the moisture contents of Larix kaempferi sawdust, the near-infrared reflectance spectra (Wavelength 1000-2400 nm) of sawdust were used as detection parameter. After acquiring the NIR reflection spectrum of specimens which were humidified at each relative humidity condition ($25^{\circ}C$, RH 30~99%), moisture content prediction model was developed using mathematical preprocessings (e.g. smoothing, standard normal variate) and partial least squares (PLS) analysis with the acquired spectrum data. High reliability of the MC regression model with NIR spectroscopy was verified by cross validation test ($R^2$ = 0.94, RMSEP = 1.544). The results of this study show that NIR spectroscopy could be used as a convenient and accurate method for the nondestructive determination of moisture content of sawdust, which could lead to optimize wood utilization.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1126-1126
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• 2001

The paper presented here is the initial part of a larger study, in which it was determined which quality parameters in cheese powder could already be predicted by NIR at an early stage in the process and which could only be predicted at the final stages of the process. This initial study was performed in order to establish the levels and nature of variation within and between batches such that the subsequent data collection could be tackled optimally. The perspectives evolved into more than was originally planned and revealed some interesting uses of NIR-technology. Cheese powder production starts as a batch process, where waste cheese from other dairies is melted down in a vat. The process then turns into a continual process as the vat is emptied and the melted cheese is then filtered, homogenized, pasteurized and finally spray dried. Between each batch the powder is to a greater or lesser degree a mixture of 2 batches. This paper is divided into 2 aspects, one regarding the optimization of sampling time and the other is a study of process dynamics. Optimizing sampling time This initial study included 9 powder samples from 9 different batches produced during one day. The raw materials for the batches were chosen with the aim of creating a relatively high level of variation in the data. The total of 81 samples were taken out at regular intervals and spectra were collected on a NIR-systems 6500 instrument. The subsequent reduction of the data by PCA to score values shows the power of NIR as a tool to determine not only when samples are representative of a certain batch, but also which batches are stable enough to include in a further study. Studying process dynamics To take this experiment a step further 1 of the 81 samples were sent to the laboratory for further analyses. The samples were chosen on the criteria that they covered the spectral variation in the dataset. These samples were analysed for 4 chemical components and 5 physical attributes, which are essential for describing the quality of the product. The latent structure of the 7 samples, using the chemical and physical variables, is totally comparable to the latent structure of the NIR spectra. This outcome makes it possible to describe the dynamics of one day's production both chemically and physically with relatively little resources. Additionally it raises the question as to whether reference values are needed, as the latent structure of the NIR-spectra appears to be sufficient in providing information on the quality of the product. To be able to use NIR in this way would require defining quality limits in the principal component space as opposed to each of the reference values. The potential of NIR applied in an explorative fashion with batch processes opens a whole new gateway for the use of this technology. This study explains yet again after so many years in the field “why I'm crazy about NIR!”.

• Journal of the Korean Applied Science and Technology
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• v.16 no.2
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• pp.155-161
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• 1999

Red pepper powder (Capsicum annum L.) is an important seasoning as a kimchi ingredient in korea and most korean consumer tend to eat the korean red pepper powder as the better than other oriental country such as China. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of red pepper powder. The objective of this study is to determine if NIR technique could be used to discriminate between the korean red pepper powder and non-korean red pepper powder according to seed content and maxing ratio in red pepper powder by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographical origin of red pepper powder by near infrared spectroscopy and chemometrics were performed. It has been observed discriminant analysis with PLS is adequate to determinate the geographical origin of red pepper powder. It tend to difficult the discrimination of geographical origin according to increase the seed content of red pepper powder. The accuracy of discrimination in mixed red pepper powder was range from 95.2% to 100%.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1512-1512
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• 2001

The University of Cordoba conducts since 1991 a breeding program to obtain new olive cultivars from intraspecific crosses. The objective is to obtain new early bearing and high-quality cultivars. In plant breeding, many seedlings must be tested to increased the chance of getting desirable genotypes. Therefore, fast, cheap and accurate methods of analysis are necessary. The conventional laboratory techniques are costly and time-consuming. Near Infrared Spectroscopy (NIRS) can satisfy the characteristics requested by plant breeders and offers many advantages such as the simultaneous analysis of many traits and cheap cost. The objective of this work was to asses the performance of NIRS to estimate oil fruit components (fruit weight, flesh moisture, flesh/stone ratio and oil flesh content in dry weight basis) and fatty acid composition in olive fruit. Genotypes from reciprocal crosses between ‘Arbequina’, ‘Frantoio’ and ‘Picual’ cultivars have been used in this study. A total of 287 samples, each from a single plant, were scanned using a DA-7000 Diode Array VIS/NIR Analysis System (Perten Instruments), which covers the visible and NIR range from 400-1700 nm. All samples were analysed for fatty acid composition (gas chromatography) and 220 for oil fruit components (oil content by nuclear magnetic resonance), 70% and 30% of samples were randomly assign for the calibration and validation sets respectively. The preliminary results shows that calibration for palmitic, oleic and linoleic acids were highly accurate with calibration and validation values of $r^2$ from 0.85 to 0.95 and 0.76 to 0.91 respectively. Calibration for palmitoleic and estearic acids were less accurate, probably because of the narrow range of variability available for these fatty acids. For the oil fruit components, calibration were high accurate for flesh moisture and oil flesh content in dry weight basis ($r^2$ higher than 0.90 in both calibration and validation sets) and less accurate for the other characteristics evaluated. The first results obtained indicate that NIRS analysis could be an ideal technique to reduce the cost, time and chemical wasted necessary to evaluate a large number of genotypes and it is accurate enough to use for pre-selecting genotypes in a breeding program.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.279.1-279.1
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• 2003

NIR reflectance spectroscopy, using a fiber-optic probe was used to determine rapidly and non-destructively the content of ambroxol in intact ambroxol 30 mg (nominal content 12.5％ m/m ambroxol) tablets by collecting NIR spectra in range 1100 - 1750 nm and using PLSR calibration method. The tablets (10.3 - 15.9％ m/m ambroxol, i.e., 82 - 127％ of the nominal label content) were used 7 calibration set and 5 validation set. (omitted)

• Korean Journal of Metals and Materials
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• v.46 no.2
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• pp.88-96
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• 2008

Thermal evaporated 10 nm-$Ni_{50}Co_{50}$/(70 nm-poly)Si films were deposited to examine the energy saving properties of silicides formed by rapid thermal annealing at temperature ranging from 500 to $1,100^{\circ}C$ for 40 seconds. Thermal evaporated 10 nm-Ni/(70 nm-poly)Si films were also deposited as a reference using the same method for depositing the 10 nm-$Ni_{50}Co_{50}$/(70 nm-poly)Si films. A four-point probe was used to examine the sheet resistance. Transmission electron microscopy (TEM) and X-ray diffraction XRD were used to determine cross sectional microstructure and phase changes, respectively. UV-VIS-NIR and FT-IR (Fourier transform infrared spectroscopy) were used to examine the near-infrared (NIR) and middle-infrared (MIR) absorbance. TEM analysis confirmed that the uniform nickel-cobalt composite silicide layers approximately 21 to 55 nm in thickness had formed on the single and polycrystalline silicon substrates as well as on the 25 to 100 nm thick nickel silicide layers. In particular, nickel-cobalt composite silicides showed a low sheet resistance, even after rapid annealing at $1,100^{\circ}C$. Nickel-cobalt composite silicide and nickel silicide films on the single silicon substrates showed similar absorbance in the near-IR region, while those on the polycrystalline silicon substrates showed excellent absorbance until the 1,750 nm region. Silicides on polycrystalline substrates showed high absorbance in the middle IR region. Nickel-cobalt composite silicides on the poly-Si substrates annealed at $1,000^{\circ}C$ superior IR absorption on both NIR and MIR region. These results suggest that the newly proposed $Ni_{50}Co_{50}$ composite silicides may be suitable for applications of IR absorption coatings.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1155-1155
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• 2001

The quality of agricultural products is very important factor for consumers. In Japan, quality is sometimes more important than cost. Usually, the quality of fresh food products is determined in terms of shape, color, size, etc. However, these indices are not always associated with taste, leaving consumers to complain. Recently, two types of the fruit quality meter (a tabletop type - K-FS200 and a portable type - K-BA100, Kubota Corp.) using NIR technology were introduced in Japan. A tabletop instrument is for post harvest use and a portable one is for precision agriculture use. The both meters use the NIR region from 600nm to 1000nm in the interactance mode to determine quality factors related to taste. The instruments can measure sugar content and acidity of such fruit as apples, tomatoes, tangerines and other fruits. The measurement is timely, nondestructive and precise. For example, the coefficient of variation (CV) is less than 6% for sugar in most fruits. The K-FS200 has been evaluated in supermarkets, grading facilities, and wholesalers in Japan. The introduction of the K-FS200) has drawn attention to taste quality and its use is becoming more popular. In addition, researchers or farmers are becoming interested in measuring product ingredient not only after harvest but also during growing in the field so that they can make intelligent judgements concerning soil amendments, such as fertilizers and water, employs the fiber probe for flexible measurement and is battery powered for field use. Design of the fruit quality meters will be discussed. Applications to fruit quality will be presented.