• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.852-862
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• 1996

This study was carried out to develop tools to detect defects of apple using machine vision. For the purpose, 6 kinds of frame for color images, R, G, B, h, S, and I frame, and a frame for near infra-red images (NIR frame) were tested first to select one which is useful to segment defect areas from apple images. After then, several methods to classify kind of defect for the segmented defect areas were developed and tested. Five kinds of apple defect -bruise , decay ,fleck worm hole and scar were investigated . The results are as follows: NIR frame was selected as the best one among the 7 kinds of image frame, and R, G and I frames showed favourable result to segment areas of apple defect. Various features of the segmented defect areas were measured to classify the defect areas. Eight kids of feature of the areas-size, roundness, axes length ratio, mean and variance of pixel values, variance of real part of spectrum, mean and variance of power spectrum resulted from spacial ourier transform were observed for the segmented defect areas in the selected 4 frames. then procedures to classify defects using the features were developed for the 4 frames and tested with 75-113 defects on apples. The test resulted that NIR and I frames showed high accuracies to classify the kind of defect as 77% and 76% , respectively.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2529-2532
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• 2003

The quality of agricultural products is represented a degree of freshness and a special qualify that has a close relation to commercial value. To grade tomatoes, it used to nondestructive equipment of a charge-coupled device(CCD) camera and near-infrared(NIR) spectrum analysis method. The NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. The CCD camera is used to measure external qualities like color and a size of tomatoes. This paper explaines the structure and movement of the automatic grade system and applies the algorithm for deformed tomtatoes and characteristics of tomatoes through image processing to the grade system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.325-333
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• 1996

This study was conducted to develop neural networks of predicting the sugar content of fruits based on the optical densities obtained from a spectrophotometer. Pear, apple and peach were used in investigating the feasbility of the developed neural networks as a nondestructive measurement. A spectrophotometer was used to measure the optical densities of test fruits. The neural networks suggested in this study consisted of multi-layers having one hidden layer and one output layer. The correlation coefficients between the predicted and the measured sugar content for most fruits were high. The neural networks using 2nd derivatives of optical density spectrum produced a better results in predicting the sugar content of fruits. This study contributed to develop a method for nondestructively predicting the sugar content of fruits.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.12a
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• pp.368-373
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• 1998

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2011.10a
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• pp.255-269
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• 2011

The purpose of study has to analyze with non destructive method for researching the tool that could be measured with the status of record written on Hanji speedily. Because the original record should be destructed for analyzing with previous method in the case of the paper record, it was to develop the tool based on non destructive method for overcoming such limit. The study was used with FT NIR (Fourier transform NIR) for analyzing the Hanji for being written and preserved. The FT NIR spectrometer that of NIR spectrometer has the better performance of precision and accuracy than dispersive NIR spectrometer was used. Also the wavelength of FT-NIR was measured with 12,500 to 4,000 $cm^{-1}$, and the integrating sphere as diffuse reflectance type was used for analyzing Hanji. The moisture and acidity (pH) of chemical factors as quality evaluated factor of Hanji was studied for the correlation of NIR spectrum. And then The NIR spectrum was pretreated for showing the coefficients of optimum correlation. MSC and First derivative of Savitzky - Golay was used as pretreated method, and the coefficients of optimum correlation were shown by PLSR(Partial least square regression). And the coefficients of optimum correlation were calculated by PLSR(Partial least square regression). The correlation coefficients of acidity had 0.92 on NIR spectra without pretreatment. Also the SEP of acidity was 0.24. And then The NIR spectra with pretreatment would have more good correlation coefficients ($R^2=0.98$) and more good SEP(=019) on acidity. Therefore the data of correlation coefficients ($R^2$) and SEP with pretreatment was shown to be superior. And NIR spectra data of first derivative had best linearity on the correlation coefficients ($R^2=0.99$) and also SEP(=0.45) was superior. Therefore the correlation coefficients and SEP of first derivative had better than those of NIR spectra of no pretreatment. As such result, it was possible to evaluate the record status of Hanji speedily with integrated sphere and NIR analyzer as non destructive method.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.5
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• pp.359-365
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• 2004

To study the lipid adsorption characteristic of chitosans with different molecular weights and the degrees of deacetylation, in vitro test and near-infrared (NIR) spectroscopic analysis have been performed for the measurement of lipid adsorption characteristics of chitosan. The degrees of deacetylation in chitosans were $70{\%},\;85{\%}\;and\;92{\%}$ at different deacetylation times (1 hr, 2 hrs, 3 hrs), respectively. The molecular weight of each chitosan was controlled by enzymatic hydrolysis, and then the molecular weight of the chitosan was 4 kDa. The bulk density, water holding capacity and fat binding capacity of each chitosan powder were $96.2-504.0{\%},\;374.4-1217.9{\%},\;and\;307.0-659.3{\%}$, respectively. The higher molecular weight of chitosan was exhibited the lower bulk density and the higher water and fat binding capacities. Bindinf capacities of chitosan powders to bile salts, cholesterol and linoleic acid were $41.2-63.3{\%},\;40.8-67.4{\%},\;42.6-72.6{\%}$, respectively. In NIR spectrum of lipid adsorbed chitosan the occurrence static eletronical binding between chitosan and lipid was identified by NIR spectrum peak induced from combination of carboxylic group in lipid and amino group in chitosan. In conclusion, the higher degree of deacetylation and molecular weight of chitosan showed the higher lipid binding capacity and the lipid adsorption of chitosan were occurred by combination of carboxylic group in lipids and amino group in chitosan.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1253-1253
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• 2001

The ability to accurately assess wine quality is important during the wine making process, particularly when allocating batches of wines to styles determined by consumer requirements. Grape payments are often determined by the quality category of the wine that is produced from them. Wine quality, in terms of sensory characteristics, is normally a subjective measure, performed by experienced winemakers, wine competition judges or winetasting panellists. By nature, such assessments can be biased by individual preferences and may be subject to day-to-day variation. Taste and aroma compounds are often present in concentrations below the detection limit of near infrared (NIR) spectroscopy but the more abundant organic compounds offer potential for objective quality grading by this technique. Samples were drawn from one of Australia's major wine shows and from BRL Hardy's post-vintage wine quality allocation tastings. The samples were scanned in transmission mode with a FOSS NIR Systems 6500, over the wavelength range 400-2500 ㎚. Data analysis was performed with the Vision chemometrics package. With samples from the allocation tastings, the best correlations between NIR spectra and tasting data were obtained with dry red wines. These calibrations used loadings in the wavelengths related to anthocyanins, ethanol and possibly tannins. Anthocyanins are a group of compounds responsible for colour in red wines - restricting the wavelengths to those relating to anthocyanins produced calibrations of similar accuracy to those using the full wavelength range. This was particularly marked with Merlot, a variety that tends to have relatively lower anthocyanin levels than Cabernet Sauvignon and Shiraz. For dry white wines, calibrations appeared to be more dependent on ethanol characteristics of the spectrum, implying that quality correlated with fruit maturity. The correlations between NIR spectra and sensory data obtained using the wine show samples were less significant in general. This may be related to the fact that within most classes in the show, the samples may span vintages, glowing areas and winemaking styles, even though they may be made from only one grape variety. For dry red wines, the best calibrations were obtained with a class of Pinot Noir - a variety that tends to be produced in limited areas in Australia and would represent the least matrix variation. Good correlations were obtained with a tawny port class - these wines are sweet, fortified wines, that are aged for long periods in wooden barrels. During the ageing process Maillard browning compounds are formed and the water is lost through the barrels in preference to ethanol, producing “concentrated” darkly coloured wines with high alcohol content. These calibrations indicated heaviest loadings in the water regions of the spectrum, suggesting that “concentration” of the wines was important, whilst the visible and alcohol regions of the spectrum also featured as important factors. NIR calibrations based on sensory scores will always be difficult to obtain due to variation between individual winetasters. Nevertheless, these results warrant further investigation and may provide valuable Insight into the main parameters affecting wine quality.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.220.2-220.2
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• 2003

Many interference in blood should be considered for non-invasive blood glucose level monitoring by near-infrared spectroscopy because blood glucose concentration is about 0.1% (w/v) in normal state. In this study, we investigated the influence of other blood components on blood glucose level monitoring by near-infrared spectroscopy. It carried out by newly developed portable type-NIR system (1100∼2200 nm). Spectrum features of NIR diffuse spectral data were investigated for some blood compnents powder such as hemoglobin, blood serum albumin, urea, uric acid, ascorbate, glucose, cholesterol and as adding glucose powder into other blood components powder mixture. (omitted)

• Proceedings of the Korean Society for Food Science of Animal Resources Conference
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• 2000.11a
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• pp.1-14
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• 2000

The Near Infrared region of the energy spectrum was first discovered by Hershel in the year 1800. The principles of NIR is based on light absorption of specific organic chemical bonds. The absorption at each wavelength is measured and a spectre is obtained. The spectre is then treated mathematically and with the absorption data is converted to absolute units via a calibration. In the last two decades it has developed dramatically. With the invention of computers and the ability to treat a large amount of data in a very short time the use of NIR for many different purposes has developed very fast. During the last decade with the aid of very powerful PC's the application of NIR technology has become even more widespread. Now or days development of very robust calibrations can be done in a relatively short time with a minimum of resources. The use of Near Infrared Spectroscopy (NIR) in the Meat industry is relatively new. The first installations were taken into operation in the 80ties. The Meat Industry in often referred to as rather conservative and slow to embrace new technologies, they stay with the old and proven methods. The first NIR instruments used by the Meat Industry, and most other industries, were multipurpose build, which means that the sample presentation was not well suited to this particular application, or many other applications for that sake. As the Meat Industry grows and develops to meet the demands of the modern markets, they realise the need for better control of processes and final products. From the early 90 ties and onward the demand for 'rear time' rapid results starts growing, and some suppliers of NIR instruments (and instruments based on other technologies, like X-ray) start to develop and manufacture instrumentation dedicated to the particular needs of the Meat Industry. Today it is estimated that there are approximately 2000 rapid instruments placed in the Meat industry world-wide. By far most of these are used as at-line or laboratory installations, but the trend and need is moving towards real on-line or in-line solutions. NIR is the most cost effective and reproducible analytical procedure available for the twenty first century.

• 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.