• Near Infrared Analysis
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• v.1 no.1
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• pp.27-30
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• 2000

In this study, we investigated the feasibility of non-destructive determination of internal quality factors of Fuji apple fruit using near infrared(NIR) reflectance spectroscopy and developed the calibration models. As the reference methods, refractometer, titration and texture analyzer for sugar content, acidity and firmness were used, respectively. Samples were scanned from 1100∼2500nm with InfraAlyzer 500C spectrometer and SESAME software was used for data analysis. A multiple linear regression(MLR) analysis was performed to develop the calibrations. The correlation coefficient(R) and standard error of prediction(SEP) were as follows; 0.91, 0.41$^{\circ}$Brix for sugar content, 0.90, 0.04% for acidity and 0.84, 0.094 kg for firmness, respectively. This study shows that NIR spectroscopy can be used to evaluate the sugar content acidity and firmness of apple fruit with acceptable accuracy.

• Near Infrared Analysis
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• v.2 no.1
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• pp.43-53
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• 2001

A non-invasive spectroscopic method is presented for the measurement of pulmonary edema. Both early diagnosis and quantitative edema estimates were investigated. The spectroscopic determination of pulmonary edema involved the acquisition of diffuse reflectance spectra in the near-infrared (NIR) region with change in water concentration - water is the main constituent of edema fluid. Pulmonary edema was induced into the excised perfused lungs of seven animals by elevating the hydrostatic pressure. Estimates of edema were ascertained from a partial least squares regression of the measured spectral response. Actual edema was determined from the change (increase) in total lung weight. Estimates in relative lung weight increases due to in vitro edema were made with the near infrared spectra. The results revealed that fluid accumulation produced spectral changes in the O-H and C-H absorptions as well as scattering changes in the spectra. Histology of the lung was used to verify the presence or absence of interstitial and alveolar edema. Results demonstrated that near infrared spectroscopy might provide a new tool for clinical assessment of pulmonary edema.

• 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.

• The Korean Journal of Legal Medicine
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• v.42 no.4
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• pp.146-152
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• 2018

We investigated the neural correlates of accurate eyewitness memory retrieval using functional near-infrared spectroscopy. We analyzed oxygenated hemoglobin ($HbO_2$) concentration in the prefrontal cortex during eyewitness memory retrieval task and examined regional $HbO_2$ differences between observed objects (target) and unobserved objects (lure). We found that target objects elicited increased activation in the bilateral ventrolateral prefrontal cortex, which is known for monitoring retrieval processing via bottom-up attentional processing. Our results suggest bottom-up attentional mechanisms could be different during accurate eyewitness memory retrieval. These findings indicate that investigating retrieval mechanisms using functional near-infrared spectroscopy might be useful for establishing an accurate eyewitness recognition model.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2000.06a
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• pp.53-53
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• 2000

• 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.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.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.

• Journal of the Korean Applied Science and Technology
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• v.16 no.1
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• pp.21-24
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• 1999

Sesame seed (Sesamum indicum L.) is an important seasoning in Korea and most korean consumer tend to eat the korean sesame seed as the best than other ones produced in oriental countries such as China and Japan. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China and so on) of sesame seeds. Near-infrared spectroscopy among the many kinds of techniques could provide a rapid screening, low cost solution to discriminate geographical origin of sesame seed. The objective of this study is to determine if NIR technique could be used to discriminate between the korean sesame seed and non-korean sesame seed by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographic origin of sesame seeds were discriminated relative accurately according to geographical origin using PLS regression method.