• Journal of electromagnetic engineering and science
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• v.17 no.4
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• pp.186-190
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• 2017

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450-1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.166-176
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• 2012

Purpose: This study was conducted to investigate the potential of interactance mode of NIR spectroscopy technology for the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from local greenhouses in three different harvesting seasons (experiments 1, 2, and 3). The fruit attributes were measured at the 6 points on an equator of each sample where the spectral data were collected. The prediction models were developed using the original spectral data and the spectral data sets preprocessed by 20 methods. The performance of the models was compared. Results: In the prediction of SSC, the highest coefficient of determination ($R_{cv}{^2}$) values of the cross-validation was 0.755 (standard error of prediction, SEP=$0.89^{\circ}Brix$) with the preprocessing of normalization with range in experiment 1. The highest coefficient of determination in the robustness tests, $R_{rt}{^2}$=0.650 (SEP=$1.03^{\circ}Brix$), was found when the best model of experiment 3 was evaluated with the data set of experiment 2. The best $R_{cv}{^2}$ for the prediction of firmness was 0.715 (SEP=3.63 N) when no preprocessing was applied in experiment 1. The highest $R_{rt}{^2}$ was 0.404 (SEP=5.30 N) when the best model of experiment 3 was applied to the data set of experiment 1. Conclusions: From the test results, it can be concluded that the interactance mode of VIS/NIR spectroscopy technology has a great potential to measure SSC and firmness of thick-skinned muskmelons.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.210-218
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• 2000

Since the SSC(soluble solid contents) and titratable acidity of fruit are highly concerned to the taste, the need for measuring them by non-destructive technology such as NIR(Visual and Near-infrared) spectroscopy is increasing. Specially, in order to grade the quality of each fruit with a sorter at sorting and packing facilities, technologies for online measurement satisfying the tolerance in terms of accuracy and speed should be developed. Many researches have been done to develop devices to measure the internal qualities of fruit such as SSC, titratable acidity, firmness, etc. with the VIS(Visual)/NIR(Near Infrared) reflectance spectra. The distributions of the SSC, titratable acidity, firmness, etc. are different with respect to the position and depth of fruit, and generally the VIS/NIR light can interact with fruit in a few millimeters of pathlength, and it is very difficult to measure the qualities of inner flesh of fruit. Therefore, to measure the average concentrations of each quality factor such as SSC and titratable acidity with the reflectance-type NIR devices, the spectra of fruit at several positions should be measured. Recently, the interest about the transmittance-type VIS/NIR devices is increasing. NIR light can penetrate through the fruit about 1/10-1/1,000,000 %. Therefore, very intensive light source and very sensitive sensor should be adopted to measure the transmitted light spectra of intact fruit. The ultimate purpose of this study was to develop a device to measure the transmitted light spectra of intact fruit such as apple, pear, peach, etc. With the transmittance-type VIS/NIR device, the feasibility of measurement of the SSC and titratable acidity in intact fruit cultivated in Korea was tested. The results are summarized as follows; A simple measurement device which can measure the transmitted light spectra of intact fruit was constructed with sample holder, two 500W-tungsten halogen lamps, a real-time spectrometer having a very sensitive CCD array sensor and optical fiber probe. With the device, it was possible to measure the transmitted light spectra of intact fruit such as apple, pear and peach. Main factors affecting the intensity of transmitted light spectra were the size of sample, the radiation intensity of light source and the integration time of the detector. Sample holder should be designed so that direct light leakage to the probe could be protected. Preprocessing method to the raw spectrum data significantly influenced the performance of the nondestructive measurement of SSC and titratable acidity of intact fruit. Representative results of PLS models in predicting the SSC of peach were SEP of 0.558 Brix% and R2 of 0.819, and those in predicting titratable acidity were SEP of 0.056% and R2 of 0.655.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Korean Journal of Agricultural Science
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• v.40 no.2
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• pp.163-167
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• 2013

Objective of the study was to compare reflectance spectrum in the blade and the vein parts of cabbage and kale leaves. A total 6 cabbage and kale leaves were taken from a plant factory in Chungnam National University, Korea. Spectra data were collected with a UV/VIS/NIR spectrometer (model: USB2000, Ocean Optics, FL, USA) in the wavelength region of 190 - 1130 nm. Median filter smoothing method was selected to preprocess the obtained spectra data. We computed reflectance difference by subtraction of averaged spectrum from individual spectrum. To estimate correlation at different parts of cabbage and kale leaves, cross - correlation method was used. Differences between cabbage and kale leaves are clearly manifested in the green, red and near - infrared ranges. The percent reflectance of cabbage leaves in the NIR wavelength band was higher than that of kale leaves. Reflectance in the blade part was higher than in the vein part by 18%. Reflectance difference in the different parts of cabbage and kale leaves were clear in all of the wavelength bands. Standard deviation of reflectance difference in the vein part was greater for kale, while the value in the blade part was greater for cabbage leaves. Standard deviation of cross - correlation increased from 0.092 in the first sensor (UV/VIS) and 0.007 in the second sensor (NIR) to 0.099 and 0.015, respectively.

• Korean Journal of Materials Research
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• v.15 no.3
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• pp.209-215
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• 2005

Titanium dioxide films $(TiO_2)$ doped cobalt transition metal were prepared on titanium metal by water spray pyrolysis technique. Micro-morphology, crystalline structure, chemical composition and binding state of sample groups were evaluated using field emission scanning microscope(FE-SEM), X-ray diffractometer(XRD), Raman spectrometer, X-ray photoelectron spectrometer(XPS). $TiO_2$ films of rutile structure were predominately formed on all sample groups and $Ti_2O_3$ oxide was coexisted on the surface of cobalt doped-sample groups. The optical absorption peaks measured by using UV-VIS-NIR spectrophotometer were observed at specific wavelength region in sample groups doped cobalt ion. This result could be analyzed by introducing crystal field theory.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.207-207
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• 2013

기존의 그래핀 성장에 관한 연구는 열화학기상증착법(Chemical vapor deposition; CVD)을 이용한다. 그래핀 성장 제어 요소로는 촉매 기판인 전이 금속[Ru, Ir, Co, Re, Pt, Pd, Ni, Cu], 기판 전처리 과정, 수소/메탄 가스 혼합비, 작업 진공 상태, 기판온도[$800{\sim}1,000^{\circ}C$, 냉각 속도 등으로 보고 되고 있다. 그래핀 성장 원리는 Cu 촉매 기판에 메탄 가스를 $1,000^{\circ}C$ 온도에서 분해해서 탄소를 고용 시킨 후 급랭하는 도중에 석출되는 탄소에 의해 그래핀 시트가 형성되는 것으로 알려져 있다. 기존의 CVD를 열원을 이용할 경우 내부 챔버에 생기는 잠열에 의해 cooling profile의 제어가 용이하지 않다. 본 연구에서는 근적외선(Near Infrared; NIR) 열원을 이용한 CVD로 챔버 내부 잠열을 최소화하고, 냉각 공정을 Natural, Linear, Convex cooling type으로 디자인해서 cooling profile 제어가 그래핀 성장에 미치는 영향을 연구 하였다. 이렇게 성장된 그래핀을 임의의 기판(SiO2, Glass, PET film) 위에 습식방법으로 전이 시킨 후, 전기적 구조적 및 광학적 특성을 면저항(four-point probe), 전계방사 주사전자현미경(Field Emission Scanning Electron Microscope; FE-SEM), 마이크로 라만 분광법(Micro Raman spectroscopy) 및 광학현미경(optical microscope), 투과도(UV/Vis spectrometer)의 측정으로 잠열이 최소화된 NIR-CVD에서 cooling profile에 따른 그래핀 성장을 평가하였다.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.177-183
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• 2012

Purpose: In near infrared spectroscopy, interactance configuration of a light source and a spectrometer probe can provide more information regarding fruit internal attributes, compared to reflectance and transmittance configuration. However, there is no through study on the parameters of interactance measurement setup. The objective of this study was to investigate the effect of the parameters on the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from greenhouses at three different harvesting seasons. The prediction models were developed at three distances of 2, 5, and 8 cm between the light source and the spectrometer probe, three measurement points of 2, 3, and 6 evenly distributed on each sample, and different number of fruit samples for calibration models. The performance of the models was compared. Results: In the test at the three distances, the best results were found at a 5 cm distance. The coefficient of determination ($R_{cv}{^2}$) values of the cross-validation were 0.717 (standard error of prediction, SEP=$1.16^{\circ}Brix$) and 0.504 (SEP=4.31 N) for the estimation of SSC and firmness, respectively. The minimum measurement point required to fully represent the spectral characteristics of each fruit sample was 3. The highest $R_{cv}{^2}$ values were 0.736 (SEP=$0.87^{\circ}Brix$) and 0.644 (SEP=4.16 N) for the estimation of SSC and firmness, respectively. The performance of the models began to be saturated when 60 fruit samples were used for developing calibration models. The highest $R_{cv}{^2}$ of 0.713 (SEP=$0.88^{\circ}Brix$) and 0.750 (SEP=3.30 N) for the estimation of SSC and firmness, respectively, were achieved. Conclusions: The performance of the prediction models was quite different according to the condition of interactance measurement setup. In designing a fruit grading machine with interactance configuration, the parameters for interactance measurement setup should be chosen carefully.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.106-106
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• 2009

Al-doped ZnO (AZO) thin films were grown on glass substrates by co-sputtering at room temperature. We made ZnO and Al target and ZnO:Al film is deposited with sputter which has two RF gun source. The Al content was controlled by varying Al RF power and effect of Al contents on the properties of ZnO:Al film was investigated. Crystallinity and orientation of the ZnO:Al films were investigated by X-ray diffraction (XRD), surface morphology of the ZnO:Al films was observed by atomic force microscope. Electrical properties of the ZnO:Al films were measured at room temperature by van der Pauw method and hall measurement. Optrical properties of ZnO:Al films were measured by UV-vis-NIR spectrometer.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.304-304
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• 2012

CIGS(CuInGaSe2) 태양전지의 후면전극(Back contact)으로 널리 사용되는 Mo 박막은 낮은 면저항, 높은 반사율, 광흡수층 Na-path 제공 등의 조건이 요구된다. 일반적으로 Mo 박막 제작은 DC 마그네트론 스퍼터링 방법이 가장 널리 사용되며, 제작조건에 따라 태양전지 효율에 강한 영향을 미치는 것으로 보고되고 있다. 본 연구에서는 DC 마그네트론 스퍼터링 시 기판에 이온빔(Ion-beam)을 동시 조사하는 이온 빔 스퍼터링 증착(Ion-beam sputter deposition)법으로 Mo 박막을 제작하였다. 제작된 박막의 전기적 및 광학적 특성은 4-point probe, UV-Vis-NIR spectrometer로 각각 조사하였으며 Na-path 제어를 위한 구조적 특성은 XRD, FE-SEM으로 분석하였다. 분석결과에 따르면 기존 DC 마그네트론 스퍼터링 방법보다 상대적으로 더 치밀한 구조와 높은 반사율을 가지는 박막이 제작됨을 알 수 있었다. Mo 박막의 최적조건은 DC power 300 W, Ion-gun power 50 W, Ar flow rate 20 sccm 였다.