• Journal of Biosystems Engineering
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• v.26 no.5
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• pp.475-480
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• 2001

Sensing soil organic matter is crucial for precision farming and environment friendly agriculture. Near infra-red(NIR) was utilized to measure the soil organic matter. Multivariate calibration methods, including stepwise multiple linear regression(MLR), principal components recession(PCR) and partial least squares regression(PLS), were applied to soil spectral reflectance data to predict the organic matter content. The effect of soil particle size and water content was studied. The range of soil organic matter contents was from 0.5 to 11%. Near infrared (NIR) region from 700 to 2,500nm was applied. For uniform soil particle size, result had good correlation (R$\^$2/ = 0.984, standard error of prediction= 0.596). The effect of soil particle size could be eliminated with 1st order derivative of the NIR signal. However. moist soil had a little lower correlation. R$\^$2/ was 0.95 and standard error of prediction was 0.94% using the PLS method. The results showed the possibility of soil organic matter measurement using NIR reflectance on the field.

• Journal of Biosystems Engineering
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• v.34 no.3
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• pp.197-203
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• 2009

This study was performed to develop a nondestructive determination technology for sugar content in sweet persimmons, and the main research results included the following. In order to determine sugar content in sweet persimmons, a dual side reflex was adopted, and the study was to measure sugar content using a reflectance spectrum for 2 parts because it was difficult to determine representative sugar content due to a great deviation in sugar content according to the part of sweet persimmons. To predict sugar contents of sweet persimmon, PLSR and PCR models were compared with a few preprocess methods. As a result, PLSR had $R^2$=0.67, SEP=0.42 brix, LV=11, and PCR had $R^2$=0.65, SEP=0.41 brix, PC=16. SNV method was the best among preprocess methods for predicting sugar contents.

• Journal of the Korean Society of Tobacco Science
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• v.17 no.2
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• pp.177-183
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• 1995

This study was conducted to develop the most precise NIR(near infrared spectrometric) calibration for rapid determination of chemical composition in ground samples of toasted burley tobacco using stepwise, stepup, principal component regression(PCR), partial least square(PLS) and modified partial least square(MPLS) calibration method. The number of wavelength(W) selected by stepup multiple linear regression using: second derivative spectra was as follows: total sugar(TS)-4 W, nicotine-9 W, total nitrogen(TN)-2 W, ash-8 W, total volatile base(TVB)-5 W, chlorine4 W, L of color-6 W, a of color-6 W and b of color-7 W. Comparing the calibration equations followed by each chemical components, the most precise calibration equation was MPLS for 75, a and b of color, PLS for nicotine, ash, TVB, chlorine and L of color and stepup for TN. The standard error of calibration(SEC) and standard error of performance(SEP) between result of near infrared analysis and standard laboratory analysis were 0.18, 0.40% for 75, 0.06, 0.08% for nicotine, 0.18, 0.16% for TN, 0.33, 0.46% for ash, 0.04, 0.03% for TVB, 0.08, 0.06% for chlorine, 0.54, 0.58 for L of color, 0.22, 0.22 for a of color and 0.27, 0.27 for b of color, respectively. The SEC and SEP of ash and TVB were within allowable error of standard laboratory analysis, nicotine, TN and chlorine were 1.2-2.0 times and 75 were 2.1-4.0 times larger than allowable error of standard laboratory analysis. The ratio of SEC and SEP to mean were 1.5, 1.6% for L of color, 3.7, 3.8% for a of color and 1.8, 1.8% for b of color, respectively. Key words : burley tobacco chemistry, near infrared spectroscopy.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.761-767
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• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2002.02a
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• pp.479-485
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• 2002

본 연구는 초음파를 이용하여 한우도체의 연도를 비파괴적이며 객관적으로 측정할 수 있는 시스템을 개발하기 위해서 수행되었다. 한우도체 연도 측정 시스템은 크게 초음파 측정장치, 자동 탐촉자 수직이동장치, 데이터 획득 및 분석장치로 구성되었는데 초음파 측정장치는 초음파 pulser/receiver 및 탐촉자, 자동 탐촉자 이동장치는 상하운동부, 구동부, 제어부, 데이터 획득 및 분석장치는 digitizer, Labview 5.1을 사용하여 구성되었다. 통합된 시스템을 이용하여 획득된 도체의 초음파 신호를 분석하기 위해 1.0~1.1 MHz의 bandpass filtering을 거쳐 hilbert 변환을 이용, envelope를 구할 수 있었으며 탐촉자와 도체의 최적 접촉 위치를 결정하기 위하여 3단계로 나누어 신호분석을 실시하였다. 시료의 개수는 40개였으며 획득된 envelope를 FFT 변환 후 PLS, PCR 분석을 수행한 결과 7단계의 PCR 분석에서 $R^2$= 0.6474의 유의성 있는 결과를 나타내었으므로 최적 접촉 위치로 결정하였다. 최적 접촉 위치를 통해 시료 80개의 추가 실험을 실시한 결과 PCR 분석에서 $R^2$= 0.4304의 결과를 나타내었으며 이를 이용, 도체의 연도를 측정하는 프로그램을 개발하고 최종 통합 시스템을 구축하였다. 본 한우도체 연도 측정 시스템의 개발을 통해 한우도체의 전단력을 예측하여 연도를 객관적으로 판정 가능할 것으로 생각되며 또한 사이즈의 확대로 도축장에 설치하는 설비로서 가능할 것이라 사료된다. 그러나 추후 좀 더 세밀한 측정과 결과의 보완을 위한 분석방법의 개선에 관한 연구가 진행되어야 할 것이다. 사용해 설계된 장치를 사용자가 쉽게 제작할 수 있도록 하였다. 공정설계프로그램을 통해 설계된 공정은 데이터베이스에 저장이 되며 장치설계프로그램에서 쉽게 이전에 설계했던 공정을 이용할 수 있도록 하여 공정 설계와 장치설계를 연계하도록 하였다.동투하시간과 비용 -종자준비부터 통마늘선별까지의 일관기계화로 투입된 주요작업의 노력은 75∼76%가 절감되고, 재배규모 3ha기준시 비용은 44-53%절감되었음. the annealing texture. Observations by TEM and EBSD revealed the formation of very fine grains of ∼1.0$\mu\textrm{m}$ after CCSS.he dislocations form local defect arrangements at the grooves permitting the substantial reduction in defect density over the remainder of the interfacial area.한 최대의 감자 재배지역을 형성하였다. 제주도는 산지지형과 따뜻한 기온으로 2기작이 가능하고, 감자가공 공장설립과 교통발달에 따른 육지 시장과의 접근이 용이해졌기 때문에 남한에서 2번째로 큰 감자재배지역이 되었다.(요약 및 결론에서 발췌)그람양성균에서 효과적이었으며, 농도별 항균력시험 결과 농도가 증가할수록 비례하여 저해율도 증가함을 알 수 있었다. 첨가농도를 달리하여 미생물의 생육도를 측정한 결과, fraction II磎꼭\ulcorner경우 그람양성균에 대해 500 ppm 이상에서 뚜렷한 증식억제효과를 나타내었다.서 뚜렷한 증식억제효과를 나타내었다.min/+}$계

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.12
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.645-655
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• 2020

Bacteria are a very common cause of food poisoning. Moreover, bacteria form biofilms to protect themselves from harsh environments. Conventional detection methods for foodborne bacterial pathogens including the plate count method, enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) assays require a lot of time and effort. Hyperspectral imaging has been used for food safety because of its non-destructive and real-time detection capability. This study assessed the feasibility of using hyperspectral imaging and machine learning techniques to detect biofilms formed by Escherichia coli. E. coli was cultured on a high-density polyethylene (HDPE) coupon, which is a main material of food processing facilities. Hyperspectral fluorescence images were acquired from 420 to 730 nm and analyzed by a single wavelength method and machine learning techniques to determine whether an E. coli culture was present. The prediction accuracy of a biofilm by the single wavelength method was 84.69%. The prediction accuracy by the machine learning techniques were 87.49, 91.16, 86.61, and 86.80% for decision tree (DT), k-nearest neighbor (k-NN), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA), respectively. This result shows the possibility of using machine learning techniques, especially the k-NN model, to effectively detect bacterial pathogens and confirm food poisoning through hyperspectral images.

• Journal of Nutrition and Health
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• v.51 no.4
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• pp.275-286
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• 2018

Purpose: Our previous study demonstrated that persimmon (Diospyros kaki Thumb.) at different stages of ripening provided different protective effects against high-fat/cholesterol diet (HFD)-induced dyslipidemia in rats. In this study, we compared the metabolites profile and gene expressions related to triglyceride (TG)/cholesterol metabolism in vitro and in vivo after treating with persimmon water extracts (PWE) or tannin-enriched persimmon concentrate (TEP). Methods: Primary and secondary metabolites in test materials were determined by GC-TOF/MS, UHPLC-LTQ-ESI-IT-MS/MS, and UPLC-Q-TOF-MS. The expression of genes related to TG and cholesterol metabolism were determined by RT-PCR both in HepG2 cells stimulated by oleic acid/palmitic acid and in liver tissues obtained from Wistar rats fed with HFD and PWE at 0, 150, 300, and 600 mg/d (experiment I) or TEP at 0, 7, 14, and 28 mg/d (experiment II) by oral gavage for 9 weeks. Results: PLS-DA analysis and heatmap analysis demonstrated significantly differential profiling of metabolites of PWE and TEP according to processing of persimmon powder. In vitro, TEP showed similar hypolipidemic effects as PWE, but significantly enhanced hypocholesterolemic effects compared to PWE in sterol regulatory element-binding protein 2 (SREBP2), HMG-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), cholesterol $7{\alpha}-hydroxylase$ (CYP7A1), and low density lipoprotein receptor (LDLR) gene expression. Consistently, TEP and PWE showed similar hypolipidemic capacity in vivo, but significantly enhanced hypocholesterolemic capacity in terms of SREBP2, HMGCR, and bile salt export pump (BSEP) gene expression. Conclusion: These results suggest that column extraction after hot water extraction may be a good strategy to enhance tannins and long-chain fatty acid amides, which might cause stimulation of hypocholesterolemic actions through downregulation of cholesterol biosynthesis gene expression and upregulation of LDL receptor gene expression.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1527-1527
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• 2001

Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.