• Journal of Biosystems Engineering
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• 제40권2호
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• pp.153-158
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• 2015

Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.

• Journal of Biosystems Engineering
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• 제37권6호
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• pp.404-410
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• 2012

Purpose: The objective of this research was to select high quality cucumber (cucumis sativus) seed by classifying into viable or non-viable one using Raman spectroscopy. Method: Both transmission and back-scattering Raman spectra of viable and non-viable seeds in the range from $150cm^{-1}$ to $1890cm^{-1}$ were collected with a laser illumination. Results: The Raman spectra of cucumber seed showed Raman peaks with features of polyunsaturated fatty acids. The partial least squares-discriminant analysis (PLS-DA) to predict viable seeds was developed with measured transmission and backscattering spectra with Raman spectroscopy and germination test results. Various types of spectra pretreatment were investigated to develop the classification models. The results of developed PLS-DA models using the transmission spectra with mean normalization or range normalization, and back-scattering spectra with mean normalization treatment or baseline correction showed 100% discrimination accuracy. Conclusions: These results showed that Raman spectroscopy technologies can be used to select the high quality cucumber seeds.

• 한국식생활문화학회지
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• 제32권2호
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• pp.150-161
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• 2017

This study was conducted to identify sensory characteristics of soy-meat samples by trained panels and to observe the relationship between these sensory characteristics and consumer acceptability of the samples. Descriptive analysis was performed on eight samples; four types of patty style soy-meat samples (Soy-meat Patty; SP) made with a Ddukgalbi recipe (YSP, VSP, LSP, and SSP) and four types of Bulgogi style soy-meat samples (Soy-meat Bulgogi; SB) made with a Bulgogi recipe (YSB, VSB, LSB, and SSB). Seven panelists were trained, and they evaluated the appearance, odor/aroma, flavor/taste, texture/mouth feel, and after taste attributes of these samples. Forty attributes were generated by panelists, and 37 attributes were significantly different across products (p<0.05). The SB group was characterized by beef, leek, and garlic flavor as well a sweetness, denseness, slipperiness, chewiness, and pepper after taste. The SP group was characterized by roughness, particle size, rancid oil flavor, raw bean flavor, astringent, sourness, and adhesiveness. Consumer test (n=125) showed that the VSB sample had the highest scores for acceptability of appearance, flavor, texture, and overall liking. The PLSR results show that the attributes that were more positively associated with acceptance of soy-meat samples were beef taste, wetness, and chewiness, whereas the raw bean smell and rancid oil flavor attributes were negative.

• 한국축산시설환경학회지
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• 제20권3호
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• pp.117-124
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• 2014

The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

• Journal of Ginseng Research
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• 제38권1호
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• pp.52-58
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• 2014

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng.

• Journal of Ginseng Research
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• 제40권4호
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• pp.344-350
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• 2016

Background: Mountain-cultivated ginseng (MCG) and cultivated ginseng (CG) both belong to Panax ginseng and have similar ingredients. However, their pharmacological activities are different due to their significantly different growth environments. Methods: An ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS)-based approach was developed to distinguish MCG and CG. Multivariate statistical methods, such as principal component analysis and supervised orthogonal partial-least-squares discrimination analysis were used to select the influential components. Results: Under optimized UPLC-QTOF-MS/MS conditions, 40 ginsenosides in both MCG and CG were unambiguously identified and tentatively assigned. The results showed that the characteristic components of CG and MCG included ginsenoside Ra3/isomer, gypenoside XVII, quinquenoside R1, ginsenoside Ra7, notoginsenoside Fe, ginsenoside Ra2, ginsenoside Rs6/Rs7, malonyl ginsenoside Rc, malonyl ginsenoside Rb1, malonyl ginsenoside Rb2, palmitoleic acid, and ethyl linoleate. The malony ginsenosides are abundant in CG, but higher levels of the minor ginsenosides were detected in MCG. Conclusion: This is the first time that the differences between CG and MCG have been observed systematically at the chemical level. Our results suggested that using the identified characteristic components as chemical markers to identify different ginseng products is effective and viable.

• 기술혁신학회지
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• 제21권2호
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• pp.684-714
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• 2018

스마트워치의 확산이 예상과는 달리 더디게 진행되고 있다. 스마트워치 공급업체들은 현재의 캐즘을 극복하기 위해 새로운 전략을 수립할 필요가 있다. 그러나 스마트워치의 어떠한 속성을 전략적으로 활용하여 시장 확산을 이루어야 하는가를 타당하게 수행한 연구는 매우 드물다. 본 연구는 스마트워치가 가져다줄 것으로 예상되는 혜택과 이를 위해 치러야 할 비용을 소비자 관점에서 분석하고, 소비자의 혁신성향이 시장 확산에 기여할 수 있는지를 살펴보았다. 이를 위해 323개의 유효데이터를 확보하여 구조 방정식 분석을 실시하였다. 분석 결과, 스마트워치의 두 가지 혜택(utilitarian and hedonic)과 세 가지 비용(usability, performance, and finance)이 가치인식을 통해 사용의도에 영향을 주는 것으로 나타났다. 또한 소비자의 혁신성향이 가치인식과 사용의도의 관계를 조절하는 것으로 드러났다. 주목할 점은, 소비자들이 스마트워치가 사회적 혜택을 가져다 줄 것으로 기대할 것이라는 가설이 기각되었다는 점이다. 즉, 스마트워치 사용이 소비자에게 이미지 향상을 가져다 줄 것이라는 전략은 스마트워치 확산에 큰 기여를 하지 않을 수 있다. 스마트워치의 시장 확산을 이루기 위해서는 혁신성향이 높은 소비자들을 대상으로 소비자들이 기대하는 혜택을 활용하는 전략을 수립해야 한다.

• 한국콘텐츠학회논문지
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• 제15권2호
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• pp.433-443
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• 2015

최근 커피 시장은 초고속 성장을 거듭하면서 커피에 대한 소비가 증가하고 있다. 하지만 커피 전문점들이 우후죽순 생겨나면서 전문점 간 경쟁이 점점 치열해지고 있다. 그래서 커피 전문점들은 고객과의 장기적 관계를 유지하기 위해서 고객 충성도를 향상시키고자 노력하고 있다. 본 연구에서는 자의 기반 메커니즘과 구속 기반 메커니즘을 통합하여 고객들의 충성도 형성 메커니즘을 살펴보았다. 자의 기반 메커니즘으로 고객 만족을 고려하였으며, 구속 기반 메커니즘으로 전환 비용을 고려하였다. 고객 만족의 선행 요인으로 커피 품질, 서비스 품질, 가격 및 가치, 서비스 환경을 선정하였으며, 전환 비용의 선행 요인으로는 습관과 브랜드 이미지를 고려하였다. 제안한 연구 모형은 커피전문점을 방문하여 커피를 음용한 경험자 중 대학생 263명을 대상으로 검증되었다. 연구 분석 결과, 고객 만족과 전환 비용은 고객 충성도 분산의 66.1%를 설명해 주었다. 커피 전문점 품질 요인들은 모두 고객 만족에 유의한 영향을 미쳤다. 또한 습관과 브랜드 이미지는 전환 비용 형성에 중요한 역할을 담당하고 있음을 알 수 있었다.

• Journal of Ginseng Research
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• 제38권3호
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• pp.187-193
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• 2014

Background: White ginseng (Panax ginseng Meyer) is commonly distributed as a health food in food markets. However, there is no practical method for distinguishing Korean white ginseng (KWG) from Chinese white ginseng (CWG), except for relying on the traceability system in the market. Methods: Ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with orthogonal partial least squares discrimination analysis (OPLS-DA) was employed to discriminate between KWG and CWG. Results: The origins of white ginsengs in two test sets ($1.0{\mu}L$ and $0.2{\mu}L$ injections) could be successfully discriminated by the OPLS-DA analysis. From OPLS-DA S-plots, KWG exhibited tentative markers derived from ginsenoside Rf and notoginsenoside R3 isomer, whereas CWG exhibited tentative markers derived from ginsenoside Ro and chikusetsusaponin Iva. Conclusion: Results suggest that ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with OPLS-DA is an efficient tool for identifying the difference between the geographical origins of white ginsengs.

• Journal of Ginseng Research
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• 제37권2호
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• pp.248-253
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• 2013

Leaves from Panax ginseng Meyer (Korean origin and Chinese origin of Korean ginseng) and P. quinquefolius (American ginseng) were harvested in Haenam province, Korea, and were analyzed to investigate patterns in major metabolites using HPLC-based metabolic profiling. Partial least squares discriminant analysis (PLS-DA) was used to analyze the the HPLC chromatogram data. There was a clear separation between Panax species and/or origins from different countries in the PLS-DA score plots. The ginsenoside compounds of Rg1, Re, Rg2, Rb2, Rb3, and Rd in Korean leaves were higher than in Chinese and American ginseng leaves, and the Rb1 level in P. quinquefolius leaves was higher than in P. ginseng (Korean origin or Chinese origin). HPLC chromatogram data coupled with multivariate statistical analysis can be used to profile the metabolite content and undertake quality control of Panax products.