• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.40-40
• /
• 2017

본 연구는 빛의 파장대가 넓어 보다 다양한 접근과 검출이 가능한 초분광 카메라 (VNIR spectral camera PS, SPECIN Filand)를 이용하여 정식시기가 다른 배추를 생육단계별로 영상을 취득한 후 배추 캐노피의 전 파장 (400~1000nm)으로 생육 추정모델을 개발하기 위해 수행하였다. 정식시기가 다른 배추를 생육단계별로 초분광 카메라로 영상을 취득한 후 취득된 영상 ($348{\times}1040$)을 ENVI (ver. 5.2, Exelis Visual Information Solutions, USA) 프로그램을 이용하여 식생지수 NDVI로 작물과 배경을 구분하였다. 배추 캐노피 영역에 전 파장을 산출한 후 반사판 영역의 전 파장을 이용하여 광 보정된 반사율을 산출하였다. 통계 프로그램인 R Project (ver.3.3.3, Development Core Team, Vienna, Austria)를 이용하여 배추의 반사율과 계측한 생육 정보를 PLSR (Partial least squares regression) 분석하여 정확도($R^2$) 및 정밀도 (RMSE [g,cm,count], RE [%])로 나타내었고 그 모델은 full-cross validation (FV) 하여 타당성을 검증하였다. 정식시기가 다른 배추의 모든 생육단계의 생육정보를 이용하여 PLSR (Partial least squares regression) 결과 엽장을 추정한 모델의 $R^2$는 84% 이상의 정확도와 RMSE 3.2cm 이하의 좋은 정밀도를 보였다. 엽폭을 추정한 모델의 $R^2$는 73% 이상의 정확도와 RMSE 3.5cm 이하의 정밀도를 보였고 엽수를 추정한 모델의 $R^2$는 93% 이상의 정확도와 RMSE 6.3Count 이하의 정밀도로 보여 캐노피의 전 파장을 이용해 생육을 추정하는 것이 가능하다고 판단되었으며 이 모델들의 타당성 검증에서도 좋은 정확도와 정밀도를 보였다. 그러나 배추의 중요한 생육인자 중 생체중을 추정한 모델의 $R^2$는 89% 이상으로 정확도가 높았으나 RMSE 571.1g 이하로 낮은 정밀도를 보여 생체중을 정확히 추정하기 어려웠다. 따라서 다른 통계분석방법으로 전 파장과 생육정보를 분석하거나 특정 밴드를 선택하여 산출한 식생지수를 이용한 추정 모델의 개발을 통하여 오차를 개선할 필요가 있다고 사료된다. 추후 반복 실험하여 분석한 추정 모델과 비교 분석하여 다양한 환경 및 생물 조건에 범용성을 가진 모델을 개발할 필요가 있다.

• Journal of the Society of Disaster Information
• /
• v.16 no.3
• /
• pp.542-549
• /
• 2020

Purpose: As nitrate nitrogen produced during fermentation of liquid fertilizer is a pollution indicator of water, in this study, four research areas where liquid fertilizer was sprayed were selected, and a model was designed to estimate the concentration of nitrate nitrogen pollution. Method: Prior to shooting on site, a spectrum library was constructed by dividing the ratio of liquid fertilizer into 5 groups: 0%, 25%, 50%, 75%, and 100%. PLSR (Partial least squares regression) method was applied to hyperspectral images acquired in the study area based on the aspect of spectrum. Result: The behavior of nitrate nitrogen was confirmed by 1st and 2nd differentiation of the spectrum of the constructed liquid fertilizer. PLSR concentration estimation modeling was implemented using images from field experiments and compared with actual concentration of nitrate nitrogen. Conclusion: When comparing the PLSR concentration estimation model with the actual concentration of nitrate nitrogen, it was measured that the detection is possible in high concentration areas where the concentration of nitrate nitrogen is 70mg/kg or more.

• Journal of the Korean Wood Science and Technology
• /
• v.43 no.3
• /
• pp.311-319
• /
• 2015

Near infrared (NIR) reflectance spectroscopy was employed to develop moisture content prediction model of pitch pine (Pinus rigida), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), yellow poplar (Liriodendron tulipifera) wood below fiber saturation point. NIR reflectance spectra of specimens ranging from 1000 nm to 2400 nm were acquired after humidifying specimens to reach several equilibrium moisture contents. To determine the optimal moisture contents prediction model, 5 mathematical preprocessing methods (moving average (smoothing point: 3), baseline, standard normal variate (SNV), mean normalization, Savitzky-Golay $2^{nd}$ derivatives (polynomial order: 3, smoothing point: 11)) were applied to reflectance spectra of each specimen as 8 combinations. After finishing mathematical preprocessings, partial least squares (PLS) regression analysis was performed to each modified spectra. Consequently, the mathematical preprocessing methods deriving optimal moisture content prediction were 1) moving average/SNV for pitch pine and red pine, 2) moving average/SNV/Savitzky-golay $2^{nd}$ derivatives for Korean pine and yellow poplar. Every model contained three principal components.

• Journal of the Korean Wood Science and Technology
• /
• v.43 no.3
• /
• pp.304-310
• /
• 2015

The moisture content of sawdust must be measured accurately and controlled appropriately during storage and transportation because biological degradation could be caused by improper moisture. In this study, to measure the moisture contents of Larix kaempferi sawdust, the near-infrared reflectance spectra (Wavelength 1000-2400 nm) of sawdust were used as detection parameter. After acquiring the NIR reflection spectrum of specimens which were humidified at each relative humidity condition ($25^{\circ}C$, RH 30~99%), moisture content prediction model was developed using mathematical preprocessings (e.g. smoothing, standard normal variate) and partial least squares (PLS) analysis with the acquired spectrum data. High reliability of the MC regression model with NIR spectroscopy was verified by cross validation test ($R^2$ = 0.94, RMSEP = 1.544). The results of this study show that NIR spectroscopy could be used as a convenient and accurate method for the nondestructive determination of moisture content of sawdust, which could lead to optimize wood utilization.

• Korean Journal of Soil Science and Fertilizer
• /
• v.37 no.4
• /
• pp.259-265
• /
• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Information Systems Review
• /
• v.18 no.2
• /
• pp.151-171
• /
• 2016

With the widespread adoption of mobile devices, such as smart phones and smart pads, as well as the rapid growth of mobile technologies, consumer shopping patterns are changing. This study investigates key factors of consumer purchasing intention in a mobile shopping mall context by incorporating trust belief into the theory of planned behavior. We posit perceived usefulness, perceived enjoyment, perceived ease of use, and trust belief as antecedents of behavioral attitude toward mobile shopping malls. Moreover, social influence and security are identified as key enablers of trust belief on mobile shopping malls. Data collected from 154 consumers with purchasing experience in mobile shopping malls are empirically tested against a research model using partial least squares. Analysis results show that behavioral attitude and perceived behavioral control significantly influence purchasing intention. Moreover, this study reveals the significant effects of perceived usefulness and perceived enjoyment on behavioral attitude. Trust belief indirectly influences purchasing intention through behavioral attitude and is significantly affected by social influence. Understanding consumer purchasing decision-making processes in mobile shopping malls can help service providers to develop effective marketing and operation strategies and campaigns.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.53 no.3
• /
• pp.244-250
• /
• 2008

The purpose of this study was to measure fundamental data required for the prediction of milling ratios, and to develop regression models to predict the head rice ratio of milled rice using NIR spectra of hulled rice. A total of 81 rice samples used in this study were collected from Jeongeup, Jeonbuk province in 2006. NIR spectra were measured using one mode of measurement, reflection. The reflectance spectra were measured in the wavelength region of 400-2500 nm with an NIR spectrophotometer "NIRSystems 6500" (Foss, Silverspring, USA). Calibration equations were developed by the modified partial least squares (MPLS), partial least squares (PLS), and principal components regression (PCR). Math treatments were 1-4-4-1, 1-10-10-1, 2-4-4-1, and 2-10-10-1. The software used was WinISI (Infrasoft International, State College, USA). Automatic head rice production and quality checking system used was "SY2000-AHRPQCS" (Ssangyong, Korea). The calibration was made with the first derivative and the spectrum designated was in 8 nm interval. The determination coefficients of head rice ratios were 0.8353, 0.8416 and 0.5277 for the MPLS, PLS and PCR, respectively. Those obtained with 20 nm interval were 0.8144, 0.8354 and 0.6908 for the MPLS, PLS and PCR, respectively. The calibration was made with second derivative that spectrum designated was 8 nm in interval. The determination coefficients of head rice ratios were 0.7994, 0.8017 and 0.4473 for the MPLS, PLS and PCR, respectively. Those with 20 nm interval were 0.8004, 0.8493 and 0.6609 for the MPLS, PLS and PCR, respectively. These results indicate that the accuracy of determination coefficient for MPLS and PLS is higher than that of PCR.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.53 no.1
• /
• pp.15-20
• /
• 2008

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure anthocyanin contents in black colored soybean by using NIRS system. Total 300 seed coat of black colored soybean samples previously analyzed by HPLC were scanned by NIRS and over 250 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed in which the coefficient of determination for anthocyanin pigment C3G, D3G and Pt3G content was 0.952, 0.936, and 0.833, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in C3G and D3G content file. In case Pt3G, the prediction model was needed more accuracy because of low $R^2$ value in validation set. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of C3G and D3G contents in black colored soybean.

• Journal of Korea Port Economic Association
• /
• v.31 no.3
• /
• pp.15-39
• /
• 2015

This paper investigates the determinants of port service quality from a resources-based approach. The research model is derived from the relevant literature in port management, service quality, and resource-based theory. It is hypothesized that tangible and intangible resources contribute to port service quality, which in turn leads to the enhancement of reputation and loyalty to ports. To test this, a questionnaire survey is undertaken on three major ports in Korea: Busan, Incheon, and Gwangyang; the collected data are then analyzed using partial least squares. It is suggested that both tangible resources and intangible resources have a positive influence on general service quality and that general service quality has a positive influence on customer satisfaction, thus improving port reputation and loyalty. The contribution to the literature is that resource-based theory is applied to a port service quality model and the model is verified. In addition, an augmented model is adopted to examine the effect of individual resources on service quality. It is also possible for port managers to use the constructs to monitor their resources and develop more specific strategies to gain reputation and loyalty from customers.

• Korean Journal of Optics and Photonics
• /
• v.20 no.6
• /
• pp.346-353
• /
• 2009

Glucose and protein in urine are among the important substances for urine analysis and have generally been measured based on a reagent strip test. In this study, these two substances were measured using mid-infrared absorption spectroscopy. Samples were prepared from a commercial synthetic urine product. Glucose and albumin were added as well as red blood cells, which are expected to create the most spectroscopic interference of any substance. Concentrations of these substances were varied independently. Optimal wavelength regions were determined from a partial least squares regression analysis (glucose 980 - 1150/cm, albumin 1400 - 1570/cm). Interference by other substances increased the differences between measured and predicted values. Albumin measurement in particular weres heavily influenced by the presence of glucose and red blood cells. Depending on the inference by other substances, measurement errors were 29.85${\sim}$45.19 mg/dl for a glucose level between 0 and 1000 mg/dl and 14.0${\sim}$93.11 mg/dl for an albumin level of 0 ${\sim}$ 500 mg/dl. Our study proposes an alternative to the chemical test-strip analysis, which shows only discrete concentration levels.