• 한국조경학회지
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• 제45권3호
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• pp.92-106
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• 2017

이 연구에서는 장기미집행 도시공원 및 녹지 토지보상 재원마련을 위한 지방채 발행의 타당성을 검토하였고, 지방채를 발행하여 지가 상승이 높은 지역을 우선보상할 것을 제안하였다. 이를 위해 장기미집행 도시공원 및 녹지 32개소를 대상으로 상관분석과 부분최소제곱(Partial Least Square: PLS) 회귀분석을 실시함으로써 '7년간 개별공시지가 상승가'에 영향을 미치는 요인을 규명하였다. PLS 회귀분석의 투영시 변수 중요도 값은 '기준년도 개별공시지가(1.919)', '해당 자치구 누적상승률(1.176)' 순으로 높았다. 본 연구의 시사점은 다음과 같다. 지난 12년간 서울의 평균개별공시지가 누적상승률이 지방채 누적이자율보다 더 높다는 것은 지방채 발행으로 지급해야 하는 이자보다 개별공시지가가 더 많이 올랐다는 것을 의미한다. 더구나 실보상가는 개별공시지가의 3배 정도 되므로, 실제로는 지급이자액보다 훨씬 더 많은 지가 상승이 이루어졌을 것이다. 이는 지방채를 발행하여 지가상승이 높은 지역과 같은 보상우선대상지를 선매수하는 것이 예산집행에 있어서 경제성과 효율성을 높일 수 있음을 보여준다. 또한 예산집행의 경제적 효율성을 위하여, 지가 상승이 높을 것으로 예상되는 '개별공시지가가 높은 곳', '지가 상승이 높은 자치구에 속한 곳'을 우선보상 기준항목으로 선정하는 것이 필요함을 보여준다. 앞으로, 장기미집행 도시공원 및 녹지 토지보상을 위해서 지방채를 발행할 경우, 지방채 상환재원 마련방안에 대한 다양한 연구도 함께 진행되어야 할 것이다.

• Journal of Biosystems Engineering
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• 제41권3호
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• 한국작물학회지
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• 제54권1호
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• pp.55-60
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• 2009

녹차, 부분발효차 및 발효차 등 다양한 차제품 117개 제품을 수집하여 분말화하여 측색계로 각 차제품의 표면 색상을 측정한 후 NIRS를 이용하여 가시광선 대역($400{\sim}700$ nm)에서 스펙트럼을 얻어 중회귀분석에 의해 각각 색상 관련 특성에 대한 검량식을 작성하였다. 1. 측색계로 제품의 색상을 측정한 결과 CIE color scale에서 L값(6.98), a값(0.25) 및 b값(15.42)이 높았으나, a/b(0.09)값은 Hunter color scale에서 높았다. 또한 색상관련 특성 $a^*$(a)와 $a^*/b^*$(a/b)의 변이계수가 $317.2{\sim}327.5%$와 $293.8{\sim}316.7%$로 제품간 변이성이 매우 컸다. 2. CIE color scale와 Hunter color scale에서 발효정도($X_9$)의 변이를 $a^*/b^*(X_4)$나 a/b($X_8$)로 99.7% 설명될 수 있어 $a^*/b^*$(a/b)값으로 차제품의 발효정도를 추정할 수 있다. 3. Modified partial least square(MPLS)를 이용하여 작성된 검량식의 결과 두 color scale을 종합하여 L값의 검량식 작성시 결정계수($R^2$)는 $0.973{\sim}0.977$, 검증시 상관도(1-VR) $0.969{\sim}0.972$, a값의 결정계수는 0.999, 검증시 상관도 0.998, b값의 결정계수는 $0.858{\sim}0.902$, 검증시 상관도 $0.833{\sim}0.888$, a/b값의 결정계수는 0.997, 검증시 상관도 0.993으로 매우 높았다. 4. 차 제품 표면 색상관련 특성들(CIE color scale; $L^*$, $a^*$, $b^*$, $a^*/b^*$, Hunter color scale; L, a, b, a/b)의 검량식 정확도가 매우 높아서 NIRS의 가시광선 대역($400{\sim}700\;nm$)에서 이들 특성을 용이하고 정밀하게 측정할 수가 있으며, 또한 근적외선 대역($900{\sim}2500\;nm$)에서 기존 성분분석 화일과 병합하여(merge) 차 제품의 표면 색상 및 화학적 성분을 $1{\sim}2$분내로 동시에 측정이 가능하다.

• 대한화학회지
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• 제53권6호
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• pp.717-726
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• 2009

Triton X-100이 함유된 상태에서 정색시약인 1-(2-thiazolylazo)-2-naphthol이 첨가된 물에서 구리 (II), 니켈(II)과 아연(II)의 동시 분광광도법적 정량을 위한 다변량 모델들이 개발되었다. 분광학적 간섭의 단점을 극복하기 위해서, 주성분회귀분석법(PCR)과 부분최소자승법(PLS) 다변량 분석법적 접근이 적용되었다. 다양한 시험 세트를 사용하여 본 방법의 수행이 입증되었고 그 결과들이 비교되었다. 일반적으로 PLS와 PCR 모델들 사이에 분석적 수행에서의 심각한 차이가 없었다. $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ 의 세 성분들을 사용한 예측의 제곱근 평균 제곱 오차(RMSEP)들은 각각 0.018, 0.010, 0.011 ppm이었다. 또한 감도, 분석감도, 검출한계(LOD)와 같은 가치들의 측면들이 평가되었다. 본 논문에서 제안하는 과정이 화합물 혼합용액과 수돗물 속의 $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$의 동시 검출에 적용되었을 때에 높은 신뢰도가 성취되었다.

• Journal of Biosystems Engineering
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• 제43권2호
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• 농업과학연구
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• 제39권3호
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• pp.413-420
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• 2012

Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

• 한국초지조사료학회지
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• 제34권4호
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• pp.277-282
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• 2014

Nutritive value analysis of feed is very important for the growth of livestock, and ensures the efficiency of feeds as well as economic status. However, general laboratory analyses require considerable time and high cost. Near-infrared reflectance spectroscopy (NIRS) is a spectroscopic technique used to analyze the nutritive values of seeds. It is very effective and less costly than the conventional method. The sample used in this study was a corn kernel and the partial least square regression method was used for evaluating nutrient composition, digestibility, and energy value based on the calibration equation. The evaluation methods employed were the coefficient of determination ($R^2$) and the root mean squared error of prediction (RMSEP). The results showed the moisture content ($R^2_{val}=0.97$, RMSEP=0.109), crude protein content ($R^2_{val}=0.94$, RMSEP=0.212), neutral detergent fiber content ($R^2_{val}=0.96$, RMSEP=0.763), acid detergent fiber content ($R^2_{val}=0.96$, RMSEP=0.142), gross energy ($R^2_{val}=0.82$, RMSEP=23.249), in vitro dry matter digestibility ($R^2_{val}=0.68$, RMSEP=1.69), and metabolizable energy (approximately $R^2_{val}$ >0.80). This study confirmed that the nutritive components of corn kernels can be predicted using near-infrared reflectance spectroscopy.

• 한국연초학회지
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• 제35권1호
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• pp.1-6
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• 2013

Near InfraRed Spectroscopy(NIRS) is a quick and accurate analytical method to measure multiple components in tobacco manufacturing process. This study was carried out to develop calibration equation of near infrared spectroscopy for the prediction of the amount of chemical components and hot water solubles(HWS) of reconstituted tobacco leaf. Calibration samples of reconstituted tobacco leaf were collected from every lot produced during one year. The calibration equation was formulated as modified partial least square regression method (MPLS) by analyzing laboratory actual values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with the standard error of prediction(SEP) of chemical components in reconstituted tobacco leaf samples, indicated as coefficient of determination($R^2$) and prediction error of sample unacquainted, followed by the verification of model equation of laboratory actual values and these predicted results. As a result of monitoring, the standard error of prediction(SEP) were 0.25 % for total sugar, 0.03 % for nicotine, 0.03 % for chlorine, 0.16 % for nitrate, and 0.38 % for hot water solubles. The coefficient of determination($R^2$) were 0.98 for total sugar, 0.97 for nicotine, 0.96 for chlorine, 0.98 for nitrate and 0.92 for hot water solubles. Therefore, the NIRS calibration equation can be applicable and reliable for determination of chemical components of reconstituted tobacco leaf, and NIRS analytical method could be used as a rapid and accurate quality control method.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4104-4104
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• 2001

Milk somatic cell count (SCC) is a recognized indicator of cow health and milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm to measure SCC content of cow milk was investigated. A total of 196 milk samples from 7 Holstein cows were collected for 28 days, consecutively, and analyzed for fat, protein, lactose and SCC. Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in a wavelength range from 1100 to 2500 nm. The calibration for logSCC was performed using partial least square (PLS) regression and different spectral data pretreatment. The best accuracy of determination was found for equation, obtained using smoothed absorbance data and 10 PLS factors. The standard error of calibration was 0.361, calibration coefficient of multiple correlation 0.868, standard error of prediction for independent validation set of samples 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. The accuracy of logSCC determination by NIR spectroscopy would allow health screening of cows, and differentiation between healthy and mastitic milk samples. When the spectral information was studied it has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. In the case of mastitis, when the disease occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk.

• 원예과학기술지
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• 제30권6호
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• pp.709-717
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• 2012

To establish the standard of ripe kiwifruit sorting, near infrared (NIR) spectroscopy was performed on kiwifruit sampled from three farms. Destructive measurements of flesh firmness, soluble solids content (SSC), and acidity were performed and compared to measurement using NIR reflectance spectrums from 408 to 2,492 nm. NIR predictions of those quality factors were calculated using the modified partial least square regression method. Flesh firmness was predicted with a standard error of prediction (SEP) of 3.32 N and with a correlation coefficient ($R^2$) of 0.88. SSC was predicted with SEP of $0.49^{\circ}Brix$ and with $R^2$ of 0.98. Acidity was predicted with SEP of 0.28% and with $R^2$ of 0.91. Kiwifruit ripened at $20^{\circ}C$ for 15 days showed uneven qualities with normal distribution. Considering the SEP of each parameter, kiwifruit after ripening treatment could be non-destructively predicted their qualities and sorted by flesh firmness or soluble solids content through NIR prediction.