• Asian-Australasian Journal of Animal Sciences
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• 제31권10호
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• pp.1670-1676
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• 2018

Objective: This study was conducted to enable on-line prediction of primal and commercial cut weights in Korean slaughter pigs by AutoFom III, which non-invasively scans pig carcasses early after slaughter using ultrasonic sensors. Methods: A total of 162 Landrace, Yorkshire, and Duroc (LYD) pigs and 154 LYD pigs representing the yearly Korean slaughter distribution were included in the calibration and validation dataset, respectively. Partial least squares (PLS) models were developed for prediction of the weight of deboned shoulder blade, shoulder picnic, belly, loin, and ham. In addition, AutoFom III's ability to predict the weight of the commercial cuts of spare rib, jowl, false lean, back rib, diaphragm, and tenderloin was investigated. Each cut was manually prepared by local butchers and then recorded. Results: The cross-validated prediction accuracy ($R^2cv$) of the calibration models for deboned shoulder blade, shoulder picnic, loin, belly, and ham ranged from 0.77 to 0.86. The $R^2cv$ for tenderloin, spare rib, diaphragm, false lean, jowl, and back rib ranged from 0.34 to 0.62. Because the $R^2cv$ of the latter commercial cuts were less than 0.65, AutoFom III was less accurate for the prediction of those cuts. The root mean squares error of cross validation calibration (RMSECV) model was comparable to the root mean squares error of prediction (RMSEP), although the RMSECV was numerically higher than RMSEP for the deboned shoulder blade and belly. Conclusion: AutoFom III predicts the weight of deboned shoulder blade, shoulder picnic, loin, belly, and ham with high accuracy, and is a suitable process analytical tool for sorting pork primals in Korea. However, AutoFom III's prediction of smaller commercial Korean cuts is less accurate, which may be attributed to the lack of anatomical reference points and the lack of a good correlation between the scanned area of the carcass and those traits.

• Journal of Crop Science and Biotechnology
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• 제10권1호
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• pp.13-18
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• 2007

Near-infrared spectroscopy(NIRS) was used as a rapid and nondestructive method to determine the fatty acid composition in intact seed samples of rapeseed(Brassica napus L.). A total of 349 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations for individual fatty acids were developed using the regression method of modified partial least-squares with internal cross validation(n=249). The equations had low SECV(standard errors of cross-validation), and high $R^2$(coefficient of determination in calibration) values(>0.8) except for palmitic and eicosenoic acid. Prediction of an external validation set(n=100) showed significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP. The models developed in this study had relatively higher values(> 3.0 and 0.9, respectively) of SD/SEP(C) and $r^2$ for oleic, linoleic, and erucic acid, characterizing those equations as having good quantitative information. The results indicated that NIRS could be used to rapidly determine the fatty acid composition in rapeseed seeds in the breeding programs for high quality rapeseed oil.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4112-4112
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• 2001

The feasibility of NIR spectroscopy as a quick and nondestructive method for quality control of uniformity of coating thickness of pharmaceutical tablets was investigated. Near infrared spectra of a set of pharmaceutical tablets with varying coating thickness were measured with a diffuse reflectance fiber optic probe connected to a Broker IFS 28/N FT-NIR spectrometer. The challenging issues encountered in this study included: 1. The similarity of the formulation of the core and coating materials, 2. The lack of sufficient calibration samples and 3. The non-linear relationship between the NIR spectral intensity and coating: thickness. A peak at 7184 $cm^{-1}$ was identified that differed for the coating material and the core material when M spectra were collected at 2 $cm^{-1}$ resolution (0.4 nm at 7184 $cm^{-1}$). The study showed that the coating thickness can be analyzed by polynomial fitting of the peak area of the selected peak, while least squares calibration of the same data failed due to the lack of availability of sufficient calibration samples. Samples of coal powder and solid pieces of coal were analyzed by FT-NIR diffuse reflectance spectroscopy with the goal of predicting their ash content, percentage of volatile components, and energy content. The measurements were performed on a Broker Vector 22N spectrometer with a fiber optic probe. A partial least squares model was constructed for each of the parameters of interest for solid and powdered sample forms separately. Calibration models varied in size from 4 to 10 PLS ranks. Correlation coefficients for these models ranged from 86.6 to 95.0%, with root-mean-square errors of cross validation comparable to the corresponding reference measurement methods. The use of FT-NIR diffuse reflectance measurement techniques was found to be a significant improvement over existing measurement methodologies in terms of speed and ease of use, while maintaining the desired accuracy for all parameters and sample forms.(Figure Omitted).

• 응용통계연구
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• 제31권4호
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• pp.447-461
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• 2018

국내 영화 산업 매출은 매년 증가하고 있다. 극장은 영화의 1차 판매 경로이며, 극장을 이용하는 관객 수는 부가판권에 영향을 준다. 따라서 극장을 이용하는 관객의 수는 영화 산업 매출에 직결되는 중요한 요소이다. 본 논문에서 특정일의 관객 수를 예측하기 위하여 다중선형회귀모형과 Bass 모형을 결합한 Hybrid 모형을 고려한다. 두 모형을 결합함으로써 회귀분석의 예측값을 Bass 모형의 예측값으로 보정하였다. 분석에는 개봉일이 모두 다른 세 영화를 이용하였다. All subset regression 방법을 이용해 모든 가능한 조합을 생성하고 5중 교차검증(5-fold cross validation)을 통해 5번 모형을 추정한다. 이 때 제곱근평균오차가 가장 작은 모형으로 예측값을 구한 뒤 Bass 모형의 예측값과 결합해 최종 예측값을 구하게 된다. 과거데이터가 존재할수록 Bass 모형의 가중치는 증가하면서 예측값에 보정효과를 준다는 것을 확인할 수 있었다.

• 응용통계연구
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• 제21권6호
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• pp.1093-1107
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• 2008

매년 전 세계는 여러 자연재해로 인하여 많은 피해를 받고 있다 그 중에서도 강수와 관련한 집중호우와 가뭄, 홍수, 상수원 부족 등으로 많은 손실을 입고 있다. 이러한 재해에 의한 피해를 줄이기 위해서는 기상에 대한 정확한 예측이 필요하다. 따라서 강수량에 대한 정확한 예측을 실시하여 수자원을 적절하게 이용하고 재해에 의한 피해를 줄이기 위하여 많은 연구가 진행되고 있다. 본 연구에서는 강수량을 측정하는 지상기상관측지점자료에 대해 공간적 상관구조를 포함하는 선형회귀모형(크리깅)을 고려하여 세미베리오그램을 기반으로한 최소제곱법과 코베리오그램을 기반으로한 최대우도추정방법으로 남한지역의 공간적 특성을 적절하게 파악할 수 있는 모형들을 찾고 이 모형들을 비교하였다. 공간적 선형회귀모형들에 대한 신뢰성을 검증하기 위하여 자동기상관측지점과 항공기상관측지점에서 측정된 실제값과 예측값을 비교하고 이를 바탕으로 강수량 예측에 관한 발전 및 개선방향에 대해 알아보았다.

• 한국초지조사료학회지
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• 제34권3호
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• pp.209-213
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• 2014

This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical and fermentation parameters of whole crop winter rye silages. A representative population of 216 fresh winter rye silages was used as database for studying the possibilities of NIRS to predict chemical composition and fermentation parameters. Samples of silage were scanned at 1 nm intervals over the wavelength range 680~2,500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in fresh condition. NIRS calibrations were developed by means of partial least-squares (PLS) regression. NIRS analysis of fresh winter rye silages provided accurate predictions of moisture, acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP) and pH as well as lactic acid content with correlation coefficients of cross-validation ($R^2cv$) of 0.96, 0.86, 0.79, 0.85, 0.82 and 0.78 respectively and standard error of cross-validation (SECV) of 1.89, 2.02, 2.79, 1.14, 1.47 and 0.46 % DM respectively. Results of this experiment showed the possibility of NIRS method to predict the chemical parameters of winter rye silages as routine analysis method in feeding value evaluation and for farmer advice.

• 한국초지조사료학회지
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• 제33권3호
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• pp.171-176
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• 2013

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages and feedstuff. This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical parameters of fresh whole crop barley silages. A representative population of 284 fresh whole crop barley silages was used as a database for studying the possibilities of NIRS to predict chemical composition. Samples of silage were scanned at 1 nm intervals over the wavelength range 680~2,500 nm and the optical data were recorded as log 1/Reflectance (log 1/R) and were scanned in fresh condition. NIRS calibrations were developed by means of partial least-squares (PLS) regression. NIRS analysis of fresh whole crop barley silages provided accurate predictions of moisture, acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP) and pH, as well as lactic acid content with correlation coefficients of cross-validation ($R^2cv$) of 0.96, 0.81, 0.79, 0.84, 0.72 and 0.78, respectively, and standard error of cross-validation (SECV) of 1.26, 2.83, 2.18, 1.19, 0.13 and 0.32% DM, respectively. Results of this experiment showed the possibility of the NIRS method to predict the chemical parameters of fresh whole crop barley silages as a routine analysis method in feeding value evaluation and for farmer advice.

• 대한화학회지
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• 제65권4호
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• pp.254-259
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• 2021

The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R², and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918-18.055, 9.014-23.825, and 9.040-13.350 mg/g of dry sample, respectively.

• 한국작물학회지
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• 제67권1호
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• pp.61-66
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• 2022

본 연구는 참깨에 함유된 세사민 및 세사몰린의 함량을 비파괴적으로 신속하게 평가하기 위하여 NIRS 분석을 이용해 검량식을 작성하고 검량식의 적용가능성을 검증하였다. 검량식 작성에 사용된 482점 참깨의 HPLC 분석 결과를 NIRS 스펙트럼에 적용시킨 후 검량식을 작성하였다. 세사민 및 세사몰린의 R² 값은 각각 0.936, 0.875로 조사되었으며 이를 cross validation 한 결과에서도 각각 0.899, 0.781로 조사되어 리그난 함량 분석에 적용 가능할 것으로 판단되었다. 작성된 검량식의 적용가능성을 확인하기 위해 2020년에 생산된 참깨 유전자원 90종의 종자를 NIRS를 통해 분석한 결과 세사민 및 세사몰린의 R²값이 각각 0.653, 0.596으로 크게 낮아졌으나 리그난 함량이 높은 상위 30%의 자원을 선발하는데 무리가 없었다. 따라서 본 연구에서 작성된 NIRS 검량식은 육종 초기에 고리그난 함량을 선발하는데 적용 가능할 것으로 판단된다.

• 비파괴검사학회지
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• 제34권4호
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• pp.283-289
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• 2014

본 연구는 라만 분광법과 부분최소자승법을 이용하여 불량 분말식품을 비파괴적으로 검출할 수 있는 기술을 개발하기 위해 수행되었다. 향신료와 건강보조식품 등으로 소비가 증가하고 있는 마늘과 생강분말을 실험대상으로 선정하고 옥수수 전분을 농도별로 혼합하여 시료를 제작하였다. 라만 반사스펙트럼과 부분최소자승법을 이용하여 불량 분말식품에 혼합된 옥수수 전분의 농도를 예측하기 위한 모델을 개발하고 교차검증을 통해 그 성능을 평가하였다. 또한 변수중요도척도를 이용하여 예측모델의 개발에 기여도가 높은 라만스펙트럼을 선정한 후 이 스펙트럼을 이용하여 새로운 예측모델을 개발하였다. 그 결과 전체 라만 스펙트럼의 약 1/3에 해당하는 스펙트럼 데이터만을 이용하여 전체 라만 스펙트럼을 이용하여 개발된 예측모델과 같은 성능을 갖는 모델을 개발하는 것이 가능하였다.