• 한국초지조사료학회지
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• 제37권4호
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Journal of the Korean Wood Science and Technology
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• 제44권6호
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1481-1488
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• 2014

Background: To avoid performing axillary lymph node dissection (ALND) for non-sentinel lymph node (SLN)-negative patients with-SLN positive axilla, nomograms for predicting the status have been developed in many centers. We created a new nomogram predicting non-SLN metastasis in SLN-positive patients with invasive breast cancer and evaluated 14 existing breast cancer models in our patient group. Materials and Methods: Two hundred and thirty seven invasive breast cancer patients with SLN metastases who underwent ALND were included in the study. Based on independent predictive factors for non-SLN metastasis identified by logistic regression analysis, we developed a new nomogram. Receiver operating characteristics (ROC) curves for the models were created and the areas under the curves (AUC) were computed. Results: In a multivariate analysis, tumor size, presence of lymphovascular invasion, extranodal extension of SLN, large size of metastatic SLN, the number of negative SLNs, and multifocality were found to be independent predictive factors for non-SLN metastasis. The AUC was found to be 0.87, and calibration was good for the present Ondokuz Mayis nomogram. Among the 14 validated models, the MSKCC, Stanford, Turkish, MD Anderson, MOU (Masaryk), Ljubljana, and DEU models yielded excellent AUC values of > 0.80. Conclusions: We present a new model to predict the likelihood of non-SLN metastasis. Each clinic should determine and use the most suitable nomogram or should create their own nomograms for the prediction of non- SLN metastasis.

• 한국물환경학회지
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• 제30권1호
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• pp.44-59
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• 2014

Despite the implementation of TMDL, the water quality in lower watershed of Nam river dam has worsened continuously since 2005. Multifarious pollution sources such as cities and industrial districts are scattered around it. Nam river downstream bed slope is very gentle towards the downstream water flow of slows it down even more, depending on the water quality deterioration is accelerated eutrophication occurs. In this study, the mainstream in lower watershed of Nam river dam region to target aquatic organic matter by phytoplankton growth contribution was evaluated by statistical analysis. and statistical evaluation of water quality and the accuracy of forecasting, model calibration and verification procedures by completing QUALKO2 it's eutrophic phenomena that occur frequently in the dam outflow through scenarios predict an increase in water quality management plans to present the best should.

• Journal of Biosystems Engineering
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• 제38권4호
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.

• Journal of Animal Science and Technology
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• 제64권3호
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• Asian Pacific Journal of Cancer Prevention
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• 제16권9호
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• pp.3773-3777
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• 2015

Background: This study aimed to establish a nomogram by combining clinicopathologic factors with overall survival of stage IA-IIB cervical cancer patients after complete resection with pelvic lymphadenectomy. Materials and Methods: This nomogram was based on a retrospective study on 1,563 stage IA-IIB cervical cancer patients who underwent complete resection and lymphadenectomy from 2002 to 2008. The nomogram was constructed based on multivariate analysis using Cox proportional hazard regression. The accuracy and discriminative ability of the nomogram were measured by concordance index (C-index) and calibration curve. Results: Multivariate analysis identified lymph node metastasis (LNM), lymph-vascular space invasion (LVSI), stromal invasion, parametrial invasion, tumor diameter and histology as independent prognostic factors associated with cervical cancer survival. These factors were selected for construction of the nomogram. The C-index of the nomogram was 0.71 (95% CI, 0.65 to 0.77), and calibration of the nomogram showed good agreement between the 5-year predicted survival and the actual observation. Conclusions: We developed a nomogram predicting 5-year overall survival of surgically treated stage IA-IIB cervical cancer patients. More comprehensive information that is provided by this nomogram could provide further insight into personalized therapy selection.

• 한국환경농학회지
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• 제33권3호
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• pp.205-212
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• 2014

BACKGROUND: This study focused on the contents of flavonoid compounds in vegetables. Generally vegetables have contributed to a healthy diet, arisen from contains a large amount of fiber and functional ingredients. And flavonoid compounds are one of major functional components in the vegetables. currently research of flavonoid contents does not enough, specially in the part of homegrown vegetable. METHODS AND RESULTS: Vegetable samples were purchased in domestic market. Sample extraction by methanol, distilled water, and formic acid based solvent. Also same solvent used for mobile phase in UPLC. Eleven types of flavonoid compounds were analyzed with same kind of external standard and one kind of internal standard (galangin) for quantification. Standard calibration curve presented linearity with the correlation coefficient $R^2$ > 0.98, analysed from 1 to 50 ppm concentration. The quantitative value and multivariate analysis results were derived from the Excel and SIMCA-P11. Overall, onion has largest amount(916.5 mg/100 g) of flavonoid and also other vegetables have has significant amount[Mugwort: 138.8, Galic stem:123.6 mg/100 g etc.] of flavonoid compounds. Edible portion of vegetables per share for simulating by SIMCA-P11, root vegetables has had difference with other vegetables according to distributions and amounts of flavonoid compounds. CONCLUSION: Optionally, the results from this experiment can use to select the material for flavonoid researches. And based on these results, if this experiment will be continuously complemented, and performed, could used in various fields.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권1호
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• pp.50-61
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• 2000

최근 원추곡선에 기반한 스테레오 비젼에 대한 연구가 주목을 받고 있는데, 이는 원추곡선이 행렬표현, 대응관계설정의 용이성, 그리고 실세계에서 쉽게 찾을 수 있다는 좋은 성질을 갖는다는 점에서 당연한 현상이라 여겨진다. 하지만, 일반적인 고차의 대수곡선에 대한 확장은 아직 성공적으로 이루어지지 못하고 있는 실정이다. 기약인 대수곡선 (irreducible algebraic curve)은 실세계에서 많지 않지만, 직선과 원추곡선은 무수히 많고, 따라서 이들의 곱으로 주어지는 높은 차수의 대수곡선도 무수히 많다. 본고에서는 2이상의 임의의 차수를 가지는 대수곡선을 calibration된 두 대의 카메라를 가지고 스테레오 문제를 푼다. 대응관계설정과 복원, 두 가지 문제 모두에 대한 closed form solution을 제시한다. $f_1,\;f_2,\;{\pi}$를 각각 두 이미지 곡선, 공간상의 평면이라 하고, $VC_P(g)$를 평면곡선 g와 점 P로 만들어지는 원추곡선이라 하면, $VC_{O1}(f_1)\;=\;VC_{O1}(VC_{O2}(f_2)\;∩\;{\pi})$ 의 관계를 이용하여 미지수인 평면 ${\pi}$의 계수들, $d_1,\;d_2,\;d_3$에 대한 다항 방정식들을 얻을 수 있다. 약간의 변형을 통하여 $d_1$에 대한 다항 방정식을 얻을 수 있고, 이 방정식의 유일한 양수해는 나머지 과정에서 매우 중요한 역할을 한다. 그 이후에는 $O(n^2)$개의 일변수 다항식에 대한 계산만으로 모든 스테레오 문제를 해결한다. 이는 과거의 여러 개의 다변수 다항식의 공통근을 구해야 했던 방법에 비교된다. synthetic 데이터와 실제 이미지에 대한 실험은 우리의 알고리듬이 옳음을 보여준다.

• Journal of Plant Biotechnology
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• 제42권1호
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• pp.60-70
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• 2015

본 연구의 목적은 적외선 분광스펙트럼 데이터를 이용하여 대두 종자내의 지방산 함량을 동시에 예측할 수 있는지 여부를 조사하기 위한 것이다. 총 153종의 대두(Glycine max Merrill) 종자로부터 적외선 분광스펙트럼 및 지방산의 함량을 기체크로마토그라피 분석을 통하여 확인하였다. 적외선 분광스펙트럼 조사결과 대두는 단백질이나 아미노산의 amide bond region ($1,700{\sim}1,500cm^{-1}$), 핵산이나 인지질의 phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) 그리고 탄수화물 등 다당류의 sugar region ($1,200{\sim}1,000cm^{-1}$)에서 계통별로 큰 차이가 이루어짐을 알 수 있었다. 총 29라인의 대두 계통별 시료로부터 지방산 함량을 조사한 결과 총 지방산의 함량은 건조 시료 0.1 g 당 $185.57{\mu}g$에서 $325.9{\mu}g$으로 계통간에 차이가 있었음을 알 수 있었으며 평균 함량은 $244.48{\mu}g$이었다. PLS regression 분석을 이용하여 총 5개 지방산(팔미틱산, 스테아릭산, 올레익산, 리노레익산 그리고 리노레닉산) 함량 예측 calibration models의 실측 검증 결과, 팔미틱산($R^2=0.8002$), 올레익산($R^2=0.8909$) 그리고 리노레익산($R^2=0.815$)은 회귀분석 상관계수가 0.8 이상으로 정확도 높음을 알 수 있었다. 그러나 스테아릭산($R^2=0.4598$)과 리노레닉산($R^2=0.6868$)의 경우 상관계수가 0.7 이하로 상대적으로 예측정확도가 낮음을 알 수 있었다. 본 연구에서 확립된 기술은 지방산의 조성 변환을 통하여 새로운 대두 품종 개발을 위한 계통선발 과정에서 매우 효율적인 수단으로 활용이 가능할 것으로 사료된다. 더 나아가 본 기술은 대두는 물론 대두 유래 농산물이나 식품의 품질 검증 수단으로 활용이 가능할 것으로 기대된다.