• Food Science of Animal Resources
• /
• v.40 no.1
• /
• pp.96-105
• /
• 2020

The appearance of white striations over breast meat is an emerging and growing problem. The main purpose of this study was to employ the reflectance of visible-near infrared (VIS/NIR) spectroscopy to differentiate between normal and white striped turkey breasts. Accordingly, 34 turkey breast fillets were selected representing a different level of white striping (WS) defects (normal, moderate and severe). The findings of VIS/NIR were analyzed by principal component (PC1) analysis (PCA). It was found that the first PC1 for VIS, NIR and VIS/NIR region explained 98%, 97%, and 96% of the total variation, respectively. PCA showed high performance to differentiate normal meat from abnormal meat (moderate and severe WS). In conclusion, the results of this research showed that VIS/NIR spectroscopy was satisfactory to differentiate normal from severe WS turkey fillets by using several quality traits.

• Journal of electromagnetic engineering and science
• /
• v.17 no.4
• /
• pp.186-190
• /
• 2017

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450-1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.1
• /
• pp.31-37
• /
• 2014

The aim of this study was the non-destructive evaluation of bloody eggs using VIS/NIR spectroscopy. The bloody egg samples used to develop the sorting mode were produced by injecting chicken blood into the edges of egg yolks. Blood amounts of 0.1, 0.7, 0.04, and 0.01 mL were used for the bloody egg samples. The wavelength range for the VIS/NIR spectroscopy was 471 to 1154 nm, and the spectral resolution was 1.5nm. For the measurement system, the position of the light source was set to $30^{\circ}$, and the distance between the light source and samples was set to 100 mm. The minimum exposure time of the light source was set to 30 ms to ensure the fast sorting of bloody eggs and prevent heating damage of the egg samples. Partial least squares-discriminant analysis (PLS-DA) was used for the spectral data obtained from VIS/NIR spectroscopy. The classification accuracies of the sorting models developed with blood samples of 0.1, 0.07, 0.04, and 0.01 mL were 97.9%, 98.9%, 94.8%, and 86.45%, respectively. In this study, a novel nondestructive sorting technique was developed to detect bloody brown eggs using spectral data obtained from VIS/NIR spectroscopy.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.104-104
• /
• 2017

정상적인 부화 여부를 판별하기 위한 1차 검란은 일반적으로 5일~7일 이후에 시행된다. 미부화란을 이보다 더 빠른 시간 안에 검출할 경우 부화에 소요되는 에너지의 감소 효과 및 미부화란을 다른 용도로 활용하는 것을 기대할 수 있다. 시중에서 쉽게 구입할 수 있는 산란계인 하이라인 브라운 품종의 유정란 29개와 인위적인 미부화란을 만들기 위한 동일 품종의 무정란 11개를 사용하였으며 $38^{\circ}C$, 70% 조건의 항온항습기에서 96시간 동안 부화하였다. 스펙트럼 획득 장치의 광원은 녹색영역을 발광하는 LED램프와 일반 할로겐 광원을 별도로 사용하였으며 스펙트로미터는 VIS/NIR 영역인 520~1,180nm영역과 NIR영역인 900~1,700nm영역의 것을 사용하였다. 부화 시작 전과 부화 시작 후 1일 간격으로 각각 1개의 샘플에 대한 1개의 스펙트럼을 측정하였다. 측정 영역은 LED광원을 이용한 경우는 520~1,1800nm, 할로겐광원을 이용한 경우에는 520~1,180nm와 900~1,700nm이었다. 정상 부화여부는 4일차에서 할란하여 확인하였고, 측정 일자별로 PLS-DA분석법을 이용한 판별 모델을 개발하였다. 4일차에서 유정란 29개 중 11개가 정상 부화하였고, 18개는 미부화하였다. 3일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 70%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 70%였다. 4일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 90%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 100%였다. 부화 3일차는 정상 부화할 경우 피가 생성되는 시기이다. 피가 형성된 이후의 부화 여부를 판단하는 광원으로는 할로겐램프보다 LED램프를 사용하는 것이 더 적합한 것으로 나타났다.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2000.06a
• /
• pp.9-16
• /
• 2000

• Journal of the Korean Ceramic Society
• /
• v.49 no.6
• /
• pp.493-497
• /
• 2012

We propose a new reliable, fast, and low cost identification method for similarly looking 0.3ct vivid yellow color of natural, HPHT treated, and synthesized diamonds. Conventional optical microscopy as well as low temperature PL(photoluminescence), FT-IR, UV-VIS-NIR, micro-Raman spectroscopy, and vibrating sample magnetometry(VSM) characterization were executed. We could not distinguish the natural diamonds from the treated or the synthesized stones with an optical microscopy, PL, FT-IR, and UV-VIS-NIR spectroscopy. However, we could identify the treated diamond with micro-Raman spectroscopy due to unique $1440cm^{-1}$ peak appearance. VSM revealed easily the synthesized diamond because of its ferromagnetic behavior. Our preliminary propose on employing the Micro-Raman spectroscopy and VSM might be suitable for identification of the similar looking vivid yellow colored diamonds.

• Agricultural and Biosystems Engineering
• /
• v.4 no.1
• /
• pp.1-7
• /
• 2003

Internal defects such as browning of the flesh and blackening and rot of the ovary of pear can be easily developed because of the inadequate environmental conditions during the storage and distribution of fruit. The quality assurance system for the agricultural product is to be settled in Korea. All defected agricultural products should be excluded prior to the distribution to enhance the commercial values. However, early stage on-line defect detection of agricultural product is very difficult and even more difficult in a case of the internal defects. The goal of this research is to develop a system that can detect and classify internal defects of agricultural produce on-line using VIS/NIR transmittance spectroscopy. And Shingo pear, which is one of the famous species of Korean pear, was used for the experiment. Soft independence modeling of class analogy (SIMCA) algorithm was employed to analyze the transmittance spectroscopic data qualitatively. On-line classification system was constructed and classification model was developed and validated. As a result, the correct classification rate (CCR) using the developed classification model was 96.1 ％.

• Korean Journal of Environmental Biology
• /
• v.39 no.4
• /
• pp.581-589
• /
• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Carbon letters
• /
• v.10 no.1
• /
• pp.9-13
• /
• 2009

We propose an evaluation method of the relative content of single-walled carbon nanotubes (SWCNT) in SWCNT soot synthesized by arc discharge using UV-VIS-NIR absorption spectroscopy. In this method, we consider the absorbance of semiconducting and metallic SWCNTs together to calculate the relative content of SWCNTs with respect to a highly purified reference. Our method provides the more reliable and realistic evaluation of SWCNT content with respect to the whole carbonaceous content than the previously reported method.

• Analytical Science and Technology
• /
• v.5 no.1
• /
• pp.135-142
• /
• 1992

Indium tin oxide(ITO) films coated on the window glass selectively transmit the solar energy and infrared. We call this system passive solar collectors. Selectively absorbing properties of sol gel dip coated ITO films were characterized by UV-VIS-NIR spectroscopy. The effects of heat treating temperature, time, atmosphere, substrate and barrier layers are concerned. Indium tin oxide films heat-treated at $500^{\circ}C$ in a reducing atmosphere show intrinsic properties. Efficiency of solar energy transmittance was enhanced by coating of $SiO_2-ZrO_2$ as an alkali ion barrier layer. Energy was saved by the double layers of $SiO_2-ZrO_2$ and ITO since solar energy is transmitted and heat generated inside(${\lambda}$ > 2700nm) is reflected.