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

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

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

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.02a
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• pp.464-469
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• 2000

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2001.02a
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• pp.359-364
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• 2001

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.340-345
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• 1999

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.02a
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• pp.457-463
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• 2000

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.02a
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• pp.451-456
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• 2000

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.382-389
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• 2009

An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.

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