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RISS 인기검색어
- 검색키워드
- 저자 : ( Byeong-hyo Cho ) (검색결과 100 건)
- 무료
- 기관 내 무료
- 유료
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Cho, Byeong-Hyo,Kang, Tae-Hwan,Lee, Dong-Il,Won, Jin-Ho,Lee, Hee-Sook,Han, Chung-Su Korean Society for Agricultural Machinery 2017 바이오시스템공학 Vol.42 No.2
Purpose: The purpose of this study was to analyze the milling characteristics of white rice depending on the guide angles of the cutting roller's induced guide, as well as to verify optimum milling conditions for the cutting-type milling machine. Methods: Brown rice, which was produced in Cheongju-si, Chungcheongbuk-do, Republic of Korea, in 2014, was used as the experimental material. The milling characteristics of white rice were measured under six different guide angle levels of the cutting roller, which were none, $0^{\circ}$, $5^{\circ}$, $10^{\circ}$, $15^{\circ}$, and $20^{\circ}$. The quantity of brown rice for each experiment was 500 kg, and the milling characteristics were measured according to the whiteness, rice temperature, cracked rice ratio, broken rice ratio, and energy consumption. Results: The whiteness of white rice maintained a uniform level, indicating at range of $38{\pm}0.5$, regardless of the cutting roller guide angles under all conditions. The rice temperature rise during milling was found to be rather low, at $13.9^{\circ}C$ and $13.6^{\circ}C$ at $10^{\circ}$ and $15^{\circ}$ guide angles, respectively. The cracked rice ratio after milling was 18.67%-19.47%, and the broken rice ratio was 0.68% at a $10^{\circ}$ guide angle, which is the lowest in comparison to other guide angles. Energy consumption was lower when the guide was used compared to that with-out the use of the guide. The energy consumption tended to increase as the cutting roller guide angle increased. Conclusions: From the above results, we conclude that the cutting roller guide angles of $0^{\circ}$ and $10^{\circ}$ are suitable for producing high quality rice during milling with a cutting-type milling machine.
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( Byeong-hyo Cho ),( Tae-hwan Kang ),( Dong-il Lee ),( Jin-ho Won ),( Hee-sook Lee ),( Chung-su Han ) 한국농업기계학회 2017 바이오시스템공학 Vol.42 No.2
Purpose: The purpose of this study was to analyze the milling characteristics of white rice depending on the guide angles of the cutting roller`s induced guide, as well as to verify optimum milling conditions for the cutting-type milling machine. Methods: Brown rice, which was produced in Cheongju-si, Chungcheongbuk-do, Republic of Korea, in 2014, was used as the experimental material. The milling characteristics of white rice were measured under six different guide angle levels of the cutting roller, which were none, 0°, 5°, 10°, 15°, and 20°. The quantity of brown rice for each experiment was 500 kg, and the milling characteristics were measured according to the whiteness, rice temperature, cracked rice ratio, broken rice ratio, and energy consumption. Results: The whiteness of white rice maintained a uniform level, indicating at range of 38±0.5, regardless of the cutting roller guide angles under all conditions. The rice temperature rise during milling was found to be rather low, at 13.9°C and 13.6°C at 10° and 15° guide angles, respectively. The cracked rice ratio after milling was 18.67%- 19.47%, and the broken rice ratio was 0.68% at a 10° guide angle, which is the lowest in comparison to other guide angles. Energy consumption was lower when the guide was used compared to that with-out the use of the guide. The energy consumption tended to increase as the cutting roller guide angle increased. Conclusions: From the above results, we conclude that the cutting roller guide angles of 0° and 10° are suitable for producing high quality rice during milling with a cutting-type milling machine.
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Effects of Main Shaft Velocity on Turbidity and Quality of White Rice in a Rice Processing System
Cho, Byeong-Hyo,Kang, Tae-Hwan,Won, Jin-Ho,Kang, Shin-Hyeong,Lee, Hee-Sook,Han, Chung-Su Korean Society for Agricultural Machinery 2017 바이오시스템공학 Vol.42 No.1
Purpose: The purpose of this study is to analyze turbidity and quality characteristics of white rice as a function of main shaft blast velocity and to verify the optimum processing conditions in the cutting type white rice processing system (CTWRPS). Methods: Sindongjin, one of the rice varieties, which used to be produced in Gimje-si, Jeollabuk-do, in 2015, was used as the experimental material. Turbidity and quality characteristics of white rice were measured at three different main shaft blast velocities: 25, 30, and 35 m/s. The amount of test material used for a single experiment was 20 kg, and after processing, whiteness was found to be $42.5{\pm}0.5$, following which, turbidity and quality characteristics were measured. Results: Turbidity decreased with increase in the shaft blast velocity, and as a result, was lowest at 35 m/s of shaft blast velocity among all the other experiment velocities. The trend of cracked rice ratios was similar to the turbidity. Broken rice ratio turned out to be less than 2.0% in all the test conditions. In the first stage of processing, the processing pressure decreased as the main shaft blast velocity increased. Additionally, in the second stage of processing, the processing pressure was at its lowest value at the main shaft blast velocity of 35 m/s. Energy consumption, too, decreased as the main shaft blast velocity was increased. Conclusions: From the above results, it is concluded that the main shaft blast velocity of 35 m/s is best for reducing turbidity and producing high quality rice in a CTWRPS.
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Byeong Hyo Cho,Tae Hwan Kang,Chung Su Han,Jung Hyun Lee,Dong Il Lee,Hyun Kwon Noh 한국원예학회 2018 원예과학기술지 Vol.36 No.3
The objective of this research was to develop a model to measure the external quality traits using Multi-Spectral Image Sensor (MSIS) in lettuce. In addition, this study was conducted to examine the effect of different intensities of LED mixed light on the growth of lettuce in a closed-type plant factory. The prediction models of lettuce growth data (shoot fresh weight, shoot dry weight, and leaf area) were developed using the correlation between growth data and the number of pixels on an acquired image. Also, SPAD value prediction models were developed using the correlation between the reflectance of a lettuce leaf in an acquired multi-spectral image and the measured SPAD value of the lettuce leaf. The characteristics of lettuce growth according to the light intensity in a closed-type plant factory was conducted under light intensities of 100, 150, and 200 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP>. At 200 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP> light intensity, the shoot fresh weight increased about 27.37-73.93% when compared to 100 and 150 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP> on 20 days after sowing. The shoot dry weight showed a similar tendency. Lettuce leaf area increased by 6.89-52.52% on 20 days after sowing when compared to plants grown under 100 and 150 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP>. At a light intensity of 200 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP>, the SPAD value increased about 3.56-23.76% when compared to plants grown under 100 and 150 μmol · m<SUP>-2</SUP> · s<SUP>-1</SUP>. Using prediction models based on the number of pixels on a lettuce leaf image, lettuce growth data (shoot fresh weight, shoot dry weight, and leaf area) can be predicted with high precision. In addition, the prediction models for SPAD value were developed using the vegetation indices NDVI (Normalized Difference Vegetation Index), GNDVI (Green NDVI), NIR/Red ratio, NIR/Green ratio, and Red/Green ratio. The SPAD values were predicted with relatively high precision (R² = 0.834) using the prediction model based on NIR/Red.
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Effects of Main Shaft Velocity on Turbidity and Quality of White Rice in a Rice Processing System
( Byeong-hyo Cho ),( Tae-hwan Kang ),( Jin-ho Won ),( Shin-hyeong Kang ),( Hee-sook Lee ),( Chung-su Han ) 한국농업기계학회 2017 바이오시스템공학 Vol.42 No.1
Purpose: The purpose of this study is to analyze turbidity and quality characteristics of white rice as a function of main shaft blast velocity and to verify the optimum processing conditions in the cutting type white rice processing system (CTWRPS). Methods: Sindongjin, one of the rice varieties, which used to be produced in Gimje-si, Jeollabuk-do, in 2015, was used as the experimental material. Turbidity and quality characteristics of white rice were measured at three different main shaft blast velocities: 25, 30, and 35 m/s. The amount of test material used for a single experiment was 20 kg, and after processing, whiteness was found to be 42.5±0.5, following which, turbidity and quality characteristics were measured. Results: Turbidity decreased with increase in the shaft blast velocity, and as a result, was lowest at 35 m/s of shaft blast velocity among all the other experiment velocities. The trend of cracked rice ratios was similar to the turbidity. Broken rice ratio turned out to be less than 2.0% in all the test conditions. In the first stage of processing, the processing pressure decreased as the main shaft blast velocity increased. Additionally, in the second stage of processing, the processing pressure was at its lowest value at the main shaft blast velocity of 35 m/s. Energy consumption, too, decreased as the main shaft blast velocity was increased. Conclusions: From the above results, it is concluded that the main shaft blast velocity of 35 m/s is best for reducing turbidity and producing high quality rice in a CTWRPS.
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조병효 ( Byeong-hyo Cho ),이성민 ( Seong Min Lee ),홍영기 ( Youngki Homg ),김경철 ( Kyoung-chul Kim ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.2
토마토는 경제적으로 중요한 과채류이며, 국내 토마토 생산량은 2021년 기준 약 37만 톤으로 전년대비 2.5만 톤 정도 증가하였다(KOSIS, 2022). 그러나, 최근에는 농업인구 감소 및 고령화, COVID-19 등 인력 부족으로 인하여 토마토 생산에 어려움을 겪고 있는 실정이며, 이러한 이유로 토마토의 재배부터 수확까지 자동화 전환에 대한 요구가 증가하고 있다. 이에 토마토 모니터링 및 수확 로봇 등 재배에서 수확 작업까지 로봇 기술을 적용하기 위한 연구가 수행되고 있으며, 이를 위해서는 우선적으로 작물의 품질 또는 성숙도 등을 모니터링할 수 있는 기술이 필요하다. 따라서 본 연구에서는 토마토의 성숙도를 비파괴적으로 예측하기 위해 초분광 영상과 기계학습 모델인 SVR (Support vector regression) 모델을 사용하였으며, 토마토의 성숙도를 정량적으로 분류하기 위한 요인으로는 경도를 사용하였다. 먼저, 경도와 밀접한 관계를 갖는 분광 영역을 조사하기 위해 상관분석을 수행하였으며, 그 결과 507-593 nm 사이의 분광 영역이 토마토의 경도와 높은 상관관계(R>0.8)를 갖는 것으로 나타났다. 앞의 결과를 바탕으로, 507-593 nm 사이의 분광 영역(30 밴드)을 입력 데이터로 하여 SVR 모델의 학습을 진행하였으며, 그 결과 SVR 모델의 최적 파라미터는 C의 경우 297, gamma와 epsilon은 각각 1.90 및 1이었다. 앞의 모델을 이용할 경우, 검증 데이터를 기준으로 0.84의 R2와 13.22 N의 RMSE로 비교적 높은 정확도에서 토마토 경도 예측이 가능하였으며, 이를 이용하여 토마토의 수확시기 예측이 가능할 것으로 판단된다. 향후에는 모델의 정확도 개선을 위해 추가적인 실험을 통해 샘플 수를 증가시키고, 실제 온실에 적용하기 위한 기초 실험을 진행할 계획이다.
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조병효 ( Byeong-hyo Cho ),이성민 ( Seong Min Lee ),홍영기 ( Youngki Homg ),김경철 ( Kyoung-chul Kim ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.2
토마토는 경제적으로 중요한 과채류이며, 국내 토마토 생산량은 2021년 기준 약 37만 톤으로 전년대비 2.5만 톤 정도 증가하였다(KOSIS, 2022). 그러나, 최근에는 농업인구 감소 및 고령화, COVID-19 등 인력 부족으로 인하여 토마토 생산에 어려움을 겪고 있는 실정이며, 이러한 이유로 토마토의 재배부터 수확까지 자동화 전환에 대한 요구가 증가하고 있다. 이에 토마토 모니터링 및 수확 로봇 등 재배에서 수확 작업까지 로봇 기술을 적용하기 위한 연구가 수행되고 있으며, 이를 위해서는 우선적으로 작물의 품질 또는 성숙도 등을 모니터링할 수 있는 기술이 필요하다. 따라서 본 연구에서는 토마토의 성숙도를 비파괴적으로 예측하기 위해 초분광 영상과 기계학습 모델인 SVR (Support vector regression) 모델을 사용하였으며, 토마토의 성숙도를 정량적으로 분류하기 위한 요인으로는 경도를 사용하였다. 먼저, 경도와 밀접한 관계를 갖는 분광 영역을 조사하기 위해 상관분석을 수행하였으며, 그 결과 507-593 nm 사이의 분광 영역이 토마토의 경도와 높은 상관관계(R>0.8)를 갖는 것으로 나타났다. 앞의 결과를 바탕으로, 507-593 nm 사이의 분광 영역(30 밴드)을 입력 데이터로 하여 SVR 모델의 학습을 진행하였으며, 그 결과 SVR 모델의 최적 파라미터는 C의 경우 297, gamma와 epsilon은 각각 1.90 및 1이었다. 앞의 모델을 이용할 경우, 검증 데이터를 기준으로 0.84의 R2와 13.22 N의 RMSE로 비교적 높은 정확도에서 토마토 경도 예측이 가능하였으며, 이를 이용하여 토마토의 수확시기 예측이 가능할 것으로 판단된다. 향후에는 모델의 정확도 개선을 위해 추가적인 실험을 통해 샘플 수를 증가시키고, 실제 온실에 적용하기 위한 기초 실험을 진행할 계획이다.
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