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논문 : 정보처리 및 복합기술 ; 초분광 반사광 영상을 이용한 "후지" 사과의 멍 검출에 관한 연구
조병관 ( Byoung Kwan Cho ),백인석 ( In Suck Baek ),이남근 ( Nam Geun Lee ),모창연 ( Chang Yeun Mo ) 한국농업기계학회 2011 바이오시스템공학 Vol.36 No.6
Defects exist underneath the fruit skin are not easily discernable by using conventional color imaging technique in the visible wavelength ranges. Development of sensitive detection methods for the defects is necessary to ensure accurate quality sorting of fruits. Hyperspectral imaging techniques, which combine the features of image and spectroscopy to acquire spatial and spectral information simultaneously, have demonstrated good potentials for identifying and detecting anomalies on biological substances. In this study, a high spatial resolution hyperspectral reflectance technique was presented as a tool for detecting bruises on apple. The two-band ratio (494 nm / 952 nm) and simple threshold methods were applied to investigate the feasibility of discriminating the bruises from sound tissue of apple. The pixel wise accuracy of the discrimination was 74%. The resultant images processed with selected wavebands and morphologic algorithm distinctively showed the early stages of bruises on apple which were not discernable by naked eyes as well as a conventional color camera. Results demonstrated good potential of the hyperspectral reflectance imaging for detection of bruises on apple.
초분광 반사광 영상을 이용한 방울토마토 내부품질 인자 예측
김대용 ( Dae Yong Kim ),조병관 ( Byoung Kwan Cho ),김영식 ( Young Sik Kim ) 한국산업식품공학회 2011 산업 식품공학 Vol.15 No.4
Hyperspectral reflectance imaging technology was used to predict internal quality of cherry tomatoes with the spectral range of 400-1000 nm. Partial least square (PLS) regression method was used to predict firmness, sugar content, and acid content. The PLS models were developed with several preprocessing methods, such as normalization, standard normal variate (SNV), multiplicative scatter correction (MSC), and derivative of Savitzky Golay. The performance of the prediction models were investigated to find the best combination of the preprocessing and PLS models. The coefficients of determination ( ) and standard errors of prediction (SEP) for the prediction of firmness, sugar content, and acid content of cherry tomatoes from green to red ripening stages were 0.876 and 1.875 kgf with mean of normalization, 0.823 and 0.388oBx with maximum of normalization, and 0.620 and 0.208% with maximum of normalization, respectively.
이훈수,정창호,김기복,조병관,Lee, Hoon-Soo,Chung, Chang-Ho,Kim, Ki-Bok,Cho, Byoung-Kwan 한국축산식품학회 2010 한국축산식품학회지 Vol.30 No.2
The purpose of this study was to evaluate the freshness of chicken meat during 19 d of storage at $4^{\circ}C$ using a portable electronic nose. The portable system consisted of six different metal oxide sensors and a moisture sensor. Determination of volatile compounds with gas chromatography-mass spectrometry, total bacterial count (TBC), and 2-thiobarbituric acid reactive substances (TBARS) monitored the quality change of the samples. These results were compared with the results measured by the electronic nose system. TBC and TBARS measurements could be separated into five groups and seven groups, respectively, among ten groups. According to principal component analysis and linear discriminant analysis with the signals of the portable electronic nose, the sample groups could be clearly separated into eight groups and nine groups, respectively, among ten groups. The portable electronic nose demonstrated potential for evaluating freshness of stored chicken.
Review: Application of Artificial Intelligence in Phenomics
납뷔래쇼나 ( Shona Nabwire ),조병관 ( Byoung-kwan Cho ) 한국농업기계학회 2021 한국농업기계학회 학술발표논문집 Vol.26 No.1
Plant phenomics has been rapidly advancing over the past few years. This is attributed to the increased innovation and availability of new technologies to enable high-throughput phenotyping of complex plant traits. The application of artificial intelligence in various domains of science has grown exponentially in recent years. Traditionally-used techniques for non-destructive plant phenotyping are now integrating artificial intelligence methods into their data management pipelines. This is gradually improving the efficiency of data analysis and has fostered further research into the development and utilization of these methods. Large volumes of plant data are now being collected in real-time at different research facilities depending on the desired research goals. The integration of a range of artificial intelligence approaches like computer vision, machine learning and deep learning at various stages in the entire phenotypic data management pipeline has become increasingly important to seamlessly consolidate plant data. This review provides an overview of current phenotyping technologies and the ongoing integration of artificial intelligence in plant phenotyping.
육류 신선도 판별을 위한 휴대용 전자코 시스템 설계 및 성능 평가 Ⅱ
김재곤(Jae-Gone Kim),조병관(Byoung-Kwan Cho) 충남대학교 농업과학연구소 2011 농업과학연구 Vol.38 No.4
The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at 4℃ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination (Rp<SUP>2</SUP>) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.
논문 : 정보처리 및 복합기술 ; IT융합 차세대 농기계 수출전략형 핵심기술 우선순위 선정에 관한 연구
장동일 ( Dong Il Chang ),조병관 ( Byoung Kwan Cho ),이훈수 ( Hoon Soo Lee ),정선옥 ( Sun Ok Chung ),박승제 ( Seung Jae Park ),김철수 ( Chul Soo Kim ),이영희 ( Young Hee Lee ) 한국농업기계학회 2011 바이오시스템공학 Vol.36 No.6
The objective of this study was to develop the export strategic core technologies for IT fusion next generation agricultural machines by the analysis of comprehensive and cooperative systems of industries, universities, and institutes. In order to achieve the objective of this study, an expert panel was formed and operated. The first survey was conducted by the Delphi method. For this the export strategic core technologies were surveyed and analyzed using the questionnaire. Based on the results of the first survey, the second survey was conducted. The questionnaire used for the second survey was designed by results of the first survey. The results of the second survey was analyzed by AHP method. The third survey was conducted based on the second one, and the final results were analyzed and the export strategic core technologies were developed through the expert meeting. The study results showed six export strategic core technologies as the followings: 1) environment-friendly engine technology for high performance 2) high performance/high efficiency power transmission system technology 3) development of measurement system technology for safety of agricultural products 4) field application of sensor networks 5) large size combine development technology for high performance 6) quality evaluation technology for agricultural products.
육류 신선도 판별을 위한 휴대용 전자코 시스템 설계 및 성능 평가
김재곤(Jae-Gone Kim),조병관(Byoung-Kwan Cho) 충남대학교 농업과학연구소 2011 농업과학연구 Vol.38 No.3
The aim of this study was to develop a portable electronic nose system for freshness measurement of meats, which could be an alterative of subjective measurements of human nose and time-consuming measurements of conventional gas chromatograph methods. The portable electronic system was o optimized by comparing the measurement sensitivity and hardware efficiency, such as power consumption and dimension reduction throughout two stages of the prototypes. The electronic nose systems were constructed using an array of four different metal oxide semiconductor sensors. Two different configurations of sensor array with dimension were designed and compared the performance respectively. The final prototype of the system showed much improved performance on saving power consumption and dimension reduction without decrease of measurement sensitivity of pork freshness. The results show the potential of constructing a portable electronic system for the measurement of meat quality with high sensitivity and energy efficiency.
광 반사방식을 이용한 감염 씨감자 비파괴 선별 기술 개발
김대용(Dae-Yong Kim),조병관(Byoung-Kwan Cho),이윤수(Youn-Su Lee) 충남대학교 농업과학연구소 2012 농업과학연구 Vol.39 No.1
Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and diseaseinfected seed potatoes with the spectral range from 400 to 1100 ㎚. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and diseaseinfected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis / NIR reflectance method has good potential for non-destructive sorting for disease- infected seed potatoes.