• Korean Journal of Food Science and Technology
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• v.21 no.5
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• pp.676-685
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• 1989

Optimal operating conditions of on-farm red pepper dryer were searched by using the simulation-optimization algorithm combining the drying and quality deterioration models of red pepper with Box's complex method. Determination of control variables such as air temperature, air recycle ratio and air flow rate was based on a criterion of minimizing energy consumption under the constrainst conditions that satisfied the specified color retention of carotenoids. As quality constraint was stricter, energy consumption increased and total drying time decreased with lower recycle ratio and higher air flow rate Product mixing during drying was found to be able to improve the energy efficiency and product quality. Currently used air flow rate was assessed to be increased for the optimal operation. Two stage drying at the fixed optimal air flow rate was proven to be useful means for further saying of energy consumption. In the optimal bistaged drying, the second stage began at about one third of the total drying time and low air temperature in the first stage Increased to a high value and air recycle ratio increased slightly in the second stage. Optimal control variable scheme could be explained by the dryer performance and the carotenoids destruction kinetics in red pepper drying.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.255-260
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• 2022

This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.149-160
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• 2022

In this study, the physical quality and microbial changes of ginseng sprout according to the pretreatment process and packaging container were evaluated to improve the storage properties of ginseng sprout produced in smart farm. Quality change during storage (10 days) according to pretreatment method (ascorbic acid, citric acid, peroxyacetic acid) and packaging container (expanded polystyrene (EP), polypropylene (PP), polyethylene (PE), polypropylene + polyethylene + cast polypropylene (PP+PE+CPP)) was evaluated in terms of texture, viable cell count, water content, and color. As a result of comparison according to the type of pretreatment, the citric acid treatment group showed the lowest texture change and the effect on inhibition of bacterial growth. On the other hand, citric acid, which was most effective among pretreatments, was treated in all samples and then stored in 4 types of containers. Specially, the ginseng sprout in PP packaging container was not observed significant softening or color changes after 10 days storage, and the lowest changes in viable cell number. Therefore, this study was shown that citric acid treatment and use of PP packaging container are effective in increasing the shelf life of ginseng sprout.

• Korean Journal of Veterinary Research
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• v.49 no.3
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• pp.257-263
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• 2009

Bovine mastitis is an important disease causing serious economic loss in dairy production and food poison in public health. Escherichia coli and Staphylococcus aureus are the major causative agents of bovine mastitis. These bacteria were found in milk and environmental condition such as feces, water, soil and so on. Bovine mastitis causative micro-organisms can survive in 1-2 weeks in feces and bed complexes. Low level of percentage of water content (PWC) of feces and bed complexes can reduce the spreading of bovine mastitis incidence from environmental contamination. In this study, we developed the fecal dehydrating system and determined the elimination rates of bovine mastitis causative agent from feces and bed complexes. To develop the fecal dehydrating system, the screw pressurized dehydrating system was used and the maximum rate of dehydrating was reached to 52% PWC using 90% PWC (wet base) of fecal and bed complexes. The elimination rates of the dehydrating system for E. coli and S. aureus were reached at 41.19 $\pm$ 7.84% to 62.55 $\pm$ 8.71% in various percentages of PWC of feces and bed complexes (80, 85 and 90%). These results suggested that the application of fecal dehydrating system would reduce the exposure of dairy cattle to bovine mastitis causing agents contaminated feces and bed complexes, and can be used for environmental bovine mastitis control avoiding misuse or abuse of chemical disinfectants and antibiotics in dairy farm.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.171-171
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• 2017

전산유체역학(CFD: Computational Fluid Dynamics)를 이용한 스마트팜 환경 내부의 정밀 제어 연구가 진행 중이다. 시계열 데이터의 난해한 동적 해석을 극복하기위해, 비선형 모델링 기법의 일종인 인공신경망을 이용하는 방안을 고려하였다. 선행 연구를 통하여 환경 데이터의 비선형 모델링을 위한 Tensorflow활용 방법이 하드웨어 가속 기능을 바탕으로 월등한 성능을 보임을 확인하였다. 그럼에도 오프라인 일괄(Offline batch)처리 방식의 한계가 있는 인공신경망 모델링 기법과 현장 보급이 불가능한 고성능 하드웨어 연산 장치에 대한 대안 마련이 필요하다고 판단되었다. CFD 해석을 위한 Solver로 SU2(http://su2.stanford.edu)를 이용하였다. 운영 체제 및 컴파일러는 1) Mac OS X Sierra 10.12.2 Apple LLVM version 8.0.0 (clang-800.0.38), 2) Windows 10 x64: Intel C++ Compiler version 16.0, update 2, 3) Linux (Ubuntu 16.04 x64): g++ 5.4.0, 4) Clustered Linux (Ubuntu 16.04 x32): MPICC 3.3.a2를 선정하였다. 4번째 개발환경인 병렬 시스템의 경우 하드웨어 가속는 OpenCL(https://www.khronos.org/opencl/) 엔진을 이용하고 저전력 ARM 프로세서의 일종인 옥타코어 Samsung Exynos5422 칩을 장착한 ODROID-XU4(Hardkernel, AnYang, Korea) SBC(Single Board Computer)를 32식 병렬 구성하였다. 분산 컴퓨팅을 위한 환경은 Gbit 로컬 네트워크 기반 NFS(Network File System)과 MPICH(http://www.mpich.org/)로 구성하였다. 공간 분해능을 계측 주기보다 작게 분할할 경우 발생하는 미지의 바운더리 정보를 정의하기 위하여 3차원 Kriging Spatial Interpolation Method를 실험적으로 적용하였다. 한편 병렬 시스템 구성이 불가능한 1,2,3번 환경의 경우 내부적으로 이미 존재하는 멀티코어를 활용하고자 OpenMP(http://www.openmp.org/) 라이브러리를 활용하였다. 64비트 병렬 8코어로 동작하는 1,2,3번 운영환경의 경우 32비트 병렬 128코어로 동작하는 환경에 비하여 근소하게 2배 내외로 연산 속도가 빨랐다. 실시간 CFD 수행을 위한 분산 컴퓨팅 기술이 프로세서의 속도 및 운영체제의 정보 분배 능력에 따라 결정된다고 판단할 수 있었다. 이를 검증하기 위하여 4번 개발환경에서 운영체제를 64비트로 개선하여 5번째 환경을 구성하여 검증하였다. 상반되는 결과로 64비트 72코어로 동작하는 분산 컴퓨팅 환경에서 단일 프로세서 기반 멀티 코어(1,2,3번) 환경보다 보다 2.5배 내외 연산속도 향상이 있었다. ARM 프로세서용 64비트 운영체제의 완성도가 낮은 시점에서 추후 성공적인 실시간 CFD 모델링을 위한 지속적인 검토가 필요하다.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.189-194
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• 2012

Measurement of compositions and somatic cells in raw milk by chemical methods usually requires a lot of time, skilled labor and expensive analytical equipments. Recently, near-infrared reflectance spectroscopy (NIRS), which is a rapid, cost-effective and non-destructive technique, has been extensively used for safety and quality evaluation in the field of dairy products. However, less study has been performed to evaluate the effect of transmitted light on milk quality during NIRS analysis. Therefore, the objective of this study was to analyze the changes in milk quality using transmitted light. Raw milk samples collected from dairy farm from Siga prefecture in Japan were analyzed for fat, protein, lactose, solids not fat, total solids, milk urea and citric acid using the Milko scan 4000. Somatic cells in raw milk samples were counted by the Fossomatic 5000. Transmittance spectra of 50 ml raw milk samples were obtained by the Lax-Cute lighter in the 400 nm or less, 689 nm, 773 nm, 900 nm and 979 nm. As a result, milk fat as well as somatic cell count was increased by 2.6% and 9.0%, respectively. The other compositions were, however, changed within the relative error of the measurement. Further studies are needed to apply raw milk quality evaluation using the UV band by accumulating more samples and more data.

• Horticultural Science & Technology
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• v.16 no.1
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• pp.15-17
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• 1998

In order to provide cool night to strawberry plant with cool air and water, an abandoned cool mine was utilized. It's effects on flower induction and fruit yield in 4 different cultivars were examined. After 70 days of transplanting, flowering frequency was below 65% and 100% in control and treatment of night cooling, respectively and regardless of cultivars. Number of flower buds and flower clusters were higher in treated plants compared with the control. Average time until flowering was much less in treated plants. In terms of yield weight and total yield, 'Suhong' was found to be the best cultivar, averaging 24.2g fruit. Cooling contributed to the 6-7 times of increase in total yield within the frame of harvesting times. The fruit were harvested at 80-97 days after transplanting.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.116-121
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• 2011

This study was conducted to develop a robust navigator which could be in positioning for precision farming through developing a plural GPS receiver with 4 sets of GPS antenna. In order to improve positioning accuracy by integrating GPS signals received simultaneously, the algorithm for processing plural GPS signal effectively was designed. Performance of the algorithm was tested using a simulation program and a fixed point on WGS 84 coordinates. Results of this study are aummarized as followings. 1. 4 sets of lower grade GPS receiver and signals were integrated by kalman filter algorithm and geometric algorithm to increase positioning accuracy of the data. 2. Prototype was composed of 4 sets of GPS receiver and INS components. All Star which manufactured by CMC, gyro compass made by KVH, ground speed sensor and integration S/W based on RTOS(Real Time Operating System)were used. 3. Integration algorithm was simulated by developed program which could generate random position error less then 10 m and tested with the prototype at a fixed position. 4. When navigation data was integrated by geometrical correction and kalman filter algorithm, estimated positioning erros were less then 0.6 m and 1.0 m respectively in simulation and fixed position tests.

• Journal of Biosystems Engineering
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• v.35 no.1
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• pp.10-14
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• 2010

Biodiesel of 20% (BD20) and 100% (BD100), alterative fuels for tractor, were tested for its power and competitiveness in the various farm operations including plowing and rotary tilling in the paddy fields. No troubles such as engine ignition or abrupt stopping were monitored during the works of plowing, rotary tilling and travelling on the road. According to the tractor PTO test in accordance with OECD tractor PTO test codes, no significant PTO output difference was found between the three fuels. However, fuel consumption rates were different between the biodiesels and diesel fuel in the paddy works, where as biodiesel percentage increased more fuels were spent than the diesel fuel. The reason for this phenomenon seems came from density difference of the three fuels. Maximum fuel consumption difference occurred between BD100 and diesel fuel was about 10% in the plowing. More energy was spent on the rotary tilling operations than the plowing, where 35~40 % more fuel needed on rotary tilling than plowing. Of the exhaust gases, more $CO_2$ was discharged from diesel fuel than biodiesels, but more NOx from biodiesels and CO was hard to determine which fuel produce more amount.

• Journal of Biosystems Engineering
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• v.34 no.6
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• pp.391-396
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• 2009

The percentage of those aged 60 and over is 43.5% among our country's 3,186 thousands farming population, so farm village is getting aging society rapidly. Moreover agricultural competitiveness has being weakened due to labor shortage by degradation in quality of labor configuration from elderly porson. For realisms easy workability, we developed a motor vehicle for agricultural activity. The vehicle has an automatic guidance system which could follows a track of magnetic tape on the floor for easy moving to given working position. We collected data from two guidance sensors, located on front and rear end of the vehicle and calculated displacement and angle deviation from the track. This traveling system was stably controlled with processing information deflection S, angle of deviation, D and angle velocity, Vt = $k_1D$ - $k_2S$ from two guidance sensors attached on front and rear of th motor vehicle. Also this system have been tested under various condition of $k_1$, $k_2$ for comparison on both stepped and turning routes. The results show that traveling performance is best at $k_1$=0.7, $k_2$=3.