• 항공우주시스템공학회지
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• 제4권1호
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• pp.15-18
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• 2010

In the hot summer manual spray work for plants would be the hardest one among the agricultural field works. Besides the physical load the possible toxication would strongly ask a way to do the job on behalf of human. Although an aircraft with sprayer could be a good candidate, the manned airplanes do not play proper roles in our country because of field geometry. Today, unmanned helicopter as expensive as 200,000 dollars can do the job with high risk of control. Therefore safe and cheap air vehicle with sprayer, if developed, could be a great help to agriculture.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.444-450
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• 2011

Environmental change, labor shortage, and international trade politics make agricultural automation ever more important. The automation demands the highest technology due to the nature of agriculture. In this paper, autonomous pesticide spray robot system has been developed for rose farming in the glass house. We developed drive platform, navigation/localization system, atomization spray system, autonomous, remote, and manual operation system, and monitoring system. The robot will be a great contribution to automation of hazardous labor-demanding chore of pesticide control in glass houses.

• Journal of Biosystems Engineering
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• 제41권4호
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• pp.294-303
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• 2016

Purpose: This study aimed to evaluate the profitability of four selective mechanization systems in rice cultivation. Methods: Field experiments were conducted in the farmers' field during the wet season (June to November) of 2015 in Bangladesh. Mechanization systems were applied to evaluate four different selective levels (treatment) in eleven consequent operations. Seedlings were raised in a traditional seedbed and trays for manual and mechanical transplanting, respectively. Land preparation, irrigation, fertilizer, pesticide, carrying, and threshing and cleaning operations were performed using the same method in all the experimental plots. The mechanical options in the transplanting, weeding, and harvesting operations were changed. The mechanization systems were $S_1$ = hand transplanting + hand weeding + harvesting by sickle, $S_2$ = mechanical transplanting + Bangladesh Rice Research Institute (BRRI) weeder + reaper, $S_3$ = mechanical transplanting + BRRI power weeder + reaper, and $S_4$ = mechanical transplanting + herbicide + reaper. This experiment was performed in a randomized complete block design with four replications. Power tiller, rice transplanter, BRRI weeder, BRRI power weeder, self-propelled reaper, BRRI open drum thresher, and BRRI winnower were used in the respective operations. Accordingly, the techno-economic performances of the different technologies were calculated and compared with those of the traditional system. Results: The mechanically transplanted plot produced 6-10% more yield than the hand transplanted plot because of the use of tender-aged seedlings. Mechanical transplanting reduced 61% labor and 18% cost compared to manual transplanting. The BRRI weeder, BRRI power weeder, and herbicide application reduced 74, 91, and 98% labor, respectively. The latter also saved 72, 63, and 82% cost, respectively, compared to hand weeding. Herbicide application reduced the substantial amount of labor and cost in the weeding operation. Mechanical harvesting also saved 96% labor and 72% cost compared to the traditional method of harvesting using sickle. Selective mechanization saved 15-17% input cost compared to the traditional method of rice cultivation. Conclusions: Mechanical transplanting with the safe use of herbicide and harvesting by reaper is the most cost- and labor-saving operation. The method might be the recommended set of selective mechanization for enhancing productivity.

• 농약과학회지
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• 제16권3호
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• pp.230-235
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• 2012

본 실험은 포장과 살포기의 차이가 고추 열매 중 농약 잔류량에 미치는 영향을 구명하고자 하였다. 위치가 다른 세 농가 포장에서 비슷한 시기에 정식한 고추를 대상으로 동일한 분무기와 노즐로 약제 처리 후 1일차의 농약 잔류량은 통계처리로 확인하여 차이가 없었다. 시료 채취시 고추나무 외부의 고추 중 잔류량은 내부의 고추 보다 2배 이상 많아 시료 채취의 위치가 고추 중 잔류량 변이의 요인이 되었다. 배부식 동력분무기와 압축식 인력분무기 사용에 따른 농약잔류량 차이는 동력분무기가 인력분무기를 사용할 때 보다 1.7배 높은 잔류농도를 보였는데 이는 약제 살포시 인력분무기의 상용압력보다 2배 정도 높은 동력분무기 압력과 노즐의 영향으로 판단되었다.

• 식물병연구
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• 제10권1호
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• pp.8-12
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• 2004

2003년 7월, 경상북도 봉화지역의 인삼포장에서 인삼의 줄기가 쓰러지고 뿌리썩음증상을 보이는 인삼을 관찰하였다 병든 뿌리로부터 분리된 병원세균을 접종한 결과, 인삼의 잎은 황화되거나 검은색으로 변하여 시들었고, 줄기는 속이 텅비어 있었다. 뿌리는 접종부위가 썩으면서 주름이 생기고 차츰 검은색으로 변화였다. 이 병원세균은 인삼의 모든 부위에 대해 병원성이 인정되었고 이 병원세균의 형태 및 생리적 특성을 Bergey' manual에 기록된 세균의 특성과 비교한 결과, Serratia liquefaciens로 동정되었다. 이 세균은 아직 인삼의 병원세균으로 기록되어 있지 않기에 인삼뿌리썩음병으로 이 병원세균도 추가할 것을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.421-441
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• 2021

Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1156-1170
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• 2019

In recent years, the problem of data drifted of the smart grid due to manual operation has been widely studied by researchers in the related domain areas. It has become an important research topic to effectively and reliably find the reasonable data needed in the Supervisory Control and Data Acquisition (SCADA) system has become an important research topic. This paper analyzes the data composition of the smart grid, and explains the power model in two smart grid applications, followed by an analysis on the application of each parameter in density-based spatial clustering of applications with noise (DBSCAN) algorithm. Then a comparison is carried out for the processing effects of the boxplot method, probability weight analysis method and DBSCAN clustering algorithm on the big data driven power grid. According to the comparison results, the performance of the DBSCAN algorithm outperforming other methods in processing effect. The experimental verification shows that the DBSCAN clustering algorithm can effectively screen the power grid data, thereby significantly improving the accuracy and reliability of the calculation result of the main grid's theoretical line loss.

• 농업과학연구
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• 제49권3호
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• pp.679-690
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• 2022

As the supply and demand of pork has become a significant concern in Korea, controlling it has become a critical challenge for the industry. However, compared to the demand for pork, which has relatively stable consumption, it is not easy to maintain a stable supply. As the preparation of measures for a supply-demand crisis response and supply control in the pig industry has emerged as an important task, it has become necessary to establish a stable supply model and create an appropriate manual. In this study, a pork supply prediction model is constructed using reported data from the pig traceability system. Based on the derived results, a method for determining the supply-demand crisis stage using a statistical approach was proposed. From the results of the analysis, working days, African swine fever, heat wave, and Covid-19 were shown to affect the number of pigs graded in the market. A test of the performance of the model showed that both in-sample error rate and out-sample error rate were between 0.3 - 7.6%, indicating a high level of predictive power. Applying the forecast, the distribution of the confidence interval of the predicted value was established, and the supply crisis stage was identified, evaluating supply-demand conditions.

• 한국토양비료학회지
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• 제43권6호
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• pp.812-822
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• 2010

1. 우리나라 전국을 45개 지역으로 구분하여 최근 30년간의 기상자료 분석에 의한 5월~6월의 일평균 PET는 2.99 mm $day^{-1}$ 이었다. 2. 토성별 유효토양수분보유량 (AWS)은 사양토 16.0%~미사질양토 24.7% 범위이었다. 3. 봄배추의 45개 지역별, 3개 토성 및 5개 순별, 총 675경우의 재배여건에 적합한 물 절약형 적정 관개간격 및 1회 관개량을 산정하였다.

• 농업과학연구
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• 제49권3호
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.