• Journal of Biosystems Engineering
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• 제34권2호
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• pp.95-105
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• 2009

A method was proposed which employed control of the drop location of fertilizer particles on a spinner disc to optimize the spread pattern uniformity. The system contained an optical sensor as a feedback mechanism, which measured discharge velocity and location, as well as particle diameters to predict a spread pattern of a single disc. Simulations showed that the feed gate adaptation algorithm produced high quality patterns for any given application rate in the dual disc spreader. The performance of the feed gate control method was assessed using data collected from a Sulky spinner disc spreader. The results showed that it was always possible to find a spread pattern with an acceptable CV lower than 15%, even though the spread pattern was obtained from a rudimentary flat disc with straight radial vanes. A mathematical optimization method was used to find the initial parameter settings for a specially designed experimental spreading arrangement, which included the feed gate control system, for a given flow rate and swath width. Several experiments were carried out to investigate the relationship between the gate opening and flow rate, disc speed and particle velocity, as well as disc speed and predicted landing location of fertilizer particles. All relationships found were highly linear ($r^2$ > 0.96), which showed that the time-of-flight sensor was well suited as a feedback sensor in the rate and uniformity controlled spreading system.

• Journal of Applied Biological Chemistry
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• 제59권2호
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• pp.165-169
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• 2016

The quantitative analytical method for the bioactive substance, 3-cyano-4-methoxy-N-methyl-2-pyridone (ricinine) and an index compound, ricinoleic acid in castor plant (Ricinus communis) extract or oil was developed. For the determination of a pyridone alkaloid compound, ricinine, successive cartridge cleanup method combined with ultra-performance liquid chromatography was set up with $ENVI-Carb^{TM}$ (0.5 g) and $C_{18}$ SPE cartridges. Accuracy and precision were evaluated through fortification studies of one biopesticide (PE) at 10 and $100mg\;kg^{-1}$. Mean recoveries of ricinine were 98.7 and 96.0 % associated with less than 10 % RSD, respectively. For the determination of ricinoleic acid in castor extract and oil, saponification and methylation were optimized using gas chromatography-time of flight mass spectrometry. Recovery was more than 84.8 % associated with 6.2 % RSD after derivatization procedure. Both methodologies developed were applied to analyze real samples including three castor oil products and six commercially available biopesticides containing R. communis, collected at Korean market. The contents of ricinine and ricinoleic acid in most commercial biopesticides were less than the oil or extract contents indicated by label.

• 지구물리와물리탐사
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• 제21권4호
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• pp.244-254
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• 2018

우리나라 농업부문에 최초로 적용된 물리탐사 기술은 전기비저항 수직탐사로, 1970년대 농업용 지하수 탐지 목적으로 적용되기 시작하였다. 농업활동이 다변화된 1990년대 이후에는 기존의 전기비저항 탐사 이외에 유도 전자기 탐사, 자연전위 탐사 등을 이용하여 대규모 간척지 염분 집적 등 토양 특성 파악, 농업현장을 포함한 지하수 공급의 최말단부인 해안지역 소유역의 해수침투 범위 탐지, 저수지 및 방조제 안전진단을 위한 물리탐사, 과잉양수에 의한 지반침하 탐지, 쓰레기 매립장 또는 가축 매몰지로부터 발생되는 침출수 누출 범위 추적 등 다양한 분야로 확대되어 활용되고 있다. 본 원고에서는 이러한 농업부문에서의 물리탐사 기술 적용 사례들을 소개하고, 이를 기반으로 미래 농업에서 추구하는 정밀농업 현장에 필요한 물리탐사 기술의 발전 방안을 제시하였다.

• 대한원격탐사학회지
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• 제34권6_3호
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• pp.1311-1317
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• 2018

위성개발의 궁극적인 목적은 위성으로부터 획득되는 정보의 활용에 있다. 따라서 국가 차원의 위성개발 프로그램은 하드웨어 개발뿐만 아니라 정보 활용을 위한 인프라 구축 및 활용기술 개발도 포함하여야 한다. 지금까지 우리나라는 다양한 위성을 개발하여 기상 및 해양 감시를 비롯하여 각종 재해재난 등에 있어 매우 유용하게 활용해 왔다. 특히 다목적실용위성 영상은 높은 공간해상도를 바탕으로 농업, 산림분야를 비롯하여 해양 분야까지 폭 넓게 활용되어 왔으며, 최근에는 정밀 지도제작 및 변화탐지 등과 관련된 연구에 많이 이용되고 있다. 본 특별호는 최근 다목적실용위성 광학 및 레이더 영상을 활용하여 수행된 다양한 연구사례에 대해서 소개함과 동시에 관련 위성영상 활용기술을 공공부문으로 전파시키는데 목적이 있다.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

• Journal of Forest and Environmental Science
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• 제39권3호
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• pp.180-194
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• 2023

This study characterize, classify and evaluates the function of topography on spatial variability of some selected soil properties to assist in designing land management that support uniform agricultural production. The study site, an agricultural land, was part of the derived savanna zone in southwest Nigeria. Four soil profile pits each were established along two delineated toposequence and described following the FAO/UNESCO guidelines. Samples were collected from the identified genetic horizons. Properties of four soil series developed on different positions of the two delineated Toposequence viz upper, middle, lower slopes and valley bottom positions respectively were studied. The soil samples were analysed for selected physical and chemical properties and data generated were subjected to descriptive and inferential statistics. The results showed that soil colour, depth and texture varied in response to changes in slope position and drainage condition. The sand content ranged from 61 to 90% while the bulk density ranged between 1.06 g cm^-3 to 1.68 g cm^-3. The soils were neutral to very strongly acid with low total exchangeable bases. Available phosphorus value were low while the extractable micronutrient concentration varied from low to medium. Soils of Asejire and Iwo series mapped in the study area were classified as Typic isohyperthermic paleustult, Apomu series as Plinthic isohyperthermic paleustult and Jago series as Aquic psamment (USDA Soil Taxonomy). These soils were correlated as Lixisol, Plinthic Lixisol and Fluvisol (World Reference Based), respectively. Major agronomic constraints of the soils associations mapped in the study area were nutrient availability, nutrient retention, slope, drainage, texture, high bulk density and shallow depth. The study concluded that the soils were not homogenous, shows moderate spatial variation across the slope, had varying potentials for sustainable agricultural practices, and thus, the agronomic constraints should be carefully addressed and managed for precision agriculture.

• 한국축산식품학회지
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• 제43권6호
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• pp.1055-1066
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• 2023

The cultured meat industry is continuously evolving due to the collective efforts of cultured meat companies and academics worldwide. Though still technologically limited, recent reports of regulatory approvals for cultured meat companies have initiated the standards-based approach towards cultured meat production. Incidents of deception in the meat industry call for fool-proof authentication methods to ensure consumer safety, product quality, and traceability. The cultured meat industry is not exempt from the threats of food fraud. Meat authentication techniques based on DNA, protein, and metabolite fingerprints of animal meat species needs to be evaluated for their applicability to cultured meat. Technique-based categorization of cultured meat products could ease the identification of appropriate authentication methods. The combination of methods with high sensitivity and specificity is key to increasing the accuracy and precision of meat authentication. The identification of markers (both physical and biochemical) to differentiate conventional meat from cultured meat needs to be established to ensure overall product traceability. The current review briefly discusses some areas in the cultured meat industry that are vulnerable to food fraud. Specifically, it targets the current meat and meat product authentication tests to emphasize the need for ensuring the traceability of cultured meat.

• Animal Bioscience
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• 제37권4_spc호
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• pp.786-793
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• 2024

Latin America is a culturally, geographically, politically, and economically diverse region. Agriculture in Latin America is marked by a remarkable diversity of production systems, reflecting various agroecological zones, farm sizes, and technological levels. In the last decade, the swine industry increased by 30.6%, emerging as a great contributor to food security and economic development in Latin America. Brazil and Mexico dominate the pig production landscape, together accounting for 70% of sow inventory in the region. The swine industry in Latin America is predominantly comprised of small and medium-sized farms, however, in the past 30 years, the number of pig producers in Brazil dropped by 78%, whereas pork production increased by 326%. Similar to the global pork industry, the growing demand for pork, driven by population growth and changing dietary habits, presents an opportunity for the industry with an expected growth of 16% over the next decade. The export prospects are promising, however subject to potential disruptions from global market conditions and shifts in trade policies. Among the challenges faced by the swine industry, disease outbreaks, particularly African Swine Fever (ASF), present significant threats, necessitating enhanced biosecurity and surveillance systems. In 2023, ASF was reported to the Dominican Republic and Haiti, Porcine Reproductive and Respiratory Syndrome (PRRS) in Mexico, Costa Rica, the Dominican Republic, Colombia, and Venezuela, and Porcine Epidemic Diarrhea (PED) in Mexico, Peru, the Dominican Republic, Colombia, and Ecuador. Additionally, feed costs, supply chain disruptions, and energy expenses have affected mainly the smaller and less efficient producers. The swine industry is also transitioning towards more sustainable and environmentally friendly practices, including efficient feed usage, and precision farming. Ensuring long-term success in the swine industry in Latin America requires a holistic approach that prioritizes sustainability, animal welfare, and consumer preferences, ultimately positioning the industry to thrive in the evolving global market.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.36-43
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• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• 한국전자통신학회논문지
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• 제19권4호
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• pp.771-780
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• 2024

본 연구에서는 딸기 농장을 대상으로 YOLOv5 아키텍처를 기반으로 한 컴퓨터 비전 모델과 Isolation Forest Classifier를 적용하여 병충해를 실시간으로 감지 및 예측하는 시스템을 개발하였다. 모델 성능 평가 결과, YOLOv5 모델은 평균 정밀도(mAP 0.5) 78.7%, 정확도 92.8%, 재현율 90.0%, F1 점수 76%로 높은 예측 성능을 나타냈다. 본 시스템은 딸기 농장뿐만 아니라 다른 작물과 다양한 환경에도 적용할 수 있도록 설계되었다. 토마토 농장에서 수집된 데이터를 기반으로 새로운 AI 모델을 학습한 결과, 주요 병충해인 역병과 황화병에 대한 예측 정확도가 85% 이상으로 나타났으며, 기존 모델보다 예측 정확도가 10% 이상 향상되었다.