농업용 트랙터 PTO 기어의 유한요소해석

소진환,남요상,최창현,정연준 한국정밀농업학회 2017 정밀농업기술 Vol.4 No.1

<P> A agricultural tractor PTO(Power Take-Off) gear optimization was conducted. The PTO 1st and 3rd gears were analyzed using ANSYS. The SCM 420H was used as the material of the shaft and the gear. The contact and boundary condition were input to the model of PTO gear. In this study, PTO 1st and 3rd gears of agricultural tractor were. The simulation results show that the deformation amounts of the maximum power points of PTO 1st and 3rd gears were 0.16598, and 0.07517 mm, and the stresses were 3171.1, and 3114.6 N/mm<SUP>2</SUP>, respectively. The maximum torque points were 0.22982, and 0104080 mm, and the stresses were 4390.8, and 4312.6 N/mm<SUP>2</SUP>. The deformation amount and the stress of the PTO 1st and 3rd gears of the maximum torque point were increased by about 38%. During farm operation, gear breakage may occur more than the maximum power point at the maximum torque point of the engine. </P>

Development of a sandy soil water content monitoring system for greenhouses using Internet of Things

Mohammod Ali,Md Razob Ali,Md Ashrafuzzaman Gulandaz,Md Asrakul Haque,Md Sazzadul Kabir,Sun-Ok Chung 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3

Precision water management is crucial for greenhouse agriculture to maximize crop yields in sandy soil. Due to the low water holding capacity, it is necessary to monitor the water movement in different depths of sandy soil to ensure effective irrigation. Therefore, this study aimed to develop a data acquisition (DAQ) system for sandy soil water content monitoring in an experimental soil bin inside a greenhouse, utilizing the capabilities of the Internet of Things (IoT). A drip irrigation system was implemented, arranged in four pipelines, spaced 60 cm apart, with drippers placed at 30 cm intervals along the pipeline. The overall system was installed in a sandy soil testing bin. A DAQ system was comprised of three basic units: sensor interfacing and circuit board, programming and sensor data acquisition, and data storage and monitoring. A microprocessor was used by interfacing a set of soil water content sensors, ambient temperature, and humidity sensors. The water content sensors were placed in the soil at different depths of 10, 20, 30, 40, and 50 cm, respectively. A microcontroller was used to collect and send the sensor data to monitor and store in memory. During the test, the maximum and minimum average of soil water content, ambient temperature, and humidity values were observed at 33.91±2.5 to 26.95±1.3%, 21.39±2.1 to 42.84±1.7°C, and 48.73±2.3 to 99.90±0.3%, respectively. The water content percentages were varied at different depths of sandy soil due to low water holding capacity. The developed automatic DAQ system would help with remote monitoring and control of greenhouse irrigation, considering the different crop characteristics and environmental conditions.

Technology development and industrialization trends of circulating nutrient solution supply systems: a review

Hyo-Jeong Kwon,Md Razob Ali,Ka Young Lee,Md Nasim Reza,Mohammod Ali,Md. Shaha Nur Kabir,Sun-Ok Chung,Kanghee Jeong 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3

Hydroponics, a soil-free plant cultivation technique, delivers nutrients directly to roots through a nutrient-rich solution. This method offers advantages over traditional soil-based approaches and has gained attention for its potential to revolutionize controlled agriculture. The review aimed to offer a summary of technological advancements and industrialization patterns in systems supplying circulating nutrient solutions. An intelligent nutrient management system enhances plant growth and productivity. The utilization of a circulating hydroponic cultivation setup can reduce environmental pollution and lower production expenses. As a result, circulating nutrient solution management systems are gaining global popularity, such as in the Netherlands, circular hydroponic cultivation has been advanced to over 95%. A limitation of circulation-type nutrient solution cultivation is the potential transmission and rapid formulation of pathogens during the recycling of discharged nutrient solutions. Addressing this concern, filtration and sterilization processes can offer viable solutions. To accelerate hydroponic farming, an integrated approach could be pursued, strengthen nutrient circulation management technology. This approach could aid in the implementation of such systems in countries like the Republic of Korea, where adoption of circulating hydroponic systems remains under 5%. The trend of technological advancement and industrial growth has been conducted through patent analysis and resources that have subsequently lead the way for the advancement of extensive hydroponic farming establishments. The cyclic hydroponic cultivation in the Republic of Korea was introduced in 2010, and based on the patent information, this endeavor gained momentum from 2020 onward. Furthermore, the analysis underscores the considerable potential of circulating nutrient solution supply systems as viable approaches for promoting sustainable and efficient food production. As a result, forthcoming research and innovation need to be tailored to the local context and prioritize user-centered methodologies, ultimately facilitating the integration and establishment of hydroponic systems in the Republic of Korea.

Survey and analysis of national standardization trends for smart farm ICT equipment

Chi-Ju Woo,Ho-Sung An,Ka Young Lee,Samsuzzaman,Md. Shaha Nur Kabir,Sun-Ok Chung,Soon Jung Hong,Jong Kyu Ha 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3

The rapid advancement of information and communication technology (ICT) has significantly transformed the agricultural sector, giving rise to the concept of smart farming. Smart farming involves the integration of various ICT equipment and technologies to enhance agricultural practices, improve productivity, and ensure sustainable resource utilization. As smart farming gains momentum, the need for standardized practices and equipment becomes crucial to ensure interoperability, reliability, and widespread adoption. This paper presents a comprehensive survey and analysis of national standardization trends for smart farm ICT equipment in smart farming. It introduces the standardization trends, smart farm ICT equipment national standard diffusion support project, and evaluation of testing ICT equipments. Additionally, it highlights the necessity and consequences of ensuring interoperability for ICT equipment in smart farming. Furthermore, the paper explores the challenges and opportunities associated with smart farm ICT equipment standardization. Challenges include reconciling diverse technical requirements, addressing security and privacy concerns, and maintaining adaptability to evolving technological landscapes. On the other hand, standardization offers the opportunity to accelerate innovation, enable market growth, and establish a foundation for sustainable agricultural practices.

CAM-based orchard path detection for developing an unmanned sprayer

조수현,Seung-Woo Kang,Baek-Gyeom Sung,이대현 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3

This study was conducted to apply a deep learning model to identify and visualise path areas in an orchard. Data was collected by attaching an image capture device to the front of a sprayer and driving it through an orchard. The collected data was classified into four classes: ground, trees, sky and obstacles for pre-processing for training. Sliding window techniques were used on the image dataset for model training and performance. The image was sampled using a sliding window method with 224x224 pixels and divided into train, validation, and test sets. A modified VGG16 algorithm was implemented and used to train the preprocessed image dataset. The performance results of this model showed an accuracy of up to approximately 99% on both the training and validation sets, and after building a confusion matrix using the test set, the classification performance was evaluated and showed an F1 score of 0.96. To visualise the results of this trained learning model, class activation maps were used to detect the paths in the orchard. The implementation of this method resulted in an average processing time of about 0.94 seconds per frame on the orchard footage, which could potentially be beneficial in real-time decision making scenarios in fruit farming where rapid response is important.

μPED based electrode modified with nanocomposite for the detection of proline: An abiotic stress biomarker in plant

Mallesh Santhosh,Tusan Park 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3

Plants when exposed to stressful conditions, accumulates array of metabolites. Among them proline plays significant and beneficial role as osmolyte, metal chelator and as anti-oxidative defense and regulator molecule. Thus the proline content is one of the potent bio-marker for the early detection of abiotic stress in plant. In this work a microfluidic paper-based electrochemical device (μPED) modified with copper oxide nanoparticles (CuO) decorated reduced graphene oxide (rGO) nanocomposite is utilized to develop disposable system for the detection of proline. Wax and screen printings were utilized to create microfluidic chambers and electrode pattern on paper device, respectively. Portable potentiostat was used for measuring the current in response from the addition of proline. The proposed sensor exhibits excellent electrochemical performance with broad linear responses over a proline concentration ranging from 0.1 mM to 7.5 mM (R2 =0.99) and showed lower detection limit of 0.05 mM at 0.4 V vs. pseudo Ag/AgCl. Excellent electrochemical performance may be attributed to presence of electroactive rGO and catalytic activity towards proline is due to the coordination between proline and copper (II) oxide nanoparticles. These results demonstrate that the proposed paper-based electrochemical sensor can be utilized in disposable and portable way to detect proline content in the abiotic-stressed plants and has potential to be applied in on-site application.

Transforming Philippine agriculture through Agriculture 4.0

Julie Anne G. Cordero,Tusan Park 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.4

Agriculture 4.0 has paved the way for Philippine agriculture through the One Department of Agriculture (One DA) Agenda. The government is slowly paving its way to Agriculture 4.0 through the support of collaborating countries and agencies. The increasing digital integration and advanced technologies emphasizing precision farming have contributed to the industry's growth. The agriculture, forestry, and fishing sectors contributed 8.9% to the Philippines' GDP (PSA, 2022). Agriculture 4.0 also contributed to the increase in farm mechanization level of the country to 2.679 horsepower per hectare (hp/ha) from 2.31 hp/ha in 2013 (Bagoso, 2023). The government has recently developed a more straightforward approach to farming problems, such as monitoring farm activity through drones, remote sensing, and satellite technologies. The farmers can now access real-time updates on infrastructure and machinery projects from proposal to turning-over through ABEMIS. Using remote sensing and data analytics has become a game changer in agriculture, especially in weather prediction, forecast of future yields, disaster assessment and access to insurance schemes are available with PRiSM and RIICE projects. Drone use in different applications was strengthened through policies set by the DA. The continuous research for development and technology transfer with local government units through province-led agriculture and fisheries extension systems helps the government promote digital transformation in agriculture. Indeed, Agriculture 4.0 is the future of global agriculture and the engine of agriculture modernization in the Philippines.

Optimizing postharvest management of bananas in Uganda: a resilience and engineering-based approach

Geoffrey Ssekyanzi,Tusan Park 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.4

This study delves into the intricacies of postharvest management in banana production in Uganda, aiming to uncover insights that can enhance resilience and capitalize on opportunities for the sustained growth of banana cultivation. The examination spans the entire postharvest process, encompassing harvesting, handling, transportation, and storage up to the market stage. By identifying the primary causes of postharvest losses and understanding the associated challenges, this research outlines best practices to pave the way for a more robust banana production system, benefiting farmers and contributing to broader agricultural sustainability goals. The investigation explores the core issues affecting millions of lives and endeavors to catalyze transformative change by adapting to challenges and leveraging innovative engineering opportunities. The overarching objective is to ensure food security and elevate the economic well-being of smallholder farmers in Uganda. Recommendations emanating from this research are directed at stakeholders, urging them to scrutinize and reevaluate policies and regulations of banana postharvest management. The intention is to foster an enabling environment conducive to innovation, sustainability, and equitable development in the banana production sector.

Analysis of 38 kW class agricultural tractor engine load rate according to agricultural operation

Cheol Woo Yang,Hyeon Ho Jeon,Seung Yun Baek,Seung Min Baek,김용주 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.4

This study was conducted to analyze the engine load ratio of a 38 kW agricultural tractor to calculate national emissions. Engine output was calculated using engine CAN (Controller area network) data measured through a load measurement system. In this study, plow tillage (PT) and rotary tillage (RT), which are the main agricultural tasks of small and medium horsepower tractors, were selected and performed three times for each stage. The engine load ratio was calculated as the ratio of the engine power generated during work and the engine rated power, and weights (25% each for PT M1, PT M2, RT L3, and RT L4) according to the agricultural work ratio were applied. The engine load ratio was found to be an average of 0.68 and 0.75 for the M1 and M2 stages of plow tillage work, respectively, and an average of 0.57 and 0.65 for the L3 and L4 stages of rotary tillage work, respectively. The weighted load ratio was 0.17, 0.19, 0.14, and 0.16 for plow tillage operation M1, M2, and rotary tillage operation L3 and L4, respectively. The integrated load factor was found to be 0.66, which is approximately 1.38 higher than the current domestic load factor of 0.48.

Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review

ISLAM SUMAIYA,REZA MD NASIM,Samsuzzaman,Ahmed Shahriar,Cho Yeon Jin,노동희,정선옥,홍순중 사단법인 한국정밀농업학회 2024 정밀농업과학기술지 Vol.6 No.1

The agricultural sector faces increasing challenges in ensuring food security and optimizing crop yield, necessitating innovative solutions for early detection and mitigation of plant growth stress. The integration of advanced imaging technologies with artificial intelligence (AI) has emerged as a powerful tool for non-invasive, real-time monitoring of plant health. The objective of this paper was to review the application of machine vision and AI in identifying and classifying plant growth stress, with a focus on stressors, datasets, and the use of intelligent algorithms. The significance of plant growth stress induced by environmental variables, including temperature, light, nutrient deficiencies, and water supply were addressed and the conventional stress detection methodologies, underscores their inherent limitations, and establishes the groundwork for the exploration of state-of-the-art technologies in stress assessment. Various sensor technologies were explored, encompassing traditional RGB cameras, multispectral and hyperspectral sensors, and thermal imaging, each capable of capturing distinct stress signatures. Machine vision, leveraging high-resolution imaging and spectroscopy, offers detailed insights into plant physiological responses. Coupled with AI approaches such as deep learning, neural networks, and pattern recognition, machine vision enables the automated analysis of vast datasets, enhancing the accuracy and speed of stress detection. The recent advancements in image processing techniques tailored for plant stress identification were focused and discussed the role of feature extraction, classification, and predictive modelling in achieving robust results. The potentials of AI in plant stress physiology and its role in overcoming the limitations of traditional methods, and the use of unsupervised identification of visual symptoms to quantify stress severity, allowing for the identification of different types of plant stress were studied. Moreover, the potentials of machine vision technology and AI for real-time monitoring and decision support systems in precision agriculture were discussed. The findings of this review would contribute to the growing field of agricultural technology, offering insights into the development of automated tools that could aid farmers and researchers in mitigating the impact of abiotic stressors on crop/plant health and productivity.