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Dissertations / Theses on the topic 'Precision farming Agricultural engineering'
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Rusch, Peter C. "Precision farming in South Africa." Diss., Pretoria : [s.n.], 2001. http://upetd.up.ac.za/thesis/available/etd-01072004-153302.
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Dube, Elias Edo. "Wireless Farming: a mobile and Wireless Sensor Network based application to create farm field monitoring and plant protection for sustainable crop production and poverty reduction." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20488.
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There is a remarkable growth in the field of Information Communication Technology (ICT) in Developing Countries (DCs). Telecommunication is one of the areas where ICT is recording an ongoing rapid change. Mobile phones are becoming pervasive in daily scenario; and among the beneficiaries of this are farmers. Farmers are using mobile phones in executing their farming business and daily life. At the same time, Wireless Sensor Networks (WSNs) are also showing a result in developed part of our world. WSNs potential in sensing various environmental condition, their affordability and applicability motivated conducting of this master thesis. Therefore, the objective of conducting this master thesis is to investigate and identify how the use of mobile phones in conjunction with WSN enable farmers in Ethiopia monitor and control their farm field. We use firsthand qualitative data we gathered during our field work in Ethiopia to design our proposed prototype. Functional requirements and system design guideless are obtained from observation we make and interviews we carry out on irrigation based farmers around town of Meki in region of Oromia. We use our prototype to demonstrate and evaluate how irrigation based farmers benefit from existence of such system.
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Chen, Yu. "Development of an Intelligent Sprayer to Optimize Pesticide Applications in Nurseries and Orchards." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1290526778.
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Adrian, Anne Mims Rainer R. Kelly. "Factors influencing adoption and use of precision agriculture." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Summer/Dissertations/ADRIAN_ANNE_27.pdf.
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Addicott, James Edward. "Farming by satellites : how West Country farmers were being driven to, and by, precision agricultural systems." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/278696.
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Precision farming integrates satellite coordination and information communication technologies into farming practices to deliver self-driving and auto-regulating machinery and equipment to farmers, who can afford to invest, right across the globe. It is often sold on the basis that it can help clean up or ‘ecologically modernise’ conventional, industrial agriculture. It should also increase production rates in industrial agriculture to help to ‘feed the world’ as well as being cost effective in ways that could make farmers more money – miracle-grow formula and win-win technology. There are critical concerns that precision farming facilitates a continuing trend of transnational firms appropriating control over agricultural industries. Many neo-Marxist or neo-Weberian critics contend that any ‘green’ benefits fall secondary to the more dominant social and economic trend of ongoing capital accumulation, increasing rationalisation and industrial progress that has been deemed detrimental to natural environments and human populations. These social and economic pressures are actually the real drivers in change. Rather than greening industrial agriculture, precision farming is another way of masking over and profiting from the risks caused by ongoing capitalist accumulation and industrial agriculture. The other set of concerns are to do with human culture and labour. Farming is the grass roots of modern civilisation and dependent upon human labour, knowledge and cultural methods. With the introduction of data over knowledge, and auto-steering tractors over human labour and skills, what kinds of impacts will this have on farm families, rural cultures within countryside landscapes in Britain or other countries where precision farming is being adopted? As a farmer’s son, I was concerned about the impact the computerisation of agriculture will have on family farms, nature and rural communities. I spent four years interviewing and working with a cooperative group of Duchy of Cornwall farmers in the West Country of England. I wanted to know why they were using these new technologies and the kinds of benefits, impacts or outcomes that they experienced following adoption. The results tend to confirm critics’ concerns, unfortunately. Precision farming has much more to do with the organising of agricultural production. The restructuring of farming by way of precision farming greater empowers transnational agribusinesses and Agri-Food supply chains, rather than protecting the environment, feeding hungry people or making family farming more sustainable. I conclude my research by suggesting that it is not technology, or agricultural technologies such as precision farming that will deliver these end goals in and of them selves. There could be room to improve precision farming systems if they are coupled with well-managed policy designs and agri-environmental schemes.
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Rahman, Baishali. "Estimating the Economic Benefits of Automatic Section Control in the North Dakota Prairie Pothole Region." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28870.
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The impact of Automatic Section Control (ASC) as a tool of Precision Agricultural Technology as considered in the more efficient application of inputs to produce the four major crops, corn, soybean, HRSW, and canola in the North Dakota Prairie Pothole Region. Reduction in machinery overlap in the sample 105 fields was calculated by simulating the routing paths of a 60-feet wide planter with 24 sections controlled and a 120-feet wide boom sprayer with individual nozzle control. The dollar and percentage seed and chemical costs that a farm can save by reducing overlapping area were calculated. Impact of field parameters on net savings were estimated by developing and estimating an econometric model. Results show that ASC can save substantial cost in the sample fields while field shape had the highest significant impact on net cost savings.North Dakota State University. Department of Agribusiness and Applied Economics
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Shelley, Anthony N. "INCORPORATING MACHINE VISION IN PRECISION DAIRY FARMING TECHNOLOGIES." UKnowledge, 2016. http://uknowledge.uky.edu/ece_etds/86.
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The inclusion of precision dairy farming technologies in dairy operations is an area of increasing research and industry direction. Machine vision based systems are suitable for the dairy environment as they do not inhibit workflow, are capable of continuous operation, and can be fully automated. The research of this dissertation developed and tested 3 machine vision based precision dairy farming technologies tailored to the latest generation of RGB+D cameras. The first system focused on testing various imaging approaches for the potential use of machine vision for automated dairy cow feed intake monitoring. The second system focused on monitoring the gradual change in body condition score (BCS) for 116 cows over a nearly 7 month period. Several proposed automated BCS systems have been previously developed by researchers, but none have monitored the gradual change in BCS for a duration of this magnitude. These gradual changes infer a great deal of beneficial and immediate information on the health condition of every individual cow being monitored. The third system focused on automated dairy cow feature detection using Haar cascade classifiers to detect anatomical features. These features included the tailhead, hips, and rear regions of the cow body. The features chosen were done so in order to aid machine vision applications in determining if and where a cow is present in an image or video frame. Once the cow has been detected, it must then be automatically identified in order to keep the system fully automated, which was also studied in a machine vision based approach in this research as a complimentary aspect to incorporate along with cow detection. Such systems have the potential to catch poor health conditions developing early on, aid in balancing the diet of the individual cow, and help farm management to better facilitate resources, monetary and otherwise, in an appropriate and efficient manner. Several different applications of this research are also discussed along with future directions for research, including the potential for additional automated precision dairy farming technologies, integrating many of these technologies into a unified system, and the use of alternative, potentially more robust machine vision cameras.
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Siemens, Mark Cornelius 1965. "Cable-drawn farming system analysis and control development." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/282232.
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Four types of cable drawn farming systems, a single engine system, a double engine system, a perimeter system, and a double implement system, were analyzed to determine which was best suited for Arizona. The systems were compared in terms of relative cost, reliability/simplicity and field capacity. Field capacity computation variables were implement width, implement speed, tower travel speed, implement carrier travel speed, and implement rotation time. The analysis showed the single engine system was the least expensive, simplest system with a field capacity identical to that of the double engine system, eight percent lower than the double implement system, and approximately thirteen percent higher than the perimeter system. Based on these results, the single implement system was judged superior to the others. The parameters affecting single implement system performance were then examined to optimize performance. The evaluation yielded a recommendation that the system be designed to have a tower speed of 48 ft/min, and a rotation time of 7.5 seconds. A positioning system for the mobile truss of a cable drawn farming system was also developed and tested. The system used a linear move irrigation system's above ground cable guidance system for steering, a wicket positioning system for stopping the machine at the indexing locations, and a wire-alignment system to control inner tower alignment. The system was tested over a length of 280 ft using a five tower, 575 ft long, linear move irrigation system. It was found that the above ground cable guidance system provided ±0.5 ft steering accuracy, the wicket positioning system controlled the power unit and end tower position within ±0.2 ft of the target destination, and that the wire alignment system controlled inner tower position within ±0.3 ft of the target destination. Statistical analysis of the test results showed the probability of position error being controlled to within ±0.4 ft and ±0.8 ft to be at the 99.7% and 99.99% confidence levels, respectively.
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Prigg, David B. "DESIGN OF A HYDRAULICALLY-ACTUATED HEXAPOD ROBOT FOR ORGANIC FARMING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1588002562729248.
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Whitlow, John Richard. "Gullying within dambos, with particular reference to the communal farming areas of Zimbabwe." Thesis, University of London, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320320.
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Chen, Howard. "Design of a controlled environment agricultural plant inspection robot." Thesis, University of Iowa, 2012. https://ir.uiowa.edu/etd/2838.
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Without an increase in cropland, agricultural efficiency must be tripled in the next 50 years to sustain the increased demand for food. Controlled environment agriculture (CEA) systems are likely to play an important role in the increase of agricultural efficiency. CEA systems, however, require constant observation because decisions must be quickly made when plants show signs of stress. A visual inspection system that uses a robotic camera system would permit visual access to inaccessible plants in a large hydroponics operation or allows an observer to remotely inspect plants for multiple small or remote CEA operations, whereas a dedicated CEA specialist would be beneficial but impractical under present conditions. This thesis presents a theoretical design for a plant inspection robot. The design parameters, design process, and the system specification necessary to satisfy the design constraints were examined for this system. The design analysis revealed that the major components of the plant inspection robot must be designed sequentially, starting with the imaging system. The imaging system design revealed that the system parameters were governed by illumination, shape and size of the object, and the desired detail. The motion system design was governed by velocity, acceleration, work area, and accuracy. An example design for a system used for visual inspection of 289 romaine lettuce plants was presented. This design was shown to be feasible from the theoretical perspective and could be built from commercially-available components, reducing development time and cost.
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Colaizzi, Paul Dominic. "Ground based remote sensing for irrigation management in precision agriculture." Diss., The University of Arizona, 2001. http://hdl.handle.net/10150/280497.
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The relationship between remotely sensed canopy temperature and soil moisture was studied. The objectives were to relate two remotely sensed canopy temperature-based indices, the Crop Water Stress Index (CWSI) and the Water Deficit Index (WDI), to soil moisture through the water stress coefficient, to estimate soil moisture depletion with the CWSI and the WDI, and to develop a remote sensing system aboard a linear move irrigation system that would provide field images of the WDI at one-meter spatial resolution. Studies were conducted in Maricopa, Arizona during the 1998 and 1999 seasons with cotton (Gossypium hirsutum, Delta Pine 90b). In 1998, the field was surface irrigated (low frequency irrigation), and the CWSI was calculated from canopy temperature measurements using stationary infrared thermometers. In 1999, the field was irrigated with a linear move system (high frequency irrigation), and the WDI was calculated using measurements made by the on board remote sensing system. Both the CWSI and the WDI were correlated to soil moisture through the water stress coefficient. Soil moisture depletion could be estimated using the CWSI under low frequency irrigation, but could not be estimated using the WDI under high frequency irrigation. These differences were attributed to the range of soil moisture resulting from infrequent surface irrigation vs. frequent irrigation using the linear move. High spatial resolution images of the WDI could nonetheless monitor water stress throughout the field from partial to full canopy cover, which demonstrated that ground-based remote sensing is feasible for irrigation management in precision agriculture. This application of remote sensing provides an opportunity to improve water use efficiency.
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Kang, Choongkwan. "Evaluation of economic and water quality effects for variable rate application of nitrogen fertilizer /." free to MU campus, to others for purchase, 1996. http://wwwlib.umi.com/cr/mo/fullcit?p9821346.
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Mourad, Jacob, and Emil Gustafsson. "Curve Maneuvering for Precision Planter." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157339.
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With a larger global population and fewer farmers, harvests will have to be larger and easier to manage. By high precision planting, each crop will have the same available area on the field, yielding an even size of the crops which means the whole field can be harvested at the same time. This thesis investigates the possibility for such precision planting in curves. Currently, Väderstads planter collection Tempo, can deliver precision in the centimeter range for speeds up to 20 km/h when driving straight, but not when turning. This thesis makes use of the available sensors on the planters, but also investigates possible improvements by including additional sensors. An Extended Kalman Filter is used to estimate the individual speeds of the planting row units and thus enabling high precision planting for an arbitrary motion. The filter is shown to yield a satisfactory result when using the internal measurement units, the radar speed sensor and the GPS already mounted on the planter. By implementing the filter, a higher precision is obtained compared to using the same global speed for all planting row units.
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Kayrouz, Benjamin Michael. "PRECISION AGRICULTURE: REALIZING INCREASED PROFIT AND REDUCED RISK THROUGH COST MAP AND LIGHTBAR ADOPTION." Lexington, Ky. : [University of Kentucky Libraries], 2008. http://hdl.handle.net/10225/875.
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Thesis (M.S.)--University of Kentucky, 2008.Title from document title page (viewed on November 3, 2008). Document formatted into pages; contains: ix, 58 p. : ill. (some col.). Includes abstract and vita. Includes bibliographical references (p. 55-57).
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Colley, Richard T. III. "Development of a Machine Vision System for Mass Flow Sensing and High-Resolution Mapping of Granular Fertilizer Application." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1543564969065918.
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Zandonadi, Rodrigo S. "COMPUTATIONAL TOOLS FOR IMPROVING ROUTE PLANNING IN AGRICULTURAL FIELD OPERATIONS." UKnowledge, 2012. http://uknowledge.uky.edu/bae_etds/11.
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In farming operation, machinery represents a major cost; therefore, good fleet management can have a great impact on the producer’s profit, especially considering the increasing costs of fuel and production inputs in recent years. One of the tasks to be accomplished in order to improve fleet management is planning the path that the machine should take to cover the field while working. Information such as distance traveled, time and fuel consumption as well as agricultural inputs wasted due to off-target-application areas are crucial in the path planning process. Parameters such as field boundary size and geometry, machine total width as well as control width resolution present a great impact on the information necessary for path planning.
Researchers around the world have proposed methods that approach specific aspects related to path planning, the majority addressing machine field efficiency per-se, which a function of total time spent in the field as well as effective working time. However, wasted inputs due to off-target-application areas in the maneuvering regions, especially in oddly shaped agricultural fields might be as important as field efficiency when it comes down to the total operation cost. Thus, the main purpose of this research was to develop a path planning method that accounts for not only machinery field efficiency, but also the supply inputs.
This research was accomplished in a threefold approach where in the first step an algorithm for computing off-target application area was developed, implemented and validated resulting in a computational tool that can be used to evaluate potential savings when using automatic section control on agricultural fields of complex field boundary. This tool allowed accomplishment of the second step, which was an investigation and better understanding of field size and shape as well as machine width of the effects on off-target application areas resulting in an empirical method for such estimations based on object shape descriptors. Finally, a path planning algorithm was developed and evaluated taking into consideration the aspects of machine field efficiency as well as off-target application areas.
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Rabe, Nicole J., and University of Lethbridge Faculty of Arts and Science. "Remote sensing of crop biophysical parameters for site-specific agriculture." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2003, 2003. http://hdl.handle.net/10133/195.
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Support for sustainable agriculture by farmers and consumers is increasing as environmental and socio-economic issues rise due to more intensive farm practices. Site-specific crop management is an important component of sutainable agriculture, within which remote sensing can play an integral role. Field and image data were acquired over a farm in Saskatchewan as part of a national research project to demonstrate the advantages of site-specific agriculture for farmers. This research involved the estimation of crop biophysical parameters from airborne hyperspectral imagery using Spectral Mixture Analysis (SMA), a relatively new sub-pixel scale image processing method that derives the fraction of sunlit canopy, soil and shadow that is contributing to a pixel's relectance. SMA of three crop types (peas, wheat and canola) performed slightly better than conventional vegetation indices in predicting leaf area index (LAI) and biomass using Probe-1 imagery acquired early in the growing season. Other potential advantages for SMA were also indentified, and it was conclude that future research is warranted to assess the full potential of SMA in a multi-temporal sense throughout the growing season.xiv, 194 leaves : ill. (some col.) ; 29 cm.
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Torres, Clayton José. "Arquitetura supervisória aplicável na robótica agrícola móvel." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/18/18145/tde-16112017-113717/.
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A agricultura nacional, buscando uma maior integração e participação no mercado global, tende a investir cada vez mais na automação de máquinas e implementos agrícolas, visando maior eficiência e qualidade em seus produtos. Para responder rapidamente às mudanças impostas pelo mercado, o emprego do conceito de Agricultura de Precisão (AP), têm mostrado bons resultados, tais como uma melhor utilização das máquinas, melhor aproveitamento na área de plantio entre outros benefícios. Para tal, pesquisas voltadas ao desenvolvimento de máquinas, com nível elevado de automação, capazes de operar de forma autônoma, estão ganhando cada vez mais espaço no setor agrícola. Considerando esse cenário, no presente trabalho são apresentadas uma revisão sobre Controle Supervisório e Aquisição de Dados (SCADA), no contexto da Agricultura de Precisão, e a proposta de um modelo supervisório, aplicável na robótica móvel utilizando, como plataforma experimental o veículo Agribot.National agriculture, seeking greater integration and participation in the global market tends to increasingly invest in the automation of agricultural machinery and implements, aiming at greater efficiency and quality in their products. To respond quickly to changes driven by the market, the use of the concept Precision Farming (PF) have shown good results, such as better machine utilization, better utilization in the planting area among others benefits. To this end, research aimed at developing machines with high level of automation, able to operate autonomous, are gaining more and more space in the agricultural sector. Considering this factor, this work is a review on the Supervisory Control and Data Acquisition (SCADA) in the Precision Farming context and the proposal of a supervisory model applicable in mobile agricultural robotics using as platform the vehicle Agribot.
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Schemper, Janel K. "Efficiency of combine usage: a study of combine data comparing operators and combines to maximize efficiency." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17738.
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Master of AgribusinessDepartment of Agricultural Economics
Vincent Amanor-Boadu
Farming is an important industry in the United States. The custom harvesting industry plays a major role in feeding the world. Schemper Harvesting is a family-owned and operated custom harvesting service that employs 20-25 seasonal workers and understanding how to manage a custom harvesting business professionally and efficiently is the key for its success. Today, there is data available through JDLink on John Deere combine performance beginning in year 2012. The purpose of this study is to examine the usefulness of this JDLink data to assess the efficiency of each of Schemper Harvesting’s seven combines, including machine efficiency and different combine operators. The goal is to determine how the data can improve Schemper Harvesting’s overall performance. Statistical methods were used to analyze Schemper Harvesting’s performance. The analysis indicated that fuel is a major expense and there are ways Schemper Harvesting can conserve fuel. This information may prove valuable in being able to operate a combine more efficiently and save money on expenses. Overall, the objective is to improve Schemper Harvesting’s performance, which results in higher profit without sacrificing quality. Precision technology is an added expense to the business. Being able to justify this expense with profit is the answer. Fuel, labor and machinery are the biggest inputs in the custom harvesting business. These costs related to production agriculture have increased the demand for precision agriculture to increase efficiency and profitability. In order to compensate for the investment in technology, it has been demonstrated that it pays for itself. Making correct use of precision technology adds to productivity. With experience, operators improve increasing their overall efficiency. Incentive plans can be utilized through this data. With the availability of data, the costs and benefits of precision technology can be further evaluated. Five of the seven combines are operated by family members and the other two by non-family employees. This study shows that the performance of the non-family employees was below that of family members. The initial assessment for this difference may be attributed to experience because all the family members have been operating combines for most of their lives. This implies that employing people with excellent performance experience records and/or a need to train non-family employees to help them understand the performance expectations at Schemper Harvesting. The results indicate that tracking operational output performance indicators, such as acreage and volume harvest should be completed so that they may be assessed in concert with the technical indicators such as time and fuel use. The study provides the potential benefits of using John Deere’s JDLink data service providing telematics information for its customers with the latest precision agriculture technologies.
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Sama, Michael P. "PRECISE EVALUATION OF GNSS POSITION AND LATENCY ERRORS IN DYNAMIC AGRICULTURAL APPLICATIONS." UKnowledge, 2013. http://uknowledge.uky.edu/bae_etds/14.
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A method for precisely synchronizing an external serial data stream to the pulse-per-second (PPS) output signal from a global navigation satellite-based system (GNSS) receiver was investigated. A signal timing device was designed that used a digital signal processor (DSP) with serial inputs and input captures to generate time stamps for asynchronous serial data based on an 58593.75 Hz internal timer. All temporal measurements were made directly in hardware to eliminate software latency. The resolution of the system was 17.1 µs, which translated to less than one millimeter of horizontal position error at travel speeds typical of most agricultural operations.
The dynamic error of a TTS was determined using a rotary test fixture. Tests were performed at angular velocities ranging from 0 to 3.72 rad/s and a radius of 0.635 m. Average latency from the TTS was shown to be consistently near 0.252 s for all angular velocities and less variable when using a reflector based machine target versus a prism target. Sight distance from the target to the TTS was shown to have very little effect on accuracy between 4 and 30 m. The TTS was determined to be a limited as a position reference for dynamic GNSS and vehicle auto-guidance testing based on angular velocity.
The dynamic error of a GNSS receiver was determined using the rotary test fixture and modeled as discrete probability density functions for varying angular velocities and filter levels. GNSS position and fixture data were recorded for angular velocities of 0.824, 1.423, 2.018, 2.618, and 3.222 rad/s at a 1 m radius. Filter levels were adjusted to four available settings including; no filter, normal filter, high filter, and max filter. Each data set contained 4 hours of continuous operation and was replicated three times. Results showed that higher angular velocities increased the variability of the distribution of error while not having a significant effect on average error. The distribution of error tended to change from normal distributions at lower angular velocities to uniform distributions at higher angular velocities. Internal filtering was shown to consistently increase dynamic error for all angular velocities.
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Dasika, Surya Saket. "ASSESSING THE SPATIAL ACCURACY AND PRECISION OF LIDAR FOR REMOTE SENSING IN AGRICULTURE." UKnowledge, 2018. https://uknowledge.uky.edu/bae_etds/56.
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The objective of this whole study was to evaluate a LiDAR sensor for high-resolution remote sensing in agriculture. A linear motion system was developed to precisely control the dynamics of LiDAR sensor in effort to remove uncertainty in the LiDAR position/velocity while under motion. A user control interface was developed to operate the system under different velocity profiles and log LiDAR data synchronous to the motion of the system. The LiDAR was then validated using multiple test targets with five different velocity profiles to determine the effect of sensor velocity and height above a target on measurement error. The results indicated that the velocity of the LiDAR was a significant factor affecting the error and standard deviation of the LiDAR measurements, although only by a small margin. Then the concept of modeling the alfalfa using the linear motion system was introduced. Two plots of alfalfa were scanned and processed to extract height and volume and was compared with photogrammetric and field measurements. Insufficient alfalfa plots were scanned which prevented any statistical analysis from being used to compare the different methods. However, the comparison between LiDAR and photogrammetric data showed some promising results which may be further replicated in the future.
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Waheed, Tahir. "Artificial intelligence analysis of hyperspectral remote sensing data for management of water, weed, and nitrogen stresses in corn fields." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86060.
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This study investigated the possibility of using ground-based remotely sensed hyperspectral observations with a special emphasis on detection of water, weed and nitrogen stresses contributing towards in-season decision support for precision crop management (PCM).A three factor split-split-plot experiment, with four randomized blocks as replicates, was established during the growing seasons of 2003 and 2004. Corn (Zea mays L.) hybrid DKC42-22 was grown because this hybrid is a good performer on light soils in Quebec. There were twelve 12 x 12m plots in a block (one replication per treatment per block) and the total number of plots was 48. Water stress was the main factor in the experiment. A drip irrigation system was laid out and each block was split into irrigated and non-irrigated halves. The second main factor of the experiment was weeds with two levels i.e. full weed control and no weed control. Weed treatments were assigned randomly by further splitting the irrigated and non-irrigated sub-blocks into two halves. Each of the weed treatments was furthermore split into three equal sub-sub-plots for nitrogen treatments (third factor of the experiment). Nitrogen was applied at three levels i.e. 50, 150 and 250 kg N ha-1 (Quebec norm is between 120-160 kg N ha-1).
The hyperspectral data were recorded (spectral resolution = 1 nm) mid-day (between 1000 and 1400 hours) with a FieldSpec FR spectroradiometer over a spectral range of 400-2500 run at three growth stages namely: early growth, tasseling and full maturity, in each of the growing season.
There are two major original contributions in this thesis: First is the development of a hyperspectral data analysis procedure for separating visible (400-700 nm), near-infrared (700-1300 nm) and mid-infrared (1300-2500 nm) regions of the spectrum for use in discriminant analysis procedure. In addition, of all the spectral band-widths analyzed, seven waveband-aggregates were identified using STEPDISC procedure, which were the most effective for classifying combined water, weed, and nitrogen stress. The second contribution is the successful classification of hyperspectral observations acquired over an agricultural field, using three innovative artificial intelligence approaches; support vector machines (SVM), genetic algorithms (GA) and decision tree (DT) algorithms. These AI approaches were used to evaluate a combined effect of water, weed and nitrogen stresses in corn and of all the three AI approaches used, SVM produced the best results (overall accuracy ranging from 88% to 100%).
The general conclusion is that the conventional statistical and artificial intelligence techniques used in this study are all useful for quickly mapping combined affects of irrigation, weed and nitrogen stresses (with overall accuracies ranging from 76% to 100%). These approaches have strong potential and are of great benefit to those investigating the in-season impact of irrigation, weed and nitrogen management for corn crop production and other environment related challenges.
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Maurer, Jacob Lafe. "The development of a conceptual benchmarking tool representing big data and agricultural technology adoption on the farm." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/19071.
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Master of AgribusinessDepartment of Agricultural Economics
Gregory Ibendahl
One of the latest buzzes amongst agriculture is the storage and analysis of “Big Data.” There are a number of questions surrounding the quality, quantity, and capacity of big data to form real-world decisions based upon past information. Much like the teachings of history, the storybook that big data can reveal about a grower’s operation may hold the answers to the question of: “what is necessary to increase food production which will be required to feed an ever-growing world?” With the increase in interest in precision agriculture, sustainability practices, and the processing of the immense spatial dataset generated on the farm, the next challenge at hand will be in determining how to make technology not only streamlined, but also profitable. Over the past few years, precision agriculture technology has become widely adopted as an agronomic decision making tool. Much like a scientific experiment, the greater the number of similar observations, the greater the degree of confidence can be placed upon a decision. As a means of increasing the number of observations that a farmer can use to base a decision upon, there is becoming increasing demand in being able to combine the data of similar farming operations in order to increase the size and scope of the dataset to generate better decisions benefitting many farms instead of just one. The growing interest in forming community data pools for farm data demonstrates the need for a study for determining how farming practices can be properly benchmarked. The goal was be to evaluate how to use farm data to make economic decisions in a similar manner as one would make agronomic decisions using similar observations. The objective was to design the proper protocol for benchmarking the farm’s potential, and evaluating potential increases in technical efficiency by adopting precision agriculture technology. To accomplish this, a data envelopment analysis was conducted using scale efficiency as a means of determining the frontier of efficient farms. The resounding goal for this study in the future will be to use the model as a means of implementing the secondary process of pooling precision agriculture data to analyze efficiencies gained by the adoption of technology. By demonstrating the value of generating peer groups to increase observations and refine farming practices, farmers can find increased profitability and efficiency by using resources that may already be held within the operation.
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Granemann, Daniel Carvalho. "Efeitos diretos e indiretos de parâmetros dos semivariogramas referentes aos atributos químicos do solo sobre a produtividade de grãos de soja." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/1727.
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De forma a agregar valor à cultura da soja, e consequentemente à comercialização, produtores de médio e grande porte tem utilizado técnicas de agricultura de precisão (AP) como o Sensoriamento Remoto, Sistemas de Informações Geográficas (SIG) e posicionamento via satélite, para auxiliar no gerenciamento das lavouras. Assim, diante da relevância econômica desta cultura para a região sudoeste do Paraná e para o Brasil, são fundamentais os estudos científicos para o aumento de sua
produtividade e rentabilidade. O objetivo deste trabalho é avaliar a correlação entre os atributos químicos do solo e a produtividade da soja, para cada estimativa de parâmetro do semivariograma (alcance, efeito pepita e patamar), e o desdobramento destas correlações em efeitos diretos e indiretos, visando melhorar o processo de
mapeamento da variabilidade espacial dos atributos químicos do solo para a aplicação em AP. A hipótese é que nem todos os atributos do solo usados para estimar os parâmetros do semivariograma tem efeito direto sobre a produtividade, e que mesmo em grupos de plantas dentro de uma área maior é possível estimar os parâmetros dos semivariogramas. O experimento foi realizado em uma área comercial de 19,7 ha, situada no município de Pato Branco – PR, de coordenadas geográficas centrais 26º 11’ 35” de latitude Sul, 52º 43’ 05” de longitude Oeste, e altitude média de 780 m. A área é cultivada com soja há mais de 30 anos, sendo
adotada atualmente a cultivar Brasmax Alvo RR – Don Mario 5.9i, com espaçamento entre fileiras de 0,50 m e 13 plantas m-1, totalizando 260 000 plantas ha-1. Para o georreferenciamento da área de estudo e dos pontos de amostragem foi utilizado um par de receptores topográficos ProMarkTM3, realizando-se um posicionamento relativo para a obtenção das coordenadas georreferenciadas. Para a coleta de dados (análises química do solo e produtividade da cultura) foram amostrados 10 blocos na área experimental, cada qual com área de 20 m2 (20 metros de extensão x 1 metro de largura), contendo duas fileiras adjacentes espaçadas de 0,5 m. Cada bloco foi dividido em 20 parcelas de 1 m2, e em cada uma delas foram coletadas 4 sub-amostras em um raio de 0,5 m em relação às entrelinhas dos blocos, compondo-se uma amostra composta para a profundidade 0-10 m e uma amostra composta para 10-20 m para cada parcela, totalizando 200 amostras para cada profundidade. A colheita da soja dos blocos foi realizada em função da maturação e, em cada bloco, formaram-se feixes a cada metro. Na análise dos dados, realizou-se o diagnóstico de multicolinearidade, e posterior análise de trilha das variáveis principais em função das variáveis explicativas (alcance dos atributos químicos: pH, K, P, Ca, etc.). Os resultados obtidos pela análise de trilha dos parâmetros dos semivariogramas dos atributos químicos do solo, indicaram que somente o Fe, Mg, Mn, Matéria Orgânica (MO), P e Saturação por Bases (SB) exerceram efeitos diretos e indiretos sobre a produtividade da soja, apesar de não terem apresentado variabilidade espacial, indicando que a distribuição dos blocos na área não foi capaz de identificar a dependência espacial destes elementos, impossibilitando a elaboração de mapas dos atributos químicos para a aplicação em AP.In order to add value to soybens crops, and hence the marketing, medium and large producers have been using precision agriculture techniques (PA), as the Remote Sensing, Geographic Information Systems (GIS) and positioning satellite, to assist the management of crops. Thus, given the economic relevance of that culture to the southwest of Paraná State and Brazil, scientific studies to increase their productivity and profitability are of main importance. The objective of this study was to evaluate the correlation between the chemical soil properties and soybean yield for each estimated parameter of semivariogram (range, nugget and level effect), and the deployment of these correlations in direct and indirect effects, aiming to improve the mapping process of spatial variability of soil chemical properties for use in PA. The hypothesis is that not all attributes of soil used to estimate the semivariogram parameters has a direct effect on productivity, and that even in groups of plants within a larger area it is possible to estimate the parameters of the semivariograms. The experiment was conducted in a commercial area of 19.7 ha, located in the city of Pato Branco - PR, central geographic coordinates 26º 11 '35 "South, 52 43' 05" West longitude, and average altitude of 780 m. The area is planted with soybeans for over 30 years, currently being adopted to cultivate Brasmax Target RR - Don Mario 5.9i, with row spacing of 0.50 m and 13 plants m-1, totaling 260,000 plants ha-1. For georeferencing of the area of study and sampling points was used a couple of topographic ProMarkTM3 receptors, making a relative positioning to obtain the georeferenced coordinates. To collect data (chemical analyzes of soil and crop yield) were sampled 10 blocks in the experimental area, each with an area of 20 m2 (20 meters long x 1 meter wide) containing two spaced adjacent rows of 0.5 m. Each block was divided into 20 portions of 1 m2, and from each were collected four subsamples at a distance of 0.5 m in relation to the lines of blocks, making up a sample depth for 0-10 cm a sample to 10-20 cm for each plot, totaling 200 samples for each depth. The soybean crop was performed on the blocks depending on maturity, and in each block was considered a bundle at each meter. In the data analysis, it was performed a diagnosis of multicollinearity, and subsequently a path analysis of the main variables according to the explanatory variables (range of chemical attributes: pH, K, P, Ca, etc.). The results obtained by the path analysis of the parameters of the semivariogram of soil chemical properties, indicated that only the Fe, Mg, Mn, organic matter (OM), P and Saturation by bases (SB) exerted direct and indirect effects on soybean productivity, although they have not presented spatial variability, indicating that the distribution of blocks in the area was unable to identify the spatial dependence of these elements, making it impossible to draw up maps of the chemical attributes for use in PA.
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Brilhador, Anderson. "Análise semi-automática do arranjo espacial de plantas de milho utilizando visão computacional." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/2954.
Full textAbstract:
A demanda mundial por alimentos cresce a cada ano, tornando necessário o desenvolvimento de novas tecnologias que aumentem a produção de grãos sem aumentar as áreas destinadas ao para plantio. A cultura de milho é uma das principais commodities do mundo, sendo utilizada na alimentação humana e como ração de outros animais, além de possuir outros fins industriais. O milho é sensível ao arranjo espacial de plantas e qualquer variação no padrão de distribuição pode levar à redução na produção do milho. Atualmente, o processo de verificação da uniformidade dos espaçamentos entre plantas é realizado de forma manual por agrônomos e produtores, a fim de prever possíveis perdas de produção. Nesse contexto, este trabalho propõe uma abordagem automática para a análise do arranjo espacial de plantas por meio da mensuração dos espaçamentos entre plantas de milho em fases inicias de crescimento. A partir dessa mensuração são extraídas informações relevantes como densidade populacional, uniformidade do plantio e estimativas de perdas. A abordagem proposta utiliza técnicas de visão computacional de baixo custo computacional para identificar as plantas de milho e mensurar os espaçamentos entre plantas, permitindo seu uso em dispositivos com baixo poder computacional como smartphones e tablets. Um conjunto de imagens foi construído como uma contribuição adicional do trabalho contento 222 imagens panorâmicas da linha de plantio de milho em três condições de plantio: direto, convencional e direto após aplicação de herbicidas. Os resultados dos experimentos alcançaram uma taxa de 90% de precisão e 87% de sensibilidade na identificação das plantas de milhos presentes na base. Uma comparação entre as medidas dos espaçamentos entre plantas realizadas de forma manual e por visão computacional, não apresentou diferenças significativas entre as medições, indicando a eficácia da abordagem proposta no trabalho.Global demand for food is growing every year, requiring the development of new technologies that increase grain production without increasing the areas destined for planting. The corn crop is a major commodity in the world and is used as food, feed for other animals, in addition to having other industrial purposes. Corn is sensitive to the spatial arrangement of plants and any variation in distribution pattern can lead to reduction in the production of corn. Currently, the process of checking the uniformity of spacing between plants is done manually by agronomists and producers in order to predict possible production losses. In this context, this paper proposes an automatic approach to the analysis of the spatial arrangement of plants by measuring the spacing between corn plants in early stages of growth. From this measurement are extracted relevant information such as population density, uniformity of planting and loss estimates. The proposed approach uses computer vision techniques of low computational cost to identify corn plants and measure the spacing between plants, allowing its use in devices with low computational power such as smartphones and tablets. A set of images was built as an additional contribution of work, containing 222 panoramic images of corn planting in three conditions of planting: direct, conventional and direct after applying herbicides. The experimental results achieve 90% of rate accuracy and 87% sensitivity in identification of corn plants present on the base. A comparison of the measurements of the distances between plants made of manual and computer vision way, no presented significant differences between the measurements, indicating the effectiveness of the proposed approach at work.
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Baublys, Andrius. "Augalų lapų optinių savybių analizės jutiklių OptRx naudojimas tręšiant kviečius." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140616_132912-60477.
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Siekiant taupiai naudoti degalus, trąšas, sėklas, augalų apsaugos produktus, gerinti gaminamų produktų kokybę ir konkurencingumą Lietuvos ūkininkų ūkiuose pradedamos diegti tiksliojo ūkininkavimo (TŪ) priemonės. Tikslusis ūkininkavimas prasideda atskiro lauko derlingumo, maisto medžiagų ir dirvožemio tipo skirtumų nustatymu. Šių duomenų pagrindu galima tikslingai planuoti technologines operacijas ir analizuoti biomasės derliaus įvairovės priežastis. Šiame darbe pateikiami žieminių ir vasarinių kviečių tręšimo mineralinėmis trąšomis, panaudojant augalų optinės analizės jutiklius OptRx, tyrimai. Tirta tiksliojo tręšimo įtaka kviečių biometriniams rodikliams, grūdų kokybei ir užaugintos biomasės kiekiui. Tręšiant skystomis mineralinėmis trąšomis (karbamido tirpalu) ir trąšų normos parinkimui naudojant augalų optinės analizės jutiklius, vasarinių kviečių Tybalt grūdų kokybė buvo šiek tiek geresnė, negu tręšiant įprastai (vienoda trąšų norma). Įprastai tręštų vasarinių kviečių grūduose baltymų kiekis buvo 12,18 ± 0,12%, o tręštų naudojant augalų optinės analizės jutiklius OptRx – 12,79 ± 0,09%. Grūdų glitimas, atitinkamai, buvo: 31,08 ± 0,37% ir 31,9 ± 0,12%, grūdų kritimo skaičius – 338,33 ± 2,52 s ir 381 ± 3,61 s, o užaugintos biomasės (šiaudų) derlius – 7,07 ± 0,26 t/ha ir 7,46 ± 0,35 t/ha.In order to sustainably use fuel, fertilizers, seeds, and crop protection products and improve quality and competitiveness of Lithuanian products, Lithuanian farms are introducing precision farming tools. Precision farming starts from the identification of the productivity of an individual field, the differences in its nutrient materials and soil types. Such data can be used for purposeful planning of technological operations and the analysis of the reasons of differences in biomass yield. This paper represents the research of winter and spring wheat fertilization in mineral fertilizers using optical sensors OptRx of crop analysis. The research comprises the influence of precision fertilization on wheat biometric parameters, grain quality, and biomass yield. Fertilizing in liquid mineral fertilizers (urea solution) using optical sensors OptRx, the quality of spring wheat Tybalt grains was a little bit better than usually (the same rate of fertilizers in the entire field). Grain protein content of conventionally fertilized spring wheat was 12.18 ± 0.12%, the same measure in plants fertilized using optical sensors OptRx was 12.79 ± 0.09%. Grain gluten was 31.08 ± 0.37% and 31.9 ± 0.12%, the falling number of grain was 338.33 ± 2.52 and 381.00 ± 3.61 s, and biomass (straw) yield was 7.07 ± 0.26 t/ha and 7.46 ± 0.35 t/ha, respectively.
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Fink, Caleb D. "Developing, Evaluating, and Demonstrating an Open Source Gateway and Mobile Application for the Smartfarm Decision Support System." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1880.
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The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed to send data to the cloud from remote SmartFarm Data Acquisition (DAQ) nodes, collect measurement data from remote SmartFarm DAQ nodes, provide a means of wirelessly programming remote SmartFarm DAQ nodes, and a tool that provides data analysis and insight from remote SmartFarm DAQ nodes. It is evaluated to work with 900MHz radios, SmartFarm DAQ nodes, and costs $35. Its setup takes 4 steps and ~20 minutes installation time, does not require maintenance, can utilize Wi-Fi, Bluetooth, and other wireless protocols, and software can port to other systems. The gateway measured data rate of 93.4Mbit/s internet upload speed, passing a range of 252 to 1592 bytes of data from a remote node to the cloud, consumes 2.8 Watts, with a software efficiency of 25% CPU usage, a measurement efficiency of 1 message every 15 seconds, can provide data analysis with the cloud service tool, and it can wirelessly program remote DAQ nodes. The goal of the mobile app is educating farmers, academia, and community members, of farming sustainably today, and for the future. The app is used as a tool to aid people in farming sustainably, teaching agricultural stewardship, and teaching environmental conservation. The app is evaluated with adaptation of 85.1%, frequency of use at 0.12 respondents/minute, and 22 respondents said they find the SmartFarm DSS as beneficial. By developing, evaluating, and demonstrating the gateway and mobile app, the SmartFarm decision support system is a viable option for improving agricultural stewardship and retaining farmers’ ownership of their data.
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Borges, Ligia Francielle. "Aplicação web para criação de mapas temáticos em agricultura de precisão." Universidade Tecnológica Federal do Paraná, 2017. http://repositorio.utfpr.edu.br/jspui/handle/1/2938.
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A análise de mapas temáticos, no contexto da agricultura de precisão (AP), é um recurso utilizado para compreender a variabilidade espacial dos atributos do solo em áreas de cultivo, podendo trazer importantes subsídios para a realização de um manejo racional, promovendo aumento da produtividade e redução do impacto ambiental. Neste contexto, o objetivo desse trabalho foi desenvolver e disponibilizar uma ferramenta computacional em ambiente web, que permite a geração de mapas temáticos fazendo uso de métodos tradicionais de interpolação de dados sugeridos na literatura (inverso da distância elevado à uma potência, média móvel e vizinho mais próximo). O software foi testado com dados provenientes de pesquisas de AP (atributos físicos e químicos do solo e produtividade do milho) desenvolvidas em uma área agrícola de 19,8 ha localizada na região oeste do estado do Paraná. Os resultados obtidos mostraram que o uso do software permitiu que fossem gerados mapas temáticos de variáveis normalmente utilizadas em agricultura de precisão, possibilitando avaliar a distribuição de cada atributo na área a ser trabalhada e identificar possíveis causas de variação na produtividade. Por estar instalado em servidor com recursos sob demanda, o software possui desempenho satisfatório do ponto de vista funcional e pode ser acessado de qualquer ambiente web (browser).The analysis of thematic maps, in the precision agriculture (AP) context, is a resource used to understand the spatial variability of soil attributes in cultivated areas, witch can bring important subsidies for rational handling, improving yield and reducing environmental impact. Thus, the main goal of this research was to develop and make available a web-based software, which provides the ability to draw thematic maps according to well-known methods of data interpolation (inverse of distance weighted, moving average, nearest-neighbor). The software was tested with AP research data (physical and chemical soil attributes and corn yield) developed in a 19.8 ha agricultural area located in the western region of Parana state. The use of the software made possible generating thematic maps of variables usually used in precision agriculture, allowing to evaluate the distribution of each attribute in the area and identify possible causes of variations in yield. As the software is installed in a on-demand server, it provides good performance from a functional point of view and can be accessed from any web environment (browser).
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Klopfenstein, Andrew A. "An Empirical Model for Estimating Corn Yield Loss from Compaction Events with Tires vs. Tracks High Axle Loads." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461316924.
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(11211111), Madhu Lekha Guntaka. "IOT BASED LOW-COST PRECISION INDOOR FARMING." Thesis, 2021.
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There is a growing demand for indoor farm management systems that can track plant growth, allow automatic control and aid in real-time decision making. Internet of Thing (IoT)-based solutions are being applied to meet these needs and numerous researchers have created prototypes for meeting specific needs using sensors, algorithms, and automations. However, limited studies are available that report on comprehensive large-scale experiments to test various aspects related to availability, scalability and reliability of sensors and actuators used in low-cost indoor farms. The purpose of this study was to develop a low-cost, IoT devices driven indoor farm as a testbed for growing microgreens and other experimental crops. The testbed was designed using off-the-shelf sensors and actuators for conducting research experiments, addressing identified challenges, and utilizing remotely acquired data for developing an intelligent farm management system. The sensors were used for collecting and monitoring electrical conductivity (EC), pH and dissolved oxygen (DO) levels of the nutrient solution, light intensity, environmental variables, and imagery data. The control of light emitting diodes (LEDs), irrigation pumps, and camera modules was carried out using commercially available components. All the sensors and actuators were remotely monitored, controlled, and coordinated using a cloud-based dashboard, Raspberry Pis, and Arduino microcontrollers. To implement a reliable, real-time control of actuators, edge computing was used as it helped in minimizing latency and identifying anomalies.
Decision making about overall system performance and harvesting schedule was accomplished by providing alerts on anomalies in the sensors and actuators and through installation of cameras to predict yield of microgreens, respectively. A split-plot statistical design was used to evaluate the effect of lighting, nutrition solution concentration, seed density, and day of harvest on the growth of microgreens. This study complements and expands past efforts by other researchers on building a low cost IoT-based indoor farm. While the experience with the testbed demonstrates its real-world potential of conducting experimental research, some major lessons were learnt along the way that could be used for future enhancements.
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Jenkins, Amanda Renee. "Precision Farming Information Sources Used by Cotton Farmers." 2009. http://trace.tennessee.edu/utk_gradthes/532.
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Precision farming entails production decisions that are made by obtaining data about soil and field traits. Information about yield and soil characteristics at different locations is collected and management strategies consistent with this information are designed. Information providers play a major role in helping farmers incorporate precision farming information into their decision-making processes. The main goal of this research is to add to the understanding of preferences of information sources in the context of precision farming. Data from cotton farmers in 11 Southeastern states were used to achieve this goal. Results from this study can be utilized by precision farming information providers to more effectively target their clientele.
This thesis examines two related research topics. The first essay focuses on the use of Extension as a source of precision farming information and the factors that determine preferences for this information source. The second essay examines farm business attributes, farmer characteristics and regional factors affecting cotton farmers‘ use of various precision farming information sources.
Farmers‘ preferences for precision farming education programming from Extension were described and analyzed using a basic statistical analysis. Results indicate that farmers tend to use various information sources simultaneously with Extension to make decisions about precision farming technology. An independent samples t-test showed that the means for age, education, income, farm size, and land tenure were statically significantly different between Extension users and non-users when other factors that may influence the use of precision farming information sources were not controlled.
A multivariate probit model was used in the second essay to determine the farm business, farmer, and regional characteristics affecting the use of different precision farming information sources. The multivariate approach accounts for correlation among the different information sources. Results suggest that the decision to use a precision farming information source may be correlated with the decision to use other information sources. When controlling for other factors that may influence the use of precision farming information sources age, education, farm size, and income were found to significantly affect the decision to use information sources.
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Ramirez, Huerta Ana Karina. "Saving water in farming : methodology for water conservation verification efforts in the agricultural sector." Thesis, 2013. http://hdl.handle.net/2152/25168.
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This dissertation develops, tests and validates statistical methods for verifying the amount of water conserved as a result of investments in precision leveling, other on-farm conservation measures in place, weather variation and farmer behavior. This evaluation uses a sample of 328 unique fields from Lakeside Irrigation Division in Texas over a six-year period, totaling 966 observations. Results show that precision leveling accounts for a 0.30 acre-feet reduction of irrigation water per acre leveled. This Mixed-Level Model (MLM) estimate for precision leveling water savings is more precise than the estimates either from an Ordinary Least Square Model or a Fixed Effect Model. A meta analysis combines the results from this model with other similar studies. Although the mean estimate of the meta-analysis is similar to the MLM estimate, the meta-analysis further reduces the standard error of the mean precision leveling estimate by 2 percent. A better approximation of the acre-feet water savings per acre farmed translates into less uncertainty for water regulators, managers and policymakers regarding the volume of conserved water that is available for transfer.text
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(11150976), Eric Kong. "Analyzing the Effects of Autonomous Navigation on Row Crop Farming." Thesis, 2021.
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As the global population rises, so does the demand for food, feed, fiber, and fuel. Meeting this demand has become increasingly difficult due to the decline in farm labor and challenges associated with the economic viability of agricultural systems. Autonomous agricultural machinery has the potential to mitigate some of major challenges that crop production systems will face. Widespread adoption of autonomous machinery is dependent on two key factors, the cost and environmental impact. The development and adoption of autonomous vehicles will only occur if it is profitable for equipment manufacturers and farmers. As distillate fuel use for crop production increases, fuel efficient operations that minimize greenhouse gas emissions will mitigate the environmental impact of farming.The objective of this research was to develop a model to quantify the cost, energy use, and emissions associated with the use of agricultural machinery used for row crop farming. The model calculates the cost of different sized machinery fleets for planting and harvest. Autonomy facilitates swarm farming, and the model can quantify and compare these to human-operated machinery systems.
For an 800-hectare case study farm in the Midwest, with the acreage split evenly between corn and soybeans, the most cost-effective planting machinery fleet was comprised of two autonomous, 56-kW JD 5075E tractors pulling 4-row planters ($40/ha/yr). The most cost-effective fleet used the most fuel (4,327 liters) and produced the most emissions (219,735 grams). For a similar conventional system to complete planting during the same working window, it would require 4 tractors and cost $75/ha/yr. The $35/ha/yr difference between the similar fleets was the value added by autonomy. Current row crop farming trends have shifted towards fewer operators with larger machines and implements. The most cost-effective, single operator machinery set from the database (Case Magnum 200 with a 16-row planter) costs $43/ha/yr more than overall most cost-effective fleet. Total fuel used to complete the planting operation was minimized by using a single John Deere 8320R pulling a 36-row planter. To plant all 800-hectares, the 8320R used 2,528 liters of diesel fuel and produced a combined 44,002 grams of emissions. The JD 5075E was able to minimize cost, but it used the most fuel and produced the most greenhouse gas.
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Lawrence, Hayden George. "Adoption of precision agriculture technologies for fertiliser placement in New Zealand : a thesis presented in partial fulfilment of the requirements of the degree of Doctor of Philosophy in Agricultural Engineering at Massey University, Palmerston North, New Zealand." 2007. http://hdl.handle.net/10179/1429.
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Major agronomic and economic losses are caused by inaccurate application of nutrients from ground based spreading vehicles. These losses come from both over and under application of fertiliser resulting from such practices as driving at inappropriate bout widths. This work reviewed current spreader testing procedures; compared the performance of international test methodologies and evaluated the use of a digital image processing program to perform spreader testing. Methods to evaluate field performance were developed; this analysis of field application was used to calculate the economic effect of using precision agricultural technologies in New Zealand dairy farming systems. A matrix of fourteen hundred 0.5 x 0.5 m fertiliser collection trays was used to evaluate individual test methodologies. Results indicated that there were major variations in calculated certifiable bout width between different methods and direct comparison should be avoided. Tray layout within ± 5 m of the centre spread line had the largest effect on calculated bout width whilst methods that incorporated rows of trays in the longitudinal direction were less variable compared to those using a single transverse test. The probability too accurately assign bout widths using different international test methods was analysed, the ACCU Spread (Australia) test method had the highest level of confidence in its bout width calculation followed by the ES (Europe) test method. The ISO(i) (World), ISO(ii) (World) and Spreadmark (NZ) tests were all found to be comparable to one another whilst the ASAE (USA) method had the lowest level of confidence in its bout width calculation because of wide collector tray spacing. A method to extract a wider range of data from spreader tests using a hybrid image processing system was developed. Results indicated that there was a strong relationship between two dimensional particle area and particle mass under laboratory (R2 = 0.991) and field (R2 = 0.988) conditions. Although transverse spreader tests provided a good indication of machine performance, they did not account for the interaction of the spreader and its operational environment. A method was developed that used the vehicle location during field application and the transverse spread pattern represented as polygons to create field application maps. Initial results showed large variations compared to the measured transverse spread pattern. A wider study over 102 paddocks on four dairy farms showed that average variation was 37.9%. An improvement to the field application method discussed is given; this tool used the geographical position, heading angle and a series of static spread pattern tests from the spreading vehicle to achieve greater accuracy in field measurements. The described field application methods were used to assess the ability to execute a nutrient plan using both actual and optimised spreading data collected during field application. A loss of $66.18 ha-1 was calculated when comparing the efficiency of using current spreading methods to those assumed in nutrient budgeting practice. If a guidance and control system were used correctly to provide optimised field application the loss could be reduced to $46.41 ha-1. This work highlighted the difficulties in achieving accurate field nutrient application; however, by developing the ability to quantify field performance, economic opportunities could be evaluated. Overall, this work found that there was a strong agronomic and economic case for the implementation of precision agricultural technologies in the New Zealand fertiliser industry. However, the current range of equipment used by the spreading industry would have difficulty in delivering these benefits.
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Prinsloo, Frederik Christoffel. "Development of a GIS-based decision support tool for environmental impact assessment and due-diligence analyses of planned agricultural floating solar systems." Diss., 2019. http://hdl.handle.net/10500/26166.
Full textAbstract:
Text in EnglishIn recent years, there have been tremendous advances in information technology, robotics, communication technology, nanotechnology, and artificial intelligence, resulting in the merging of physical, digital, and biological worlds that have come to be known as the "fourth industrial revolution”. In this context, the present study engages such technology in the green economy and to tackle the techno-economic environmental impact assessments challenges associated with floating solar system applications in the agricultural sector of South Africa. In response, this exploratory study aimed to examine the development of a Geographical Information System (GIS)-based support platform for Environmental Impact Assessment (EIA) and due-diligence analyses for future planned agricultural floating solar systems, especially with the goal to address the vast differences between the environmental impacts for land-based and water-based photovoltaic energy systems. A research gap was identified in the planning processes for implementing floating solar systems in South Africa’s agricultural sector. This inspired the development of a novel GIS-based modelling tool to assist with floating solar system type energy infrastructure planning in the renewable energy discourse. In this context, there are significant challenges and future research avenues for technical and environmental performance modelling in the new sustainable energy transformation. The present dissertation and geographical research ventured into the conceptualisation, designing and development of a software GIS-based decision support tool to assist environmental impact practitioners, project owners and landscape architects to perform environmental scoping and environmental due-diligence analysis for planned floating solar systems in the local agricultural sector. In terms of the aims and objectives of the research, this project aims at the design and development of a dedicated GIS toolset to determine the environmental feasibility around the use of floating solar systems in agricultural applications in South Africa. In this context, the research objectives of this study included the use of computational modelling and simulation techniques to theoretically determine the energy yield predictions and computing environmental impacts/offsets for future planned agricultural floating solar systems in South Africa. The toolset succeeded in determining these aspects in applications where floating solar systems would substitute Eskom grid power. The study succeeded in developing a digital GIS-based computer simulation model for floating solar systems capable of (a) predicting the anticipated energy yield, (b) calculating the environmental offsets achieved by substituting coal-fired generation by floating solar panels, (c) determining the environmental impact and land-use preservation benefits of any floating solar system, and (d) relating these metrics to water-energy-land-food (WELF) nexus parameters suitable for user project viability analysis and decision support. The research project has demonstrated how the proposed GIS toolset supports the body of geographical knowledge in the fields of Energy and Environmental Geography. The new toolset, called EIAcloudGIS, was developed to assist in solving challenges around energy and environmental sustainability analysis when planning new floating solar installations on farms in South Africa. Experiments conducted during the research showed how the geographical study in general, and the toolset in particular, succeeded in solving a real-world problem. Through the formulation and development of GIS-based computer simulation models embedded into GIS layers, this new tool practically supports the National Environmental Management Act (NEMA Act No. 107 of 1998), and in particular, associated EIA processes. The tool also simplifies and semi-automates certain aspects of environmental impact analysis processes for newly envisioned and planned floating solar installations in South Africa.
Geography
M.Sc. (Geography)
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(7847804), Grace L. Baldwin. "DEVELOPMENT OF DESIGN CRITERIA AND OPTIONS FOR PROMOTING LAKE RESTORATION OF LAKE BOSOMTWE AND IMPROVED LIVELIHOODS FOR SMALLER-HOLDER FARMERS NEAR LAKE BOSOMTWE - GHANA, WEST AFRICA." Thesis, 2019.
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The Lake Bosomtwe impact crater is located in the Ashanti region of Ghana, West Africa. The impact crater diameter from rim to rim is approximately 10.5 km wide with a lake located at the center. Three different districts touch the lake containing 155,000 hectacres of land. There are approximately 7,500 people from 24 villages, and 12 of those villages reside within walking distance of the lake shore. Within the last ten years, the lake has been subjected to overfishing and environmental degradation. The health of the lake has declined due to overfishing and algae blooms caused by improper fertilization rates. Because of these factors, residents of the area have been forced to transition to subsidence farming as their main vocation. According to the Ghana Statistical Service group, 97.6% of the population participates in some form of rural crop farming (Ghana Statistical Service, 2010). Experience with common practices such as crop rotation, fertilizer use, and erosion control is extremely limited. The lake has not been recommended for recreational use due to the excess runoff in the form of agrochemicals, liquid, and organic waste. Caged aquaculture and traditional fishing within Lake Bosomtwe is currently illegal.
A comprehensive Institutional Review Board (IRB) survey was developed for the six primary research questions to be examined. From these six research questions, 147 specific questions were developed. Three of the 147 questions were to obtain Global Positioning System (GPS) data for community households, pit latrines, and water wells or boreholes. This study sought to interview 10-15 farmers per village, for each of the 12 villages located along the shore of Lake Bosomtwe of their perspective on land use change/cover in the Lake Bosomtwe area, current farming practices, current water sanitation and hygiene practices, and current fishing practices. These surveys were collected in the form of oral responses, for which 118 small-holder farmers were interviewed. Of the participants surveyed, 66% were qualified to answer all questions, and 100% of participants completed the survey.
Some specific statistical tests were conducted based of market assessment survey. It was determined that no association between gender and level of education existed. Meaning, that female participants interviewed have just as many opportunities as male participants to pursue education beyond Junior High School (JHS). Yield averages between the villages on the north side of the lake with road access and villages on the southern portion of the lake with limited to no road access were determined to be significantly different. It was determined that road access does affect village yield. When comparing average usable yields between villages located on the northern side of the lake with road access or between villages on the southern side of the lake with limited to no road access, these results were not statistically significant. No significant difference in the scores for villages with road access on the northern side of the lake and villages with limited to no road access on the southern side of the lake existed. Therefore, road access does not affect village usable yield. Through statistical analysis an association was determined between people who practice bathing and washing in the lake and those who practice fishing as a form of livelihood.
Four decision matrices were created to prioritize the following items: Farm Components, technologies to showcase at an appropriate technology center, improved farming practices to showcase through Demonstration Plots, and extension outreach topics. The top three results for the Farm Components were: Appropriate Technology Center (ATC), Demonstration Plots, and a Micro-Credit Union. The top three technologies to showcase as part of the ATC are: PICS Bags, Moisture Meters, and Above-Ground Aquaculture. The three demonstration plots recommended terracing/erosion control, crop rotation, and cover crops. The highest priority extension outreach topics were: basic home/farm finance, improving health through washing stations, and post-harvest loss prevention. The top three priorities of each decision matrix will be the focus of further study, so that these topics can be developed and programs focusing on these needs can be implemented in collaboration with the community partners.