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1. Saltmed Model As An Integrated Management Tool For Precision Management Of Water, Crop, Soil, And FertilizersSALTMED-2009: A modelling tool for Precision Agriculture R. Ragab Centre for Ecology and H... R. Ragab |
2. Smoothness Index Of Thematic MapsA thematic map shows the spatial distribution of one or more specific data themes for standard geographic areas. The thematic maps are generated to represent the studied variables, so interpolators are used to determine their values in places not sampled. It is usuall... C.L. Bazzi, E.G. Souza, D. Stiehl |
3. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial InterpolationStudy on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracti... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang |
4. Analysis Of Water Use Efficiency Using On-the-go Soil Sensing And A Wireless NetworkAn efficient irrigation system should meet the demands of the growing crops. While limited water supply may result in yield reduction, excess irrigation is a waste of resources. To investigate water use efficiency, on-the-go sensing technology was used to reveal soil spatial variability relevant to water holding capacity (in this example, field elevation and apparent electrical conductivity). These high-density data layers were used to identify strategic sites where monitoring water availabil... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson |
5. Evaluation Of Yield Maps Using Fuzzy IndicatorsThe ultimate goal of application of yield maps is profitable crop output in many farming systems. Yield maps are the starting point in the precision farming system, and provide the final record indicating the effectiveness of any management changes. Researches on yield mapping shown, that positions and boundaries of zones with different levels ... E. Krueger shvetsova, D. Kurtener, D. Kurtener, H. Torbert |
6. Assessment Of Climate Variability On Optimal Nitrogen Fertilizer Rates For Precision AgricultureYield response functions... B. Basso, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac |
7. Mapping The Effect Of Food Prices, Productivity And Poverty In The Development Domains Of NigeriaPoverty remains the major obstacle to economic emancipation and achievement of development agenda in Nigeria. Worse still, rising food prices pose a major threat to feeding the teeming population in Nigeria. Declining food production, high population growth, and negative food trade balance combine to worsen the food and poverty situations in Nigeria. We stand on the premise that surging and volatile food prices could have a hardest hit on those who could not afford it –... O.E. Olayide, A.E. Ikpi, V.O. Okoruwa, , T. Alabi, T. Omodele |
8. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral SignaturesEarly recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga |
9. Decision Making And Operational PlanningIn order to automatize crop farming and its processes, a number of technological and other problems have to be solved. Agricultural field robots are in our vision to fulfill operations in fields. Robots involve number of technological challenges in order to be functional and reliable, but also systems controlling these robots are to be developed. In this paper automatic crop farming is the vision, and decision making models and operational planning is discussed. Study is carried out with simu... T. Oksanen, , |
10. Wheat Growth Stages Discrimination Using Generalized Fourier Descriptors In Pattern Recognition Context... F. Cointault, A. Marin, L. Journaux, J. Miteran, R. Martin |
11. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton ProductionCrop models simulate growth and development, and provide relevant information for the routine management of the crop. The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global p... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller |
12. Mapping Soil Salinity Using Cokriging Method In Arsanjan Plain, Southern IranSalt-affected landscapes are highly sensitive to changes in climatic, edaphic and hydrological conditions in time and space in semi-arid regions such as Arsanjan plain, southern Iran. The objective of this study was to combine digital satellite data with ground based measurements of ECe by cokriging method to possibility improve the soil salinity maps of study area. Soil samples in the 85 sampling site (10187 ha)were collected from 0-30 cm depths, georefrenced using GPS recei... M.P. Baghernejad, M.M. Emadi |
13. Accounting For Spatial Correlation Using Radial Smoothers In Statistical Models Used For Developing Variable-rate Treatment PrescriptionsVariable-rate treatment prescriptions for use on commercial farms can be developed from embedded field trials on those farms. Such embedded trials typically involve non-random, high-density sampling schemes that result in large datasets and response variables exhibiting spatial correlation. In order to accurately evaluate the significance of the effects of the applied treatments and the measured field characteristics on the response of interest, this spatial correlation must be accounted for ... K.S. Mccarter, E. Burris |
14. Crop Rotation Impacts ‘Temporal Sampling’ Needed For Landscape-defined Management ZonesYield and landscape position are used to delineate management zones, but this approach is confounded by yield’s weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options (e.g. crop rotation) also influence yield stability. Our objective was to build a model that would describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotat... E.M. Pena-yewtukhiw, J. Grove |
15. Extension: Precision Ariculture On The InternetThis session will include an overall description of the new eXtension precision agriculture Web site. eXtension is an interactive learning environment delivering the best, most researched knowledge from land-grant university across America. Session participants will learn about the Website, and how to participate in the continued site development. The precision agriculture eXtension Web site is a virtual platform for engage... J. Nowatzki, T. Brase |
16. Not Possible In Real Life: Precision Agriculture’s Future In 3D Virtual WorldsImmersive 3D virtual worlds may be several years away from mainstream adoption, but thousands of scientists, educators, and visionary thinkers are already using these environments to network with colleagues, conduct research, create engaging simulations, and develop instructional models that can reach global audiences. Virtual reality offers the potential to create dynamic content that is either not possible to build in real life, or prohibitively expensive. Travel costs can be reduced by bri... L. Phillips |
17. The Scholarship Of eXtensioneXtension (www.extension.org) is an interactive on-line learning environment delivering "best of the best," researched-based knowledge from the top minds across the land-grant university system. It is a space where university content providers can collaborate to gather and produce new educational and information resources on wide-ranging topics while continually interacting with their customers to help solve real-life problems in real time. The works of ... M. Lambur |
18. We Want You: Contributing Your Expertise To A Community Of Practice (COP)eXtension Communities of Practice (CoP’s) are online collaborative networks of subject matter experts. Community of Practice as a method are not new, almost everyone has come across one by now, but you may not have realized what you were looking at was a collaborative effort. CoP’s exist on sites like Consumer Reports, in CNET, and many other places where groups of experts work to create the content that populates a website. Communities are self-... A. Hays |
19. Site Specific Costs Concerning Machine Path OrientationComputer algorithms have been created to simulate in advance the orientation/pattern of a machine operation on a field. Undesired impacts were obtained and quantified for these simulations, like: maneuvering and overlap of inputs in headlands; servicing of secondary units; and soil loss by water erosion. While the efforts could minimize the overall costs, they disregard the fact that these costs aren’t uniformly distributed over irregular fields. The cost of a non-productive machine pro... M. Spekken, J.P. Molin, T.L. Romanelli, M.N. Ferraz |
20. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision AgricultureAgriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in te... C. Lundström, J. Lindblom |
21. Comparing Adapt-N to Static N Recommendation Approaches for US Maize ProductionLarge temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses. Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune |
22. Data Normalization Methods for Definition of Management ZonesThe use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evalua... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi |
23. EZZone - An Online Tool for Delineating Management ZonesManagement zones are a pillar of Precision Agriculture research. Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions. The use of Geographic Information Systems for agricultural management is common, especially with management zones. Although many algorithms have been produced in research settings, no online software for management zone delineation exists. This research used a ... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos |
24. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian AgricultureWith the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with bett... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek |
25. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the NetherlandsPrecision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traff... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten |
26. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, BrazilIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphi... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto |
27. On Farm Studies to Determine Seeding Rate in CornSeeding rate (SDR) is one of the most critical production practices impacting productivity and economic return for corn (Zea mays L.) By changing SDRs in different zones within a field, herein termed as site-specific management, better economic results can be produced as the outcome of reducing SDRs in low productivity areas and increasing SDRs under high-yielding environments, relative to the uniform SDR management performed by the producer. The aim of this study was to analyze yield respons... G. Balboa, S. Varela, I. Ciampitti, S. Duncan, T. Maxwell, D. Shoups, A. Sharda |
28. Closing Yield Gaps with GxExM and Precision AgricultureThere are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate. A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges. The yield gap –defined as the difference between current farmer yields and pote... C. Walthall, J. Hatfield, S. Schneider, M. Vigil |
29. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, IranDrone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitativ... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali |
30. Treetop Tech: Uplifting German Foresters' Drone Perspectives Through the Technology Acceptance ModelForests play a key role in nature as they purify water, stabilize soil, cycle nutrients, store carbon and also provide habitats for wildlife. Economically, forest product industries provide jobs and economic wealth. Sustainable forest management and planning requires foresters’ understanding of the forests dynamics for which the collection of field data is necessary, which can be time consuming and expensive. Unmanned aerial vehicles or drones can improve the efficiency of tradition acq... M. Michels, H. Wever, O. Mußhoff |
31. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase IntentionsClimate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, t... M. Michels, V. Bonke, H. Wever, O. Mußhoff |
32. Finnish Future Farm Speeding Up the Uptake of Precision AgricultureThe Finnish Future Farm (FFF) is an innovative concept that seamlessly integrates a physical Smart Farm with a Digital Twin, complemented by educational programs and business development opportunities. This holistic approach aims to propel the evolution of Smart Agriculture in Finland. At its core, FFF is a platform for co-creation with a strong emphasis on User-Centered Design. It employs a Multi-Actor Approach, bringing together companies, experts, researchers, and end users to co... H.E. Haapala |
33. Global Adoption of Precision Agriculture: an Update on Trends and Emerging TechnologiesThe adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial i... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics |
34. R2B2 Project: Design and Construction of a Low-cost and Efficient Autonomous UGV For Row Crop MonitoringDriving the adoption of agricultural technological advancements like Unmanned Ground Vehicles (UGVs) by small-scale farmers (SSFs) is a major concern for researchers and agricultural organizations. They aim for the adoption of precision farming (PF) by SSFs to increase crop yield to meet the increasing demand for food due to population growth. In the United States, the cost of purchasing and maintaining rugged UGVs capable of precision agricultural operations stands as a barrier to the a... J.O. Kemeshi, S. Gummi, Y. Chang |
35. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management NebraskaA statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%), intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies. ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti |
36. Bio-Effectors As a Promising Tool for Precision Agriculture and Integrated Plant NutritionBio-effectors, such as microorganisms and active natural compounds, are of increasing interest as promising alternatives or substitutes to precarious agrochemicals. European and global markets (valued at 14.6 billion US$ in 2023) for agricultural biologicals (bio-pesticides, bio-fertilizers, and bio-stimulants) are predicted to grow at rates of more than 13.5 % per year. Improved availability and use efficiency of mineral nutrients, tolerance to abiotic stresses, yield and quality traits, as ... M. Weinmann, M. Nkebiwe, N. Weber, K. Bradacova, N. Morad-talab, U. Ludewig, T. Müller, G. Neumann, M. Raupp, K. Bradacova |
37. Who Are the Data Stewards: Moving Data Driven Agriculture ForwardNearly a decade ago agricultural equipment manufacturers, service providers, retailers, land grant universities, and grower organizations came together to begin discussing the growing needs for producers to manage their farm data. This discussion was partly fueled by the industry shifting from moving data via physical media to cloud API connections. Several initiatives including the Agricultural Data Coalition (ADC) were subsequently launched focusing on addressing data privacy and security c... B.E. Craker, D. Bierman |
38. Comparing Global Shutter and Rolling Shutter Cameras for Image Data Collection in Motion on a UGVIn a bid to drive the adoption of precision farming (PF) technology by reducing the cost of developing an Unmanned Ground Vehicle (UGV), during the Reduction-To-Below-Two grand (R2B2) project we compared Arducam’s AR0234, a global shutter camera (GSC) to their IMX462, a rolling shutter camera (RSC). Since the cost of the AR0234 is approximately three times the price of the IMX462, the comparison was done to determine the possibility of using the latter for image data collection in place... J.O. Kemeshi, Y. Chang, P.K. Yadav, M. Alahe |
39. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about syne... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |
40. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm ManagementOn-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflo... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel |
41. Decision Making Factors of Precision Agricultural Practices in South DakotaA survey among South Dakota Farmers was conducted to document current nutrient management practices. The survey included questions regarding adoption and use of precision ag technologies in addition to information considered to create prescription maps for variable fertilizer and seeding rates. The survey collected demographic information from the producers. The presentation will also highlight how farm size, farm location, farmer/decision maker’s age and/or education level in... P. Kovacs, J. Clark, J. Schad, E. Avemegah |