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| Filter results61 paper(s) found. |
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1. Design and Implementation of Virtual Terminal Based On ISO11783 Standard for Agricultural TractorsThe modern agricultural machinery most common use of the embedded electronic and remote sensing technology demands adoption of the Precision Agriculture (PA). One of the common devices is the Virtual Terminal (VT) for tractor. The VT’s functions and terminology are described in the ISO11783 standard. This work presents the control system design and implementation of the VT and some Electronic Control Units (ECU) for agricultural vehicles based on the ISO 11783 standard. The VT developme... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon |
2. Path Generation Method with Steering Rate ConstraintThe practical way to generate a reference path in path tracking is to follow an adjacent swath. However, if the adjacent swath contains sharp turnings, the reference path will eventually contain sharper turn than the tractor is able to follow. This occurs especially in the corner of a field plot when the field is driven around. In the headland, the objective is to minimize the time to reach the next swath. The commonly known method to generate the shortest path between two arbitrary... J. Backman, T. Oksanen, A. Visala |
3. Research on Straight-Line Path Tracking Control Methods in an Agricultural Vehicle Navigation SystemIn the precision agriculture (PA), an agricultural vehicle navigation system is essential and precision of the vehicle path tracking is of great importance in such a system. As straight line operation is the main way of agricultural vehicles on large fields, this paper focuses on the discussion of straight-line path tracking control methods and proposes an agricultural vehicle path tracking algorithm based on the optimal control theory. First, the paper deduces a relative kinematics model of ... T. Li, J. Hu, L. Gao, H. Hu, X. Bai, X. Liu |
4. Pesticide Drift Control with Wireless Sensor NetworksPrecision Agriculture is an agricultural practice that uses technology based on the principle of variability. The geographically referenced data implement the process of agricultural automation so as to dose fertilizers and pesticides. The efficient application of low cost pesticides without contamination the environment is an agricultural production challenge. The main effect to be avoided during application is pesticide drift. To minimize it is important to know the environmental conditions... C.E. Cugnasca, I.M. Santos |
5. The Ultimate Soil Survey in One Pass: Soil Texture, Organic Matter, pH, Elevation, Slope, and CurvatureThe goal of accurately mapping soil variability preceded GPS-aided agriculture, and has been a challenging aspect of precision agriculture since its inception. Many studies have found the range of spatial dependence is shorter than the distances used in most grid sampling. Other studies have examined variability within government soil surveys and concluded that they have limited utility in many precision applications. Proximal soil sensing has long been envisioned as a metho... E. Lund, C. Maxton, G. Kweon |
6. Path Tracking Control of Tractors and Steerable Towed Implements Based On Kinematic and Dynamic Modelingrecise path tracking control of tractors became the enabling technology for automation of field work in recent years. More and more sophisticated control systems for tractors however revealed that exact positioning of the actual implement is equally or even more important. Especially sloped and curved terrain, strip till fields, buried drip irrigation tapes and high-value crop... G. Kormann, S. Mueller, R. Werner |
7. Use of Active Crop Canopy Reflectance Sensor for Nitrogen Sugarcane FertilizationResearches about the use of ground-based canopy reflectance sensors aiming the nitrogen management fertilization on variable-rate over the sugarcane crop have been conducted in São Paulo, Brazil since 2007. Sugarcane response to nitrogen is variable, making difficult the development of models to estimate its d... L.R. Amaral, G. Portz, H. Rosa, J. Molin |
8. Mapping the Leaf Area Index In Vineyard Using a Ground-Based LIDAR ScannerThe leaf area index (LAI) is defined as the one-sided leaf area per unit ground area and is probably the most widely used index to characterize grapevine vigour. However, direct LAI measurement requires the use of destructive leaves sampling methods which are costly and time-consuming and so are other indirect methods. Faced with these techniques, vineyard leaf area can be indirectly estimated using ground-based LIDAR sensors that scan the vines and get information about the geometry and/or s... J. Arno, I. Del moral, A. Escolà, J. Company, J.A. MartÍnez-casasnovas, J. Masip, R. Sanz, J.R. Rosell |
9. Testing The Author Sequence - FinalizeThis is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla |
10. Improvement of the Quality of “On-The-Go” Recorded Soil pHAn important basis for lime fertilisation is the recording of pH values. Many studies have shown that the pH value can vary greatly within a small area. Only through the development of a sensor by VERIS has it become possible to determine the pH value cheaply in a much higher sampling density than with the time and cost intensive laboratory method. With respect to their measurement principles, both methods differ fundamentally in that in the laboratory method an extraction medium is used. Thi... M. Schneider, T. Leithold, P. Wagner |
11. Optimizing Path Planning By Avoiding Short Corner Tracks... J.P. Molin, M. Spekken |
12. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on SugarcaneAmong the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply i... L.R. Amaral, J.P. Molin, L. Taubinger |
13. Nineteen-Soil-Parameter Calibration Models and Mapping for Upland Fields Using the Real-Time Soil SensorIn precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for soil management, crop quality control using fertilizer, manure and compost, and variable-rate input for s... S. Shibusawa, K. Ninomiya, M. Kodaira |
14. Impact of Nitrogen (N) Fertilization on the Reflectance of Cotton Plants at Different Spatial ScalesThis study was conducted to examine the reflectance of cotton plants measured at three different spatial scales: individual leaf, canopy, and scene, in relation to N treatment effects, and consequently to select the best spatial scale(s) for estimating chlorophyll or N contents. At the leaf scale, N treatments effects were most apparent at 550... S. Maas, F. Muharam |
15. A Remote Interface for a Human-Robot Cooperative Vineyard Sprayer... Y. Edan, R. Berenstein, I. Ben-halevi |
16. Improvement Precision Agricultural Communication Schema agroXML Based on Multi-Agents System's Deliberation and Decision Making Processes... A. Pentjuðs, A. Gailums |
17. Temporal N Status Evaluation Using Hyperspectral Vegetation Indices in a Potato CropThe amount and timing of nitrogen (N) fertilization represents a leading issue in precision agriculture, especially for potato (Solanum tuberosum L.) crop since N is an essential element for plant growth and tuber yield. Therefore, the ability to assess in-season crop N status from non-destructive methods such as proximal sensing is a promising alternative to optimize N f... A. Cambouris, K. Chokmani, T. Morier |
18. Integrated Crop Canopy Sensing System for Spatial Analysis of In-Season Crop PerformanceOver the past decade, the relationships between leaf color, chlorophyll content, nitrogen supply, biomass and grain yield of agronomic crops have been studied wi... L. Shiratsuchi, C.C. Lutz, R.B. Ferguson, V.I. Adamchuk |
19. Architecture and Model of Data Integration between Management Systems and Agricultural Machines for Precision AgricultureThe development of robotic systems has challenges as the high degree of interdisciplinarity, the difficulty of integration between the various robotic contro... R. Dutra, R. Sousa, A. Porto, R. Inamasu, W. Lopes, M. Tronco |
20. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten |
21. Estimating Soil Quality Indicators with Diffuse Reflectance SpectroscopyKnowledge of within-field spatial variability in soil quality indicators is important to assess the impact of site-specific management on the soil. Standard methods for measuring these properties require considerable time and expense, so sensor-based approaches would b... R.J. Kremer, N.R. Kitchen, K.A. Sudduth, D.B. Myers |
22. Compatible ISOBUS Applications Using a Computational Tool for Support the Phases of the Precision Agriculture Cycle... W.C. Lopes, G. Domingues, R.V. Sousa, A.J. Porto, R.Y. Inamasu, R.R. Pereira |
23. Evaluation of the Sensor Suite for Detection of Plant Water Stress in Orchard and Vineyard CropsA mobile sensor suite was developed and evaluated to predict plant water status by measuring the leaf temperature of nut trees and grapevines. It consists of an infrared thermometer to measure leaf temperature along with relevant ambient condition sensors to measure microclimatic variables in the vicinity of the leaf. Sensor suite was successfully evaluated in three crops (almonds, walnuts and grapevines) for both sunlit and shaded leaves. Stepwise linear regression models developed for ... R. Dhillon, V. Udompetaikul, F. Rojo, S. Upadhyaya, D. Slaughter, B. lampinen, K. Shackel |
24. Proximal Sensing Tools to Estimate Pasture Quality Parameters.To date systems for estimating pasture quality have relied on destructive sampling with measurement completed in a laboratory which was very time consuming and expensive. Results were often not received until after the pasture was grazed which defeated the point of the measurement, as farmers required the information to make decisions about grazing strategies to e... R. Pullanagari, I. Yule, M. Tuohy, M. Hedley, W. King, . Dynes |
25. Performance of Two Active Canopy Sensors for Estimating Winter Wheat Nitrogen Status in North China Plain... Q. Cao, Y. Miao, G. Feng, X. Gao, B. Liu, R. Khosla |
26. Different Leaf Sensing Approaches for the Estimation of Winter Wheat Nitrogen StatusNondestructive real time diagnosis of crop N status is crucial to the development of precision nitrogen (N) management strategies. Chlorophyll meter has been a popular sensor for such purposes and different approaches to use this sensor has been developed using a threshold value, nitrogen sufficiency index (NSI) or ratio ... B. Liu, Y. Miao, G. Feng, S. Yue, F. Li, X. Gao |
27. Assessing Water Status in Wheat under Field Conditions Using Laser-Induced Chlorophyll Fluorescence and Hyperspectral MeasurementsClassical measurements for estimating water status in plants using oven drying or pressure chambers are tedious and time-consuming. In the field, changes in radiation conditions may further influence the measurements and thus requir... S. El-sayed, U. Schmidhalter, B. Mistele |
28. Development of a PWM Precision Spraying System for Unmanned HelicopterApplication of protection materials is a crucial component in the high productivity of agriculture. Motivated by the needs of aerial precision application, in this paper we present a pulse width modulation (PWM) based precision spraying system for unmanned helicopter. The system is composed of the tank, pipelines, pump, nozzles and the automatic control unit. The system can spray with a constant rate automatically when the speed of the UAV fluctuates between 1 m/s to 8 m/s. The application ra... R. Zhang, L. Chen, T. Yi, Y. Guo, H. Zhang |
29. Use of Unmanned Aerial Vehicles to Inform Herbicide Drift AnalysisA primary advantage of unmanned aerial vehicle-based imaging systems is responsiveness. Herbicide drift events require prompt attention from a flexible collection system, making unmanned aerial vehicles a good option for drift analysis. In April 2015, a drift event was documented on a Mississippi farm. A combination of corn and rice fields exhibited symptomology consist with non-target injury from a tank mix of glyphosate and clethodim. An interesting observation was t... J.M. Prince czarnecki, D.B. Reynolds, R.J. Moorhead |
30. Plant Stand Count and Corn Crop Density Assessment Using Texture Analysis on Visible Imagery Collected Using Unmanned Aerial VehiclesEnsuring successful corn farming requires an effective monitoring program to collect information about stand counts at an early stage of growth and plant damages due to natural calamities, farming equipment, hogs, deer and other animals. These monitoring programs not only provide a yield estimate but also help farmers and insurance companies in assessing the causes of damages. Current field-based assessment methods are labor intensive, costly, and provide very limited information. Manual asse... S. Samiappan, B. Henry, R.J. Moorhead, M.W. Hock |
31. Privacy Issues and the Use of UASs/Drones in MarylandAccording to the Federal Aviation Administration (FAA), the lawful use of Unmanned Aerial Vehicles (UAV), also known as Unmanned Aircraft Systems (UAS), or more commonly as drones, are currently limited to military, research, and recreational applications. Under the FAA’s view, commercial uses of drones are illegal unless approved by the Federal government. This will change in the future. Congress authorized the FAA to develop regulations for the use of drones by priva... P. Goeringer, A. Ellixson, J. Moyle |
32. Multispectral Imaging and Elevation Mapping from an Unmanned Aerial System for Precision Agriculture ApplicationsAs the world population continues to grow, the need for efficient agricultural production becomes more pressing. The majority of farmers still use manual techniques (e.g. visual inspection) to assess the status of their crops, which is tedious and subjective. This paper examines an operational and analytical workflow to incorporate unmanned aerial systems (UAS) into the process of surveying and assessing crop health. The proposed system has the potential to significantly red... C. Lum, M. Dunbabin, C. Shaw-feather, M. Mackenzie, E. Luker |
33. Weather Impacts on UAV Flight Availability for Agricultural Purposes in OklahomaThis research project analyzed 21 years of historical weather data from the Oklahoma Mesonet system. The data examined the practicality of flying unmanned aircraft for various agricultural purposes in Oklahoma. Fixed-wing and rotary wing (quad copter, octocopter) flight parameters were determined and their performance envelope was verified as a function of weather conditions. The project explored Oklahoma’s Mesonet data in order to find days that are acceptable for fly... P. Weckler, C. Morris, B. Arnall, P. Alderman, J. Kidd, A. Sutherland |
34. Safety and Certification Considerations for Expanding the Use of UAS in Precision AgricultureThe agricultural community is actively engaged in adopting new technologies such as unmanned aircraft systems (UAS) to help assess the condition of crops and develop appropriate treatment plans. In the United States, agricultural use of UAS has largely been limited to small UAS, generally weighing less than 55 lb and operating within the line of sight of a remote pilot. A variety of small UAS are being used to monitor and map crops, while only a few are being used to apply agricul... H. Verstynen, K. Hayhurst, J. Maddalon, N. Neogi |
35. Early Detection of Nitrogen Deficiency in Corn Using High Resolution Remote Sensing and Computer VisionThe continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the detection and characterization of Nitrogen (N) deficiencies in corn fields. Current methods of field surveillance are either completed manually or with the assistance of satellite imaging, which of... D. Mulla, D. Zermas, D. Kaiser, M. Bazakos, N. Papanikolopoulos, P. Stanitsas, V. Morellas |
36. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote SensingActive crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing sys... J. Lu, Y. Miao, Y. Huang, W. Shi |
37. Developing UAV Image Acquisition System and Processing Steps for Quantitative Use of the Data in Precision AgricultureMapping natural variability of crops and land is first step of the management cycle in terms of crop production. Several methods have been developed and engaged for data recording and analyzing that generate prescription maps such as yield monitoring, soil mapping, remote sensing etc. Although conventional remote sensing by capturing images via satellites has been very popular tool to monitor the earth surface, it has several drawbacks such as orbital period, unattended capture, investment co... A. Tekin, M. Fornale |
38. Towards Calibrated Vegetation Indices from UAS-derived OrthomosaicsCrop advisors and farmers increasingly use drone data as part of their decision making. However, the vast majority of UAS-based vegetation mapping services support only the calculation of a relative NDVI derived from compressed JPEG pixel values and do not include the possibility to include more complex aspects like soil correction. In our ICPA12 contribution, we demonstrated the effects and consequences of the above shortcomings. Here, we present the stepwise development of a solution to ens... K. Pauly |
39. Large-scale UAS Data Collection, Processing and Management for Field Crop ManagementNorth Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twic... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin |
40. Small UAS Integrated Sensing Tools for Abiotic Stress Monitoring in Irrigated Pinto BeansPrecision agriculture is a practical approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of specific and high resolution crop data at critical growth stages is a key for real-time data driven decision support for precision agriculture management during the production season. The goal of this study was to evaluate the feasibility of using small unmanned aerial system (UAS) integrated remote sensing tools to monitor the abiotic stress of eight i... L. Khot, J. Zhou, R. Boydston, P.N. Miklas, L. Porter |
41. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera SystemThe COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitor... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens |
42. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in CornRemotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia |
43. Seeding and Planting Plots for Crop Performance Evaluation Using Gps-rtk Auto SteeringCrop performance evaluation plots are seeded both on and off the University of Nebraska West Central Research and Extension Center. Plots off the Center must match the producer’s rows for pesticide application, cultivation, ditching, irrigation, fertilization and any other operations performed in the fields. With row crops the producer blank-plants the plot area before we can follow up with planting the plots. This means that we have to wait for the producer to plant in the field. Blank... R.N. Klein, J.A. Golus, A.S. Cox |
44. Use of Farmer’s Experience for Management Zones DelineationIn the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this s... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães |
45. Supporting and Analysing On-Farm Nitrogen Tramline Trials So Farmers, Industry, Agronomists and Scientists Can LearN TogetherNitrogen fertilizer decisions are considered important for the agronomic, economic and environmental performance of cereal crop production. Despite good recommendation systems large unpredicted variation exists in measured N requirements. There may be fields and farms that are consistently receiving too much or too little N fertilizer, therefore losing substantial profit from wasted fertilizer or lost yield. Precision farming technologies can enable farmers (& researchers) to test appropr... D. Kindred, R. Sylvester-bradley, S. Clarke, S. Roques, D. Hatley, B. Marchant |
46. An On-farm Experimental Philosophy for Farmer-centric Digital InnovationIn this paper, we review learnings gained from early On-Farm Experiments (OFE) conducted in the broadacre Australian grain industry from the 1990s to the present day. Although the initiative was originally centered around the possibilities of new data and analytics in precision agriculture, we discovered that OFEs could represent a platform for engaging farmers around digital technologies and innovation. Insight from interacting closely with farmers and advisors leads us to argue for a change... S. Cook, M. Lacoste, F. Evans, M. Ridout, M. Gibberd, T. Oberthur |
47. Evaluation of Strip Tillage Systems in Maize Production in HungaryStrip tillage is a form of conservation tillage system. It combines the benefits of conventional tillage systems with the soil-protecting advantages of no-tillage. The tillage zone is typically 0.25 to 0.3 m wide and 0.25 to 0.30 m deep. The soil surface between these strips is left undisturbed and the residue from the previous crop remain on the soil surface. The residue-covered area reaches 60-70%. Keeping residue on the surface helps prevent soil structure and reduce water loss from the so... T. Rátonyi, P. Ragán, D. Sulyok, J. Nagy, E. Harsányi, A. Vántus, N. Csatári |
48. Delineation of 'Management Classes' Within Non-Irrigated Maize Fields Using Readily Available Reflectance Data and Their Correspondence to Spatial Yield VariationMaize is grown predominantly for silage or gain in North Island, New Zealand. Precision agriculture allows management of spatially variable paddocks by variably applying crop inputs tailored to distinctive potential-yield limiting areas of the paddock, known as management zones. However, uptake of precision agriculture among in New Zealand maize growers is slow and limited, largely due to lack of data, technical expertise and evidence of financial benefits. Reflectance data of satellite and a... D.C. Ekanayake, J. Owens, A. Werner, A. Holmes |
49. Improving Yield Prediction Accuracy Using Energy Balance Trial, On-the-Go and Remote Sensing ProcedureOur long term experience in the ~23.5 ha research field since 2001 shows that decision support requires complex databases from each management zone within that field (eg. soil physical and chemical parameters, technological, phenological and meteorological data). In the absence of PA sustainable biomass production cannot be achieved. The size of management zones will be ever smaller. Consequently, the on the go and remote sensing data collection should be preferred. ... A. Nyéki , G. Milics, A.J. Kovács, M. Neményi, I. Kulmány, S. Zsebő |
50. Variety Effects on Cotton Yield Monitor CalibrationWhile modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replic... E. Vories, A. Jones, G. Stevens, C. Meeks |
51. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management str... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus |
52. Draft Privacy Guidelines and Proposal Outline to Create a Field-Scale Trial Data Repository for Data Collected by On-Farm NetworksImplementing better management practices in corn and soybeans that increase profitability and reduce pollution caused by the practices requires large numbers of field-scale, replicated trials. Numerous complex and often unmeasurable interactions among the environment, genetics and management at the field scale require large numbers of trials completed at the field scale in a systematic and uniform manner to enable calculation of probabilities that a practice will be an improvement compared wi... T. Morris, N. Tremblay |
53. An Economic-Theory-Based Approach to Management Zone DelineationIn both the academic and popular literatures on precision agriculture technology, a management zoneis generally defined as an area in a field within which the optimal input application strategy is spatially uniform. The characteristics commonly chosen to delineate management zones, both in the literature and in commercial practice, are yield and variables associated with yield. But microeconomic theory makes clear that economically optimal input application strategi... B. Edge |
54. Influence of Planter Downforce Setting and Ground Speed on Seeding Depth and Plant Spacing Uniformity of CornUniform seed placement improves seed-to-soil contact and requires proper selection of downforce control across varying field conditions. At faster ground speeds, downforce changes and it becomes critical to select the level of planter downforce settings to achieve the desired consistency of seed placement during planting. The objective of this study was to assess the effect of ground speed and downforce setting on seeding depth and plant spacing and to evaluate the relationship of ground spee... A. Sharda, S. Badua, I. Ciampitti, R. Strasser, T.W. Griffin |
55. Investigate the Optimal Plot Length in On-Farm TrialsAgronomic researchers have recently begun running large-scale, on-farm field trials that employ new technologies that enable us to conduct hundreds of farm trials all over the world and, by extension, rigorous quantitative and data-centered analysis. The large-scale, on-farm trials follow traditional small-plot trials where the fields are divided into plots, and different treatments are randomly assigned to each plot. Over the past two years, researchers have been designing trials with ... A. Gong |
56. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision AgriculturePrecision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protei... J. Sheppard, A. Peerlinck, B. Maxwell |
57. Can Unreplicated Strip Trials Be Used in Precision On-Farm Experiments?On-farm experiments are used to evaluate a wide variety of products ranging from pesticide and fertilizer rates to the installation of tile drainage. The experimental design for these experiments is usually replicated strip trials. Replication of strip trials is used to estimate experimental error, which is the basis for judging statistical significance of treatment effects. Another consideration for using strip trials is greater within-field variability than smaller fields us... G. Hatfield, G. Reicks, E. Carter |
58. eFields – An On-Farm Research Network to Inform Farm RecommendationsOn-farm research has been traditionally used to provide local, field-scale information about agronomic practices. Farmers tend to have more confidence in on-farm research results because they are perceived to be more relevant to their farm operations compared to small plot research results. In recent years, more farmers have been conducting on-farm studies to help evaluate practices and input decisions. Recent advances in precision agriculture technologies have stream-lined the on-... J.P. Fulton, E. Hawkins, R. Colley iii, K. Port, S. Shearer, A. Klopfenstein |
59. The Effect of Slope Gradient on the Modelling of Soil Carbon Dioxide Emissions in Different Tillage Systems at a Farm Using Precision Tillage Technology in HungaryUnderstanding the role of natural drivers in greenhouse gas (GHG) emitted by agricultural soils is crucial because it contributes to selecting and adapting acceptable eco-friendly farming practices. Hence, Syngenta Ltd. collaborating with researchers, aimed to investigate the effect of two tillage treatments, conventional-tillage (CT) and minimum-tillage (MT) on soil carbon dioxide (CO2) emissions. The research field is in Hungary. Soil columns were derived from different tillage s... I.M. Kulmany, S. Benke, L. Bede, R. Pecze, V. Vona |
60. Ecological Refugia As a Precision Conservation Practice in Agricultural SystemsCurrent global agriculture fails to meet the basic food needs of 687.7 million people. At the same time, our food system is responsible for catastrophic losses of biodiversity. Precision conservation solutions offer the potential to benefit both production systems and natural systems. Transforming low-producing areas on farm fields into ecological refugia may provide small-scale habitat and ecosystem services in fragmented agricultural landscapes. We collaborated with three precision agricult... H. Duff, B. Maxwell |
61. Analysis of the Mapping Results Using SoilOptix TM Technology in Chile After Two SeasonsSoil mapping is a key element to successfully implement Integrated Nutrient Management (INM) in high value crops. SoilOptixTM is a mapping service based on the use of gamma radiation technology that arrived in Chile in 2019. Since then, around 2000 ha have been mapped, mainly in fruit orchards and vineyards. The technology has demonstrated its value in determining the most limiting factors in new and old orchards, and the possibility of correcting them in a site-spe... R.A. Ortega, A.F. Ortega, M.C. Orellana |