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1. Beyond NDVI - Additional Benefits of RapidEye Image Products... U. Schulthess, K. Schelling |
2. The Map - Supported by New NPK-Sensors - is Intelligent, Not the TractorDI Walter H. Mayer PROGIS Software GmbH Postgasse 6, A-9500 Villach www.progis.com office@progis.com +43 4242 26332 WinGIS®-AGROffice® and BING®-maps: Since years PROGIS has been developing an object oriented GIS (WinGIS®), agriculture and forestry applications for single enterprises, for advisors, for the chain management including logistics and communication implementation with mobile GIS (mobG... W. Mayer |
3. An Approach to Selection of Soil Water Content Monitoring Locations within FieldsIncreased input efficiency is one of the main challenges for a modern agricultural enterprise. One way to optimize production cycles is to rationalize crop residue utilization. In conditions where there is limited use of mineral fertilizers and without applying manure, plant residues may be used as an organic fertilizer ... V.I. Adamchuk, L. Pan, R.B. Ferguson |
4. The Use of Crop Sensors Beyond Nitrogen and Improving the Right to Farm... C. Mackenzie |
5. John Deere FarmSight™Agriculture has had several revolutions in the past century, and it currently faces what may be its greatest challenge to date – population growth and the increased need for food, fiber, and fuel in the future. To meet this challenge the agricultural industry will have to drive efficiencies to a level never seen before, within a context of several macro trends (e.g., farm sizes increasing, environmental sustainability requirements evolving). John Deere FarmSightTM... M. Stelford |
6. AMMO Ag: Agricultural Marketing & Merchandising OptimizerEHedger provides an integrated risk management solution for farm operations utilizing our proprietary AMMO platform combined with proven hedging strategies, first-hand market insight, effective trade execution and farming expertise. AMMO software enables real-time analysis of crop/livestock production. Farmers can set profit margins, evaluate variable profit scenarios, understand production costs and risks, and create sustainable marketing programs to maximize their... C. Krol, D. Dempsey |
7. Real-Time Fluorescence Sensors for Precision Agriculture... J. Ayral |
8. Raven Sponsor Presentation: Slingshot OverviewSlingshot, a suite of products and services centered around high-speed wireless connectivity in the cab ... D. Schwiesow |
9. Precision Agriculture and SpringerMaryse Walsh will be presenting Precision Agriculture, the Springer journal, but also the discipline and its place in the Springer publications overall. The community attending the ICPA has a major role in ensuring the positive development of these publications and the affiliation of the journal to the ISPA will only help. ... M. Walsh |
10. Raising Awareness of the Potential of Crop Sensing Technologies to Improve Environmental StewardshipExtensive research and on-farm work using active crop sensors for input management have been conducted in the Midwest and Great Plain USA with favorable results. Contrasting is the situation in the Southeast where the adoption by farmers is still limited and current on-going research is focused on the main southeastern crops. This presentation will provide an overview of the multiple extension activities related to crop sensing involving farmers, extension agents and crop consultants in ... B. Ortiz |
11. Making the Most of Precision Ag Data: Big Data in Farm Managementna ... T. Griffin |
12. Davco's Journey Into Precision Sugarcane FarmingDavco's Journey Into Precision Sugarcane Farming ... D. Cox |
13. Sensor Algorithms 101This presentation will break down the algorithms used for Optical Sensor Based Nitrogen rate recommendations. The group will walk through the mechanics and agronomics behind the most commonly used equations, in order to turn the black boxes into slightly muddied waters. ... B. Arnall |
14. Use of Zone or Grid Soil Nutrient Management as Part of an Integrated Site-specific Nutrient StrategyZone and grid sampling are used as a basis for fertilizing with nutrients site-specifically. Use of sensors to assist in-season management of nitrogen is also gaining momentum. The presentation will suggest when grid or zone sampling for preplant nutrients might be utilized and how these recommendations would be used in an integrated approach of preplant plus in-season nutrient management. ... D. Franzen |
15. A Five Year Study Of Variable Rate Fertilization In CitrusCitrus is a major crops in Brazil, especially in the São Paulo state, which is the main citrus production region in the world. Yet, site specific technology is still in early stages of adoption. Variable rate application of inputs is the most important tool in a Precision Agriculture system, however its effect on citrus agronomical aspects are still unknown, especially during long periods of observation. Thus, variable rate fertilizer application has been tested in citrus... J.P. Molin, A.F. Colaço |
16. A Precise Fruit Inspection System for Huanglongbing and Other Common Citrus Defects Using GPU and Deep Learning TechnologiesWorld climate change and extreme weather conditions can generate uncertainties in crop production by increasing plant diseases and having significant impacts on crop yield loss. To enable precision agriculture technology in Florida’s citrus industry, a machine vision system was developed to identify common citrus production problems such as Huanglongbing (HLB), rust mite and wind scar. Objectives of this article were 1) to develop a simultaneous image acquisition system using multiple c... D. Choi, W. Lee, J.K. Schueller, R. Ehsani, F.M. Roka, M.A. Ritenour |
17. Development of a Multiband Sensor for Citrus Black Spot Disease DetectionCitrus black spot (CBS), or Guignardia citricarpa, is known as the most destroying citrus fungal disease worldwide. CBS causes yield loss as a result of early fruit drop, and it leaves severely blemished and unmarketable fruit. While leaves usually remain symptomless, CBS generates various forms of lesions on citrus fruits including hard spot, cracked spot, and virulent spot. CBS lesions often appear on maturing fruit, starting two months before maturity. Warm temperature and sunlight exposur... A. Pourreza, W. Lee, J. Lu, P. Roberts |
18. Sensor-based Technologies for Improving Water and Nitrogen Use EfficiencyLimited reports exist on identifying the empirical relationships between plant nitrogen and water status with hyperspectral reflectance. This project is aiming to develop effective system for nitrogen and water management in wheat. Specifically: 1) To evaluate the effects of nitrogen rates and irrigation treatments on wheat plant growth and yield; 2) To develop methods to predict yield and grain protein content in varying nitrogen and water environments, and to determine the minimum nit... O.S. Walsh, K. Belmont, J. Mcclintick-chess |
19. Development of a Multispectral Sensor for Crop Canopy Temperature MeasurementQuantifying spatial and temporal variability in plant stress has precision agriculture applications in controlling variable rate irrigation and variable rate nutrient application. One approach to plant stress detection is crop canopy temperature measurement by the use of thermographic or radiometric methods, generally in the long wave infrared (LWIR) wavelength range. A confounding factor in LWIR canopy temperature estimation is eliminating the effect of the soil background in the image. One ... P. Drew, K.A. Sudduth, E. Sadler |
20. Prediction of Sugarcane Yields in Commercial Fields by Early Measurements with an Optical Crop Canopy SensorAs a grass (Poaceae), sugarcane needs supplemental mineral nitrogen (N) to achieve high yields on commercial production areas. In Brazil, N recommendations for sugarcane ratoons are based on expected yield and the results of N response trials, as soil N analyses are not a suitable basis for decisions on optimum N fertilizer rates under tropical conditions. Since the vegetative parts in sugarcane are harvested, yield components such as the number of stalks and stalk height are directly correla... G. Portz, J. Jasper, J.P. Molin |
21. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as ... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
22. Active and Passive Crop Canopy Sensors As Tools for Nitrogen Management in CornThe objectives of this research were to (i) assess the correlation between active and passive crop canopy sensors’ vegetation indices at different corn growth stages and (ii) assess sidedress variable rate nitrogen (N) recommendation accuracy of active and passive sensors compared to the agronomic optimum N rate (AONR). The experiment was conducted near Central City, Nebraska on a Novina sandy loam planted to corn on 15 April 2015. The experiment was a randomized complete-block design w... L. Bastos, R. Ferguson |
23. Sensor-based Nitrogen Applications Out-performed Producer-chosen Rates for Corn in On-farm DemonstrationsOptimal nitrogen fertilizer rate for corn can vary substantially within and among fields. Current N management practices do not address this variability. Crop reflectance sensors offer the potential to diagnose crop N need and control N application rates at a fine spatial scale. Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer. Fifty-five replicated on-farm demonstrat... P. Scharf, K. Shannon, K. Sudduth, N. Kitchen |
24. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case StudyWhile on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate cont... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson |
25. Precision Nitrogen Management Based on Nitrogen Removal in Rainfed WheatGrowers of hard red spring wheat may capture price premiums for maximizing the protein concentration of their grain. Nitrogen (N) nutrition adequacy is crucial to achieving high grain protein concentration. The objective of this study was to determine the usefulness of N removal maps by comparing grain protein, yields, and dollar returns obtained from this precision N management approach with that from conventional uniform N management. Strip plot experiments were designed to compare spatiall... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long |
26. Using Pricise Gps/gis Based Barley Yield Maps to Predict Site-specific Phosphorus RequirementsThree fundamental stages and technologies as main parts of a precision farming project should be considered precisely. These are access to actual multi- dimensional variability detail or variable description on farms, creating a suitable variable-rate technology, and finally providing a decision support system. Some results of a long term practical research conducted by the author in Upon-Tyne Newcastle University of UK for reliable yield monitoring and mapping were utilised to prepare this p... A. Sanaei |
27. Seasonal Patterns of Vegetative Indices Over Cropping SystemsRemote sensing of reflectance in the visible and near-infrared portions of the spectrum has been used for agronomic applications for a number of years. The combination of different wavelengths into vegetative indices have proven useful for a variety of applications that range from biomass, leaf area, leaf chlorophyll, yield, crop residue, and crop damage. To help refine our understanding of vegetative indices studies were conducted on corn (Zea mays L.), soybean (Glycine max (L.) Merr.), whea... J.L. Hatfield, J.H. Prueger |
28. Canopy Temperature Mapping with a Vineyard RobotThe wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an ... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves |
29. Agricultural Robots: Drivers, Barriers and Opportunities for AdoptionIn the next decades, agriculture is to feed a rapidly growing population, while tackling changes in climate, overexploited resources, changes in markets and competition with other sectors. Agriculture is, therefore, expected to move towards a more sustainable intensification. In this context, robotic technologies are aimed to reduce labor, using fewer resources and improving agricultural productivity. There is growing demand and awareness of the potential use of such technologies in the farmi... K. Rial-lovera |
30. Design and Analysis of ISO 11783 Task Controller's Functionality in Server - Client ECU for Agricultural VehiclesA modern agricultural vehicle's electronic control units (ECU) communicated based on the ISO 11783 standards. The connection of different machines, implements, different manufacturers into a single bus for the exchange of control commands and sensor data are a challenge for the precision agriculture. One of main functionality is the Task controller in the intelligent monitoring system. The task controller is to log data and assign set-point values for automated work (task) seque... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham |
31. UAV Images As a Source for Retrieval of Machine Tracks and Vegetation Gaps Along Crop RowsThe trend of acquiring equipment and obtaining high resolution remote sensed images by Unmanned Aerial Vehicles (UAV) have been followed by sugarcane producers in Brazil, given its low cost. The images taken from fields have been used for retrieval of information like Digital Terrain Models (DTMs) from stereoscopy of overlapping images and spatial variance of biomass. In sugarcane production, driving deviations occur during planting because of manual steering inaccuracy, sliding of machines s... M. Spekken, J.P. Molin |
32. Economics of Swarm Bot Profitability for Cotton HarvestImproved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row ... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine |
33. High Accuracy Path Tracking for Rice Drill Seeder in Uneven Paddy FieldsHigh accuracy track tracing is a challenging task in paddy fields due to uneven grounds as well as wet soil conditions, thus restricting the development of autonomous rice drill seeder in China. For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven mud paddy fields is introduced in this paper. Combining lateral deviation and heading a... Y. Li, Y. Zhang, X. Liu, C. Liu |
34. Development of a Machine Vision Yield Monitor for Shallot Onion HarvestersCrop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully develop... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller |
35. Computer Vision Techniques Applied to Natural Scenes Recognition and Autonomous Locomotion of Agricultural Mobile RobotsThe use of computer systems in Precision Agriculture (PA) promotes the processes’ automation and its applied tasks, specifically the inspection and analysis of agricultural crops, and guided/autonomous locomotion of mobile robots. In this context, this research aims the application of computer vision techniques for agricultural mobile robot locomotion, settled through an architecture for the acquisition, image processing and analysis, in order to segment, classify and recognize patterns... L.C. Lugli, M.L. Tronco, A.J. Porto |
36. Use of MLP Neural Networks for Sucrose Yield Prediction in SugarbeetINTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation o... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes |
37. You Can Not Manage What You Dont MeasureThe problem of variability in soil nutrient analysis has been studied for years by a number of industry experts; unable to decipher and commercialize hyperspectral soil sensing. Many studies have taken years of testing to account for variability thathas a dramatic impacts on precision of recommendations. The main tradeoff we have identified is between accuracy and precision. Large quantities of raw data are requir... K. Fleming, N. Schottle, P. Nagel, G. Koch |
38. Assessing the Distribution Uniformity of Broadcast-interseeded Cover Crops at Different Crop Stages by an Unmanned Aerial VehicleDrones can now carry larger payloads and have become more affordable, making them a viable option to use for broadcast-interseeding cover crops in the fall, prior to main crop harvest. This strategy has become popular in Ohio over the past two years. However, this new strategy arose quickly with a limited understanding of field performance of the drone’s distribution uniformity under different parameters such as rates, swath widths, speeds, or cash crop type. Therefore, the objective of... A.D. Thomas, J.P. Fulton, S. Khanal, O. Ortez, G. Mcglinch |