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1. Precision Design Of Vegetative BuffersPrecision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, vari... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey |
2. Soil Compaction: Impact Of Tractor And Equipment On Corn Growth, Development And YieldThis project looks at the impact of soil compaction on corn emergence, growth and development, and yield. This is a two-year study, begun in the in the spring of 2013, it will be completed after the 2014 growing season. Corn was produced in the field both years. The project hypotheses are to: 1) Soil compaction does impact corn growth, development and yield; 2) Soil compacted in the fall season by farm equipment is measurable the followin... S. Sivarajan, S. Bajwa, J. Nowatzki |
3. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means MethodsThe generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi |
4. The Influence Of The Interpolation Method In The Management Zones GenerationThe definition of management zones (MZ) allows the concepts of precision agriculture (PA) to be used even in small producers. Methods for defining these MZ were created and are being used, obtaining satisfactory results with different crops and parameters (FLEMING & WESTFALL, 2000; ORTEGA & SANTIBÁÑEZ, 2007; MILANI et al., 2006). Through methodologies, the attributes that are influencing the productivity are selected and thematic maps are generated with the... K. Schenatto, C. Bazzi, V. Bier, E. Souza |
5. Production And Conservation Results From A Decade-Long Field-Scale Precision Agriculture SystemResearch is needed that simultaneously evaluates production and conservation outcomes of precision agriculture practices. From over a decade (1993-2003) of yield and soil mapping and water quality assessment, a multi-faceted, “precision agriculture system” (PAS) was developed and initiated in 2004 on a 36-ha field in Central Missouri. The PAS assessment was accomplished by comparing it to the previous decade of conventional corn-soyb... C. Baffaut, K. Sudduth, J. Sadler, R. Kremer, R. Lerch, N. Kitchen, K. Veum |
6. GIS Mapping of Soil Compaction and Moisture Distribution for Precision Tillage and Irrigation ManagementSoil compaction is one of the forms of physical change of soil structure which has positive and negative effects, in agriculture considered to make soil degradation. The undisciplined use of heavy load traffic or machinery in modern agriculture causes substantial soil compaction, counteracted by soil tillage that loosens the soil. Higher soil bulk densities affect resistance to root penetration, soil pore volume and permeability to air, and thus, finally the pore space habitable... H.P. Jayasuriya, M. Al-wardy, S. Al-adawi, K. Al-hinai |
7. Spatial Variability Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar Land Clay SandyThe assessment of soil compaction levels and choosing the best management system are very important in modern agriculture, aiming to prevent or at least restore their physical conditions to a satisfactory level. The renewal of sugar cane plantation happens on average every 5 or 6 years. The current way repeats a sequence compaction and decompaction events during successive cycles of sugarcane, which promotes breakdown of soil structure. During the harvesting and transportation, ... F.C. Masiero, B.B. Fernandes, S.P. Guerra, K.P. Lanças, I. Marasca |
8. 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 |
9. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry HarvestingWild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the p... K. Esau, Q. Zaman, A. Farooque, A. Schumann |
10. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed wit... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis |
11. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil DataOur hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenou... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi |
12. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape AttributesOne of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity i... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes |
13. Optimal Placement of Proximal Sensors for Precision Irrigation in Tree CropsIn agriculture, use of sensors and controllers to apply only the quantity of water required, where and when it is needed (i.e., precision irrigation), is growing in importance. The goal of this study was to generate relatively homogeneous management zones and determine optimal placement of just a few sensors within each management zone so that reliable estimation of plant water status could be obtained to implement precision irrigation in a 2.0 ha almond orchard located in California, USA. Fi... C.L. Bazzi, K. Schenatto, S. Upadhyaya, F. Rojo |
14. Prediction of Corn Economic Optimum Nitrogen Rate in ArgentinaStatic (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aire... L. Puntel, A. Pagani, S. Archontoulis |
15. Field Test of a Satellite-Based Model for Irrigation Scheduling in CottonCotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table a... O. Beeri, S. May-tal, J. Raz, R. Rud |
16. Variable Selection and Data Clustering Methods for Agricultural Management Zones DelineationDelineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster anal... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto |
17. Field Grown Apple Nursery Tree Plant Counting Based on Small UAS Imagery Derived Elevation MapsIn recent years, growers in the state are transitioning to new high yielding, pest and disease resistant cultivars. Such transition has created high demand for new tree fruit cultivars. Nursery growers have committed their incoming production of the next few years to meet such high demands. Though an opportunity, tree fruit nursery growers must grow and keep the pre-sold quantity of plants to supply the amount promised to the customers. Moreover, to keep the production economical amidst risin... M. Martello, J.J. Quirós, L. Khot |
18. Optimising Nitrogen Use in Cereal Crops Using Site-Specific Management Classes and Crop Reflectance SensorsThe relative cost of Nitrogen (N) fertilisers in a cropping input budget, the 33% Nitrogen use efficiency (NUE) seen in global cereal grain production and the potential environmental costs of over-application are leading to changes in the application rates and timing of N fertiliser. Precision agriculture (PA) provides tools for producers to achieve greater synchrony between N supply and crop N demand. To help achieve these goals this research has explored the use of management classes derive... B. Whelan, M. Fajardo |
19. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor NetworksMobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is ta... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza |
20. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast ChinaThe objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla |
21. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your BenefitsClimate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water f... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet |
22. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in OmanAgriculture under arid environment is always become a challenge due to water scarcity and salinity problems. With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstractio... H. Jayasuriya, A. Al-busaidi, M. Ahmed |
23. Overview and Value of Digital Technologies for North American Soybean ProducersIn the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers. Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies. However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide. The objective of th... J. Lee, J. Fulton, K. Port, R. Colley iii |
24. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer ManagementDetermination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. ... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi |
25. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US MidwestEffective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly acr... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan |