Proceedings
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| Filter results10 paper(s) found. |
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1. Embedded Sensing System To Control Variable Rate Agricultural InputsThis paper presents an embedded sensing system for agricultural machines to collect information about plants and also to control the application of fertilizer with variable rate in corn crop. The Crop Circle reflectance sensor was used with the aim to explore the spectral... G.T. Tangerino, R.V. Sousa, A.J. Porto, R. . Inamasu, P. Pinkston |
2. 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 effectively... R. Pullanagari, I. Yule, M. Tuohy, M. Hedley, W. King, . Dynes |
3. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft SystemsSmall Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infrared... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt |
4. UAV-based Crop Scouting for Precision Nutrient ManagementPrecision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of wheat... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda |
5. Spatial Variability of Soil Nutrients and Precision Nutrient Management for Targeted Yield Levels of Groundnut (Arachis Hypogaea L.)A field study was conducted during rabi / summer 2014-15 to know the spatial variability and precision nutrient management practices on targeted yield levels of groundnut. The experimental field has been delineated into 36 grids of 9 m x 9 m using geospatial technology. Soil samples from 0-15 cm were collected and analysed. Spatial variability exists for available nitrogen, phosphorous and potassium and they varied from 99 to 197 kg N, 12.1 to 64.0 kg P2O5 and 166... H. D.c, S. Dr., N. Dr., M. Giriyappa, S. T |
6. Precision Nutrient Management Through Drip Irrigation in Aerobic RiceA field experiment was conducted during kharif 2015 to asses the spatial variability and precision nutrient management through drip irrigation in aerobic rice at ZARS, GKVK, Bangalore. The experimental field has been delineated into 48 grids of 4.5 m x 4.5 m using geospatial technology. Soil samples from 0-15 cm depth were collected and analysed. There was spatial variability for available nitrogen (154 to 277 kg ha-1), phosphorous (45 to 152 kg ha-1) and potassium... N. Dr., S. T, M. Giriyappa, H. D.c, B. Patil, D. Prabhudeva, G. Kombali, S. Noorasma, M. Thimmegowda |
7. Use of a Cropping System Model for Soil-specific Optimization of Limited WaterIn the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen |
8. Using Drone Based Sensors to Direct Variable-Rate, In-Season, Aerial Nitrogen Application on CornImproving nutrient management on farms is a critical issue nationwide. Applying a portion of N fertilizer during the growing season, alongside the growing corn crop is one way to improve nitrogen management. Sidedress N applications allow the availability of N fertilizer to more closely match the time when the crop is rapidly uptaking N. Additionally, waiting to apply a portion of the N during the growing season allows for management which is responsive to current growing season conditions. Crop... L.J. Thompson |
9. 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) sequences... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham |
10. Observational Studies in Agriculture: Paradigm Shift RequiredThere is a knowledge gap in agriculture. For instance, there is no way to tell with precision what is the outcome of cutting N fertilizer by a quarter on important outcomes such as yield, net return, greenhouse gas emissions or groundwater pollution. Traditionally, the way to generate knowledge in agriculture has been to conduct research with the experimental method where experiments are conducted in a controlled environment with trials replicated in space and... L. Longchamps, B. Panneton, N. Tremblay |