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| Filter results11 paper(s) found. |
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1. 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 370-800... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga |
2. Evaluation And Contrast Of An Auto Guidance System Operating On A Sugar Cane Harvester In BrazilThe change on the harvesting sugar cane operation from the manual to mechanized cut increased the amount of sugar cane cut by the mill per day, but the operation increased the cane loss, which is left behind on the field. The purpose of this work was to contrast the accuracy achieved... F. Baio |
3. Interaction Between Air Spray Drift And Climatic Conditions Creating Drift Map Related To The Aerial Application Of Pesticides Using Low Volumes In BrazilBetween 30 to 50% of the pesticides total applied over agricultural areas can be lost by the air, depending of the applying conditions, by the spray drift action. This spray drift problem is increased when the field is too close to the urban locations, bringing environmental contamination, and when the application is made with oil on the tank mixture. The society demands by... F. Baio, U. Antuniassi |
4. Computer Model By A Linear Program And Via Internet To Select Agricultural Mechanized Systems Based On The Smallest Operational CostComputer programs have been used to help the farmers on the fleet selection. However, these computing models are based on the previous choice of the mechanized system made by the user. On this context, the purpose of this work was to develop a free computer model by a linear program and via internet to select agricultural mechanized systems based... F. Baio, , |
5. A Case Study For Variable-rate Seeding Of Corn And Cotton In The Tennessee Valley Of AlabamaFarmers have recently become more interested in implementing variable-rate seeding of corn and cotton in Alabama due to increasing seed costs and the potential to maximize yields site-specifically due to inherent field variability. Therefore, an on-farm case study was conducted to evaluate the feasibility of variable-rate seeding for a corn and cotton rotation. ... S.H. Norwood, J.P. Fulton, A.T. Winstead, J.N. Shaw, D. Rodekohr, C.J. Brodbeck, T. Macy |
6. Stable Isotope N-15 as Precision Technique to Investigate Elemental Sulfur Effects on Fertilizer Nitrogen Use Efficiency of Corn Grown in Calcareous Sandy Soils... A.A. Soaud, .M. Rahman, F.H. Al darwish |
7. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance SpectraSuccessful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and Memory... A. Gholizadeh, M. Saberioon, L. Borůvka |
8. 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 |
9. 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 nitrogen... O.S. Walsh, K. Belmont, J. Mcclintick-chess |
10. Understanding Temporal and Spatial Variation of Soil Available Nutrients with Satellite Remote SensingSoil available nutrients are the key determinants in crop growth, field stable output and ecological balance. The soil nutrients loss and surplus can strongly influence the stability of field ecological environment and cause unnecessary pollution. Hence, optimizing the status of soil available nutrients status has significant ecological and economic significance. With the advancement of mechanized farming and control technologies, soil available nutrients can be optimize by variable rate fertilization.... J. Meng, H. Fang, Z. Cheng |
11. Potential Benefits of Variable Rate Nitrogen Topdressing Strategy Coupled with Zoning Technique: a Case Study in a Town-scale Rice Production SystemIntegrating remote sensing (RS)-based variable rate nitrogen (N) recommendation (VRNR) algorithms and management zones (MZs) may improve the accuracy and efficiency of site-specific N management. However, its potential benefits for application in commercial rice production systems can hardly be assessed, since it requires to intervene in common agricultural practices and causes certain economic and environmental consequences. Through a machine learning approach, this study aims to comprehensively... J. Zhang, W. Wang, Z. Fu, Q. Cao, Y. Tian, Y. Zhu, W. Cao, X. Liu |