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| Filter results5 paper(s) found. |
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1. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry FieldsAn automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang |
2. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop ProductivitySite-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang |
3. Measuring And Mapping Sugarcane GapsSugarcane is an important crop in tropical regions of the world and especially for Brazil, the largest sugar supplier in the market, also running a domestic fleet of flex-fuel driven vehicles based on ethanol. Site specific production management can impact sugarcane production by increasing yield and reducing cost. Sugarcane fields are planted each five years, in average, and an important parameter that is measured after the planting operation is the gaps caused by problems during planting... J.P. Veiga, D.S. Cavalcante, J.P. Molin |
4. Exploring Tractor Mounted Hyperspectral System Ability to Detect Sudden Death Syndrome Infection and Assess Yield in SoybeanPre-visual detection of crop disease is critical for both food and economic security. The sudden death syndrome (SDS) in soybeans, caused by Fusarium virguliforme (Fv), induces 100 million US$ crop loss, per year, in the US alone. Field-based spectroscopic remote sensing offers a method to enable timely detection, but still requires appropriate instrumentation and testing. Soybean plants were measured at canopy level over a course of a growing season to assess the capacity of spectral measurements... I. Herrmann, S. Vosberg, P. Ravindran, A. Singh, P. Townsend, S. Conley |
5. 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 of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes |