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| Filter results11 paper(s) found. |
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1. Performance Evaluation Of A Prototype Variable Rate Sprayer For Spot- Application Of Agrochemicals In Wild Blueberry FieldsWild blueberry yields are highly dependent on agrochemicals for adequate weed control. The excessive use of agrochemicals with uniform application in significant bare spots and plant areas has resulted in increased cost of production. A cost-effective automated prototype variable rate (VR) sprayer was developed for spot-application (SA) of agrochemicals in a specific section of the sprayer boom where the weeds have been detected. The weed patches were mapped with an RTK-GPS... Q. Zaman, A.W. Schumann, D.C. Percival, T.J. Esau, S.M. Read |
2. Estimating Soil Moisture And Organic Matter Content Variabality Using Electromagnatic Induction MetodAbstract: Electromagnetic induction (EMI) methods are gaining popularity due to their non-destructive nature, rapid response and ease of integration into mobile platforms for assessment of the soil moisture content, water table depth, and salinity etc. The objective of this study was to estimate and map soil moisture content and organic matter content using DualEM.... A. Farooque, Q. Zaman, A.W. Schumann, D.C. Percival, T.J. Esau, T. Stauffer |
3. Design And Construction Of A Computer Aided Control And Monitoring System For GreenhousesABSTRACT High expenditure is one the major disadvantages of using human or labor work force in agriculture division. Lack of accurate and precise processing, low working speed and the effect of physical tiredness on their efficiency are same other disadvantages. Using modern technology and replacing human work force with the automated mechanisms and instruments or intelligent machinery leads to the reduction of these expenses, enhancement of precision, accuracy and work speed and... A. Sanaei |
4. 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 |
5. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry FieldsOne of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan |
6. 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 |
7. Does Nitrogen Balance Surplus Done At Field Level Help To Assess Environmental Effects Of Variable Nitrogen Application In Winter Wheat?Increased nitrogen use efficiency (NUE) is important as a specific consideration to decrease negative impacts of nitrogen (N) on the environment and provide better crop quality. Therefore, in many European countries N is used with restrictions due to UE regulations, set to increase NUE. This is particularly important in wheat production because this crop in EU accounts for 48% of cereal production and uses about 25% of total N-fertilizer applied. One of the methods applied to increase NUE... S.M. Samborski |
8. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild BlueberryDeep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White |
9. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield EstimatorsPrediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that most... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh |
10. Potato Disease Detection Using Laser Speckle Imaging and Deep LearningEarly detection of potato diseases is essential for minimizing crop loss. Implementing advanced imaging techniques can significantly improve the accuracy and efficiency of disease detection in potato crops. Leveraging machine learning algorithms can further enhance the speed and precision of disease identification, enabling timely intervention measures. This work presents a novel potato disease detection technique using whole-potato speckle imaging and deep learning. Laser Speckle Imaging (LSI),... A.H. Rabia, M.A. Salem |
11. Development of a High-throughput UAV System for Precision Weed Detection and Control Using Laser Speckle Imaging and UV-C IrradiationTraditional weed control methods, predominantly reliant on herbicides or labor-intensive ground robots, present notable environmental and efficiency challenges within agricultural practices. To address these concerns, this study introduces an innovative approach utilizing unmanned aerial vehicles (UAVs) for autonomous weed detection and control in agricultural fields. Our proposed system depends on the agility of UAV platforms, integrating two primary technologies. Firstly, Laser Speckle Imaging... M.A. Salem, A.H. Rabia |