Proceedings
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| Filter results6 paper(s) found. |
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1. Weed Detection Among Crops by Convolutional Neural Networks with Sliding WindowsOne of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang |
2. Precision Agriculture Research Infrastructure for Sustainable FarmingPrecision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan |
3. 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 |
4. Can Topographic Indices Be Used for Irrigation Management Zone DelineationSoil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble |
5. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in AlabamaEfficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De oliveira |
6. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation StrategiesFarmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble |