Proceedings
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| Filter results5 paper(s) found. |
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1. Building Proactive Predictive Models With Big Data Technology For Precision AgricultureIn a world with ever increasing shortages of food production due to increasing populations and depletion of resources, the need for new technologies and techniques for sustainable and efficient agriculture with long term financial, environmental and cultural benefits are critical. An area of scientific study concerning crop-production management called Precision Agriculture (PA) is a concept based on integrating modern information technologies such as Big Data Analytics, GPS... C. Lai, C. Belsky |
2. Applying a Bivariate Frequency Ratio Technique for Potato High Yield Susceptibility MappingSpatial variation of soil characteristics and vegetation conditions are viewed as the most important indicators of crop yield status. Therefore, this study was designed to develop a crop yield prediction model through spatial autocorrelation between the actual yield of potato (Solanum tuberosum L.) crop and selected yield status indicators (soil N, EC, pH, texture and vegetation condition), where the vegetation condition was represented by the cumulative normalized difference vegetation index... K. Al-gaadi, A.A. Hassaballa, E. Tola, R. Madugundu, A.G. Kayad |
3. 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 |
4. 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 |
5. Employment of the SSEB and CROPWAT Models to Estimate the Water Footprint of Potato Grown in Hyper-arid Regions of Saudi ArabiaQuantifying crops’ water footprint (WF) is essential for sustainable agriculture especially in arid regions, which suffers from harsh environmental conditions and severe shortage of freshwater resources such as Saudi Arabia. In this study, WF of irrigated potato crop was estimated for the implementation of precision agriculture techniques. The CROPWAT and the Simplified Surface Energy Balance (SSEB) approaches were adopted. Soil, plant, and yield samples were randomly collected from six... R. Madugundu, K. Al-gaadi, E. Tola |