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| Filter results7 paper(s) found. |
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1. Economic Analysis Of Auto-swath Control For Alabama Crop ProductionWith the rising costs of fertilizer and pesticides and a push towards increasing environmental stewardship, farmers are seeking means to save money while preserving the environment and wildlife habitat. One technology that aids in remedying these concerns is auto-swath control. This investigation evaluates overlap savings using this technology on different application equipment and resulting in economic savings for those adopting it. Several field boundaries were obtained from across the state... D. Mullenix, A.M. Troesch, J.P. Fulton, A.T. Winstead, S.H. Norwood |
2. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate VariationsImproving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and seeding... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin |
3. Evaluating low-cost Lidar and Active Optical Sensors for pasture and forage biomass assessmentAccurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration accuracy... M. Trotter, K. Andersson, M. Welch, M. Chau, L. Frizzel, D. Schneider |
4. Data Clustering Tools for Understanding Spatial Heterogeneity in Crop Production by Integrating Proximal Soil Sensing and Remote Sensing DataRemote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected using these sensors may provide essential information for precision or site-specific management in a production field. In this paper, we introduced a new clustering technique was introduced and compared with existing clustering tools for determining relatively homogeneous... M. Saifuzzaman, V.I. Adamchuk, H. Huang, W. Ji, N. Rabe, A. Biswas |
5. Computer Vision Techniques Applied to Natural Scenes Recognition and Autonomous Locomotion of Agricultural Mobile RobotsThe use of computer systems in Precision Agriculture (PA) promotes the processes’ automation and its applied tasks, specifically the inspection and analysis of agricultural crops, and guided/autonomous locomotion of mobile robots. In this context, this research aims the application of computer vision techniques for agricultural mobile robot locomotion, settled through an architecture for the acquisition, image processing and analysis, in order to segment, classify and recognize patterns... L.C. Lugli, M.L. Tronco, A.J. Porto |
6. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, IranDrone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitative... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali |
7. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease DetectionThe early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordinated... S. Gummi, M. Alahe, Y. Chang, C. Pack |