Proceedings
Authors
| Filter results3 paper(s) found. |
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1. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor DataCotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey |
2. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton ProductionCrop models simulate growth and development, and provide relevant information for the routine management of the crop. The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global positioning... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller |
3. Guiding Spot Sprayer Decisions: Toward Species-Selective Weed ControlSite-specific weed management is a key approach in precision crop protection, enabling spatially targeted herbicide application based on within-field variability in weed distribution. However, most operational spot-spraying systems rely on uniform nozzle activation rules, implicitly treating all detected weeds equally despite differences in competitive ability and ecological function. This limits the potential of precision systems to exploit species-level differentiation in practice. This... M. Gentili, M.S. Madsen, V.A. Nichols, R.N. Jørgensen, J.R. Jørgensen, |