Proceedings
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| Filter results6 paper(s) found. |
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1. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide EmissionsTo minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions. Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller |
2. Delineation of Yield Zones Using Optical and Radar Remote SensingIdentifying yield zones in agricultural areas is essential for efficient resource allocation, operational optimization, and decision-making. While optical remote sensing is widely used in precision agriculture, the interest in radar remote sensing data, notably from the Sentinel-1 Synthetic Aperture Radar (SAR), has increased due to its operation in the C-band frequency, capturing data through cloud cover and the availability of free data. The main objective of this study was to evaluate whether... I.A. Da cunha, H. Oldoni, D.D. Melo, L.R. Amaral |
3. Yield Potential Zones and Their Relationship with Soil Taxonomic Classes and Management ZonesThe use of management zones (MZ) to subdivide agricultural areas based on the variability of yield potential and production factors is increasingly being explored by scientific research and demanded by farmers. However, there is still much uncertainty about which layers of information and procedures should be adopted for this purpose. Thus, our goal was to demonstrate whether simplistic approaches to creating MZ can satisfactorily address the variability of yield potential and soil classes. For... L.R. Amaral, H. Oldoni, D.D. Melo, N.A. Rosin, M.R. Alves, J.M. Demattê |
4. Hierarchical Zoning: Targeted Sampling for Soil Attribute MappingThe mapping of soil attributes for fertilizer recommendation remains challenging in precision agriculture. Traditionally, this mapping is done through soil sampling in a regular grid, which generally yields good results when done in denser grids. However, due to the high costs associated with sampling and analysis, sparser grids have been adopted, which has not produced good prediction results. Some studies with directed sampling points to obtain more accurate soil maps have been adopted to address... D.D. Melo, I.A. Da cunha, T.L. Brasco, H. Oldoni, L.R. Amaral |
5. Predicting Soybean Yield Using Remote Sensing and a Machine Learning ModelSoybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore |
6. Unlocking Canopy Dynamics: Uav-lidar-based Biomass Estimation in Ocimum BasilicumUAV-LiDAR offers a high-throughput route to phenotyping and biomass estimation in basil (Ocimum basilicum L.). Over three crops seasons (2021–2023), we evaluated three commercial varieties across 96 plots under different irrigation regimes and sowing densities. Multi-temporal LiDAR acquisitions quantified canopy height, LAI and volume and were validated against ground truth. Canopy volume strongly predicted fresh biomass (R² = 0.93; mean error < 8%). Across years, fresh biomass... P. Toscano |