Proceedings
Authors
| Filter results9 paper(s) found. |
|---|
1. Fluorescence Imaging Spectroscopy Applied To Citrus DiseasesDiseases are one of the most serious threats for citrus production worldwide. Sao Paulo, Brazil and Florida, USA, are the most important citrus producers and, both, are making efforts for citrus diseases control. Citrus canker is one of the serious diseases, caused by the Xanthomonas citri subsp. citri bacteria, that infects citrus trees and relatives, causing a large economic loss in the citrus juice production. Another important disease affecting the citrus production worldwide is the Huanglongbing... C. Wetterich, J. Belasque jr., L. Marcassa |
2. Precision Conservation: Using Precision Agriculture Technology To Optimize Conservation And Profitability In Agricultural LandscapesUSDA Farm Bill conservation programs provide landowner incentives to remove marginal lands from agricultural production and reestablish them to natural vegetation (e.g., native grasses, trees, etc.). However, removal of arable land from production imposes an opportunity cost associated with loss in revenue from commodities that otherwise would have been produced. Northern bobwhite (bobwhite) populations have shown a positive response to numerous conservation programs implemented in agricultural... M.D. Mcconnell, L.W. Burger, W. Givens |
3. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In CornA number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon |
4. Soil Microbial Communities Have Distinct Spatial Patterns in Agricultural FieldsSoil microbial communities mediate many important soil processes in agricultural fields, however their spatial distribution at distances relevant to precision agriculture is poorly understood. This study examined the soil physico-chemical properties and topographic features controlling the spatial distribution of soil microbial communities in a commercial potato field in eastern Canada using next generation sequencing. Soil was collected from a transect (1100 m) with 83 sampling points in a landscape... B. Zebarth, C. Goyer, S. Neupane, S. Li, A. Mills, S. Whitney, A. Cambouris, I. Perron |
5. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water StressesThis paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman |
6. Increasing the Accuracy of UAV-Based Remote Sensing Data for Strawberry Nitrogen and Water Stress DetectionThis paper presents the methods to increase the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data for the determination of plant nitrogen and water stresses with increased accuracy. As the demand for agricultural products is significantly increasing to keep up with the growing population, it is important to investigate methods to reduce the use of water and chemicals for water conservation, reduction in the production cost, and reduction in environmental impact. UAV-based remote... S. Bhandari, A. Raheja |
7. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in VineyardsThis paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg. ... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat |
8. Effective Furrow Closing Systems for Consistent Corn Seed PlacementFarmers face a constant challenge when choosing the appropriate planter setup due to the variability of cropping systems under no-till. Effective performance of the planter's closing wheels can reduce errors from previous components that affect seedbed formation in the furrow. Effective seed-to-soil contact during planting is essential for optimal seed emergence and overall crop stand, with the closing wheels playing a pivotal role in this process. Producers have a range of closing wheels... J. Peiretti, B. Gigena, S. Badua, A. Sharda |
9. Comparing Proximal and Remote Sensors for Variable Rate Nitrogen Management in CottonSensing and variable rate technology are becoming increasingly important in precision agriculture. These technologies utilize sensors to monitor crop growth and health, enabling informed decisions such as diagnosing nitrogen (N) stress and applying variable rates of N. Sensor-based solutions allow for customized N applications based on plant needs and environmental factors. This approach has led to notable reductions in N application rates, minimized N losses by improving N use efficiency (NUE),... A. Bhattarai, A. Jakhar, L. Bastos, G.J. Scarpin |