Proceedings
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| Filter results16 paper(s) found. |
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1. Spectral Angle Mapper (SAM) Based Citrus Greening Disease Detection Using Airborne Hyperspectral ImagingOver the past two decades, hyperspectral (HS) imaging has provided remarkable performance in ground objects classification and disease identification, due to its high spectral resolution. In this paper, a novel method named ‘extended spectral angle mapping (ESAM)’ is proposed to detect citrus greening disease (Huanglongbing or HLB), which is a destructive disease of citrus. Firstly, Savitzky-Golay smoothing filter was applied to the raw image to remove spectral noise within the data,... W. Lee, K. Wang, H. Li, R. Ehsani, C. Yang |
2. Post-Harvest Quality Evaluation System On Conveyor Belt For Mechanically Harvested CitrusRecently, a machine vision technology has shown its popularity for automating visual inspection. Many studies proved that the machine vision system can successfully estimate external qualities of fruit as good as manual inspection. However, introducing mechanical harvesters to citrus industry caused the following year’s yield loss due to the loss of immature young citrus. In this study, a machine vision system on a conveyor belt was developed to inspect mechanically... W. Lee, R. Ehsani, F. Roka, D. Choi, C. Yang |
3. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of WordsThe production of sugar and ethanol in Brazil is very prominent economically and the reducing costs and improving the production system being necessary. The management crops operations of sugarcane and the control of weed is one of the processes that cause the greatest increase in production costs; because the competition that exists between cane plants and weed, for water, nutrients and sunlight is big, contribute to the loss of up to 20% of the useful cane. The use of image processing techniques... W.E. Santiago, A.R. Barreto, D.G. Figueredo, R.C. Tinini, B.T. Mederos, N.J. Leite |
4. Effect Of Starch Accumulation In Huanglongbing Symptomatic Leaves On Reflecting Polarized LightHuanglongbing (HLB) or citrus greening disease is an extremely dangerous infection which has severely influenced the citrus industry in Florida. It was also recently found in California and Texas. There is no effective cure for this disease reported yet. The infected trees should be identified and removed immediately to prevent the disease from being spread to other trees. The visual leaf symptoms of this disease are green islands, yellow veins, or vein corking; however,... W. Lee, A. Pourreza |
5. A Precise Fruit Inspection System for Huanglongbing and Other Common Citrus Defects Using GPU and Deep Learning TechnologiesWorld climate change and extreme weather conditions can generate uncertainties in crop production by increasing plant diseases and having significant impacts on crop yield loss. To enable precision agriculture technology in Florida’s citrus industry, a machine vision system was developed to identify common citrus production problems such as Huanglongbing (HLB), rust mite and wind scar. Objectives of this article were 1) to develop a simultaneous image acquisition system using multiple cameras... D. Choi, W. Lee, J.K. Schueller, R. Ehsani, F.M. Roka, M.A. Ritenour |
6. A Photogrammetry-based Image Registration Method for Multi-camera SystemsIn precision agriculture, yield maps are important for farmers to make plans. Farmers will have a better management of the farm if early yield map can be created. In Florida, citrus is a very important agricultural product. To predict citrus production, fruit detection method has to be developed. Ideally, the earlier the prediction can be done the better management plan can be made. Thus, fruit detection before their mature stage is expected. This study aims to develop a thermal-visible camera... H. Gan, W. Lee, V. Alchanatis |
7. A Data Fusion Method for Yield and Soil Sensor MapsUtilizing yield maps to their full potential has been one of the challenges in precision agriculture. A key objective for understanding patterns of yield variation is to derive management zones, with the expectation that several years of quality yield data will delineate consistent productivity zones. The anticipated outcome is a map that shows where soil productive potentials differ. In spite of the widespread usage of yield monitors, commercial agriculture has found it difficult... E. Lund, C. Maxton, T. Lund |
8. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case StudyPrecision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are described... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie |
9. Economics of Swarm Bot Profitability for Cotton HarvestImproved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine |
10. Strawberry Pest Detection Using Deep Learning and Automatic Imaging SystemStrawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality. However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez |
11. Measuring Soil Carbon with Intensive Soil Sampling and Proximal Profile SensingSoils have a large carbon storage capacity and sequestering additional carbon in agricultural fields can reduce CO2 levels in the atmosphere, helping to mitigate climate change. Efforts are underway to incentivize agricultural producers to increase soil organic carbon (SOC) stocks in their fields using various conservation practices. These practices and the increased SOC provide important additional benefits including improved soil health, water quality and – in some cases –... E. Lund, T. Lund, C. Maxton |
12. HOPSY: Harvesting Optimization for Production of Strawberry Using Real-time Detection with YOLOv8Optimizing the harvesting process presents a continuous challenge within the strawberry industry, especially during peak seasons when precise labor allocation becomes critical for efficiency and cost-effectiveness. The conventional method for addressing this issue has been hindered by an absence of real-time data regarding yield distribution, resulting in less-than-ideal worker assignments and unnecessary expenditures on labor. In response, a novel, portable, real-time strawberry detection system... Z. Huang, W. Lee, N. Takkellapati |
13. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, RiversideFunded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus |
14. Accurately Mapping Soil Profiles: Sensor Probe Measurements at Dense Spatial ScalesProximal sensing of soil properties has typically been accomplished using various sensor platforms deployed in a continuous sensing mode collecting data along transects, typically spaced 10-20 meters apart. This type of sensing can provide detailed maps of the X-Y soil variability and some sensors provide an indication of soil properties within the profile, however without additional investigations the profile is not delineated precisely. Alternatively, soil sensor probes can provide detailed... T. Lund, E. Lund, C.R. Maxton |
15. Using Soil Samples and Soil Sensors to Improve Soil Nutrient EstimationsEstimating soil nutrient levels, especially immobile nutrients like P and K, has been a primary activity for providers of precision agriculture services. Soil nutrients often vary widely within fields and growers have been eager to manage them site-specifically. There are many causes of the variability, including pedogenic factors such as soil texture, organic matter, landscape position and other factors that have resulted in an accumulation of unused nutrients in some areas of the... C.R. Maxton, T. Lund, E. Lund |
16. Veris Technologies - Sponsor PresentationVeris Technologies, Inc. designs, builds, and markets sensors and software for precision agriculture. ... T. Lund |