Proceedings
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| Filter results10 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. 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 |
4. Using A Decision Tree To Predict The Population Density Of Redheaded Cockchafer (Adoryphorus Couloni) In Dairy FieldsA native soil dwelling insect pest, the redheaded cockchafer (Adoryphorus couloni) (Burmeister) (RHC) is an important pest in the higher rainfall regions of south-eastern Australia. Due to the majority of its lifecycle spent underground feeding on the roots and soil organic matter the redheaded cockchafer is difficult to detect and control. The ability to predict the level of infestation and location of redheaded cockchafers in a field may give producers the option to use an endophyte containing... A. Cosby, G. Falzon, M. Trotter, J. Stanley, K. Powell, D. Schneider, D. Lamb |
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. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, CanadaManagement zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath |
8. Rapid Identification of Mulberry Leaf Pests Based on Near Infrared Hyperspectral ImagingAs one of the most common mulberry pests, Diaphania pyloalis Walker (Lepidoptera: Pyralididae) has occurred and damaged in the main sericulture areas of China. Naked eye observation, the most dominating method identifying the damage of Diaphania pyloalis, is time-wasting and labor consuming. In order to improve the identification and diagnosis efficiency and avoid the massive outbreak of Diaphania pyloalis, near infrared (NIR) hyperspectral imaging technology combined with partial least discriminant... L. Yang, L. Huang, L. Meng, J. Wang, D. Wu, X. Fu, S. Li |
9. 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 |
10. 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 |