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Agricultural and Biological Engineering

Agricultural and Biological Engineering

A person using a computer system out on the field.
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Precision Agriculture Lab

During the last two decades, we have focused on developing sensing systems for specialty crop production in Florida. Dr. Lee and his team developed many sensing systems, including mature and immature green citrus yield mapping using machine vision and artificial intelligence (AI); yield mapping systems of silage, blueberry, and strawberry; detection and prediction of crop nutrients and soil properties; disease detection for citrus, tomato, and apple; pest detection in strawberry (two-spotted spider mites) using smartphones; strawberry maturity and bruise detection; and strawberry plant wetness detection.

 

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What is Precision Agriculture?

Precision agriculture is managing each crop production input on a site-specific basis to reduce waste, increase profits and maintain the quality of the environment. Precision agriculture is a set of managerial practices whereby spatial variability in a field can be controlled on a micro scale. The main idea behind precision agriculture is spatial variability. This refers to all of the ways a field can differ from one location to another. Variability can include: soil pH, soil moisture, soil depth, soil type, soil texture, topography, pest populations, nutrient levels, organic matter content, etc. The reason precision agriculture can be an effective practice is it defines more accurately the needs of specific locations of individual fields. This in turn can increase the efficiency of crop management in ways that were financially, and scientifically unattainable in the past .

Tools For Precision Agriculture:

  • Global Navigation Satellite System (GNSS) and Geographic Information System (GIS) - These systems allow for precise mapping and interpretation of variability in a field.
  • Yield Monitoring and Mapping - These practices record and collect data about crop yield from specific locations of a field.
  • Soil Testing - This practice defines soil characteristics based on differences in availability of nutrients and variable between testing locations. When used in concert with GPS it has very powerful uses such as variable rate application.
  • Variable Rate Technology and Application - There are two basic methods of Variable Rate Application (VRA), map-based and sensor based. Map-based VRA adjust the application rate based on an electronic map, also called a prescription map. Using GPS field position can be determined, based on the prescription map the rate, or concentration of input can be changed as you drive through the field. Sensor-based VRA requires no map or positioning system. Sensors on the application machine measure soil properties or crop characteristics "on-the-go". Based on this continuous stream of information a computer program calculates the input needs of the soil or plants and then transfers the information to an applicator which delivers the input to the needed location.
  • Crop Scouting and Ground Truthing - These practices aid soil testing and accuracy of GPS and GIS.
  • Remote Sensing - Remote sensing is gathering information about an object without being in contact with it. The two most common methods of remote sensing are aerial photography and satellite imagery. Electromagnetic (EM) energy is the basic element of remote sensing. When electromagnetic radiation comes in contact with an object it can be reflected, absorbed or transmitted. Depending on the characteristics of the object different wavelengths of EM radiation respond differently. Plants have a distinct reflectance pattern thus enabling us to interpret this pattern and gather information about plant health, plant moisture content, plant nutrient levels, etc.

For more information on precision agriculture visit:

  • University of Nebraska, Lincoln's Precision Agriculture Homepage
  • Ohio State University Precision Agriculture
  • University of Minnesota Precision Agriculture
  • Texas A&M University Precision Agriculture
  • NASA's Remote Sensing Tutorial
  • American Society for Photogrammetry and Remote Sensing
  • GPS World Magazine
  • Trimble
  • International Society of Precision Agriculture (ISPA)

Research

Current Projects

  • Two-spotted spider mite detection using artificial intelligence
  • Strawberry plant wetness detection
  • Strawberry plant canopy volume detection

Teaching

  • View Classes

    AOM 3333: Pesticide Application Techniques

    Semester Taught - Fall
    Credits: 3
    Equipment and methods used to apply pesticides in agriculture. Techniques used to avoid misapplication, a common cause of pesticide failures, are emphasized.

    AOM 4434: Precision Agriculture

    Semester Taught - Spring
    Credits: 3
    Principles and applications of technologies supporting precision farming and planning for natural resource data management. Global positioning system (GPS), yield monitoring and mapping, remote sensing, geographic information system (GIS), variable rate technologies (VRT), data layering of independent variables, Internet information access, and computer software for management.

    AOM 5435: Advanced Precision Agriculture

    Semester Taught - Fall, even years
    Credits: 3
    Principles and applications of technologies supporting precision farming and natural resource data management planning. Global positioning system (GPS), geographic information system (GIS), variable rate technologies (VRT), data layering of independent variables, field sensors and computer software for precision farming.

    AOM 5334C: Agricultural Chemical Application Technology

    Semester Taught - Fall
    Credits: 3
    Equipment and methods used to apply pesticides in agriculture. Emphasis on techniques to avoid misapplication and pesticide drift.

Publications

Quick links to publication by Google Scholar:
Google Scholar

Quick links to publication by year:
2020  2019  2018  2017  2016  2015  2014  2013  2012  2011  2010  2009  2008  2007  2006  2005  2004  2003  2002  2001

2020

  • SH Park, Y Hong, M Shuaibu, S Kim, WS Lee. 2020. Detection of Apple Marssonina Blotch with PLSR, PCA, and LDA Using Outdoor Hyperspectral Imaging. SPECTROSCOPY AND SPECTRAL ANALYSIS 40 (4), 1309-1314.
  • DM Queiroz, EDTS Sousa, WS Lee, JK Schueller. 2020. Development and Testing of a low-Cost Portable Apparent Soil Electrical Conductivity Sensor Using a BeagleBone Black. Applied Engineering in Agriculture 36(3), 341-355 .

2019

  • MM Shimwela, SE Halbert, ML Keremane, P Mears, BH Singer, WS Lee,JB Jones, RC Ploetz, AHC van Bruggen. 2019. In-Grove Spatiotemporal Spread of Citrus Huanglongbing and Its Psyllid Vector in Relation to Weather. Phytopathology 109 (3), 418-427.
  • H Gan, WS Lee, N Peres, C Fraisse. 2019. Development of A Multi-Angle Imaging System for Automatic Straw-berry Flower Counting. Association for the Advancement of Artificial Intelligence (www.aaai.org).
  • Y Chen, WS Lee, H Gan, N Peres, C Fraisse, Y Zhang, Y He. 2019. Strawberry Yield Prediction Based on a Deep Neural Network Using High-Resolution Aerial Orthoimages. Remote Sensing 11 (13), 1584.
  • Y Zhang, M Li, L Zheng, Q Qin, WS Lee. 2019. Spectral features extraction for estimation of soil total nitrogen content based on modified ant colony optimization algorithm. Geoderma 333, 23-34.

2018

  • Gan, H., Lee, W.S., Alchanatis, V., Ehsani, R., Schueller, J.K. 2018. Immature green citrus fruit detection using color and thermal images. Computers and Electronics in Agriculture, 152 (2018): 117-125.
  • Gan, H., Lee, W.S., Alchanatis, V. 2018. A photogrammetry-based image registration method for multi-camera systems - with applications in images of a tree crop. Biosystems Engineering, 174 (2018): 89-106.
  • Gan, H., Lee, W.S., Alchanatis, V., Abd-Elrahman, A. 2018. An active thermography method for immature citrus fruit detection. Proceedings of the 14th ICPA.
  • Lu, J., Lee, W. S., Gan, H., Hu, X. 2018. Immature citrus fruit detection based on local binary pattern feature and hierarchical contour analysis. Biosystems Engineering, 171(2018): 78-90.
  • Wang, C., Lee, W. S., Zou, X., Choi, D., Gan, H., Diamond, J. 2018. Detection and counting of immature green citrus fruit based on the local binary patterns (LBP) feature using illumination-normalized images. Precision Agriculture, https://doi.org/10.1007/s11119-018-9574-5.
  • Shuaibu, M., Lee, W. S., Schueller, J., Gader, P., Hong, Y.K., Kim, S. 2018. Unsupervised hyperspectral ban selection for apple Marssonina blotch detection. Computers and Electronics in Agriculture, 148(2018): 45-53.

2017

  • Barocco, R., W. S. Lee, and G. Hortman. 2017. Yield mapping hardware components for grains and cotton using on-the-go monitoring systems. UF/IFAS EDIS
  • Khedher Agha, M. K., W. S. Lee, C. Wang, R. W. Mankin, A. R. Blount, R. A. Bucklin, and N. Bliznyuk. 2017. Detection and prediction of Sitophilus oryzae infestations in triticale via visible and near infrared spectral signatures. Journal of Stored Products Research
  • Queiroz, D., Lee, W.S., Schueller, J. K., Santos, E.D.T. (2017). Development and test of a low cost portable soil apparent electrical conductivity sensor using a Beaglebone Black. In the proceeding of 2017 ASABE AIM, Spokane, Washington DOI: 10.13031/aim.201700062
  • Gan, H., Lee, W.S., Alchanatis, V. (2017). A prototype of an immature citrus fruit yield mapping system. In the proceeding of 2017 ASABE AIM, Spokane, Washington DOI: https://doi.org/10.13031/aim.201700164
  • Choi, D., Lee, W.S., Schueller, J. K., Ehsani, R., Roka, F., Diamond, J. (2017). A performance comparison of RGB, NIR, and depth images in immature citrus detection using deep learning algorithms for yield prediction. In the proceeding of 2017 ASABE AIM, Spokane, Washington DOI: https://doi.org/10.13031/aim.201700076
  • Khedher Agha, M.K., Bucklin, R.A., Lee, W. S., Mankin, R.W., Blount, A.R. (2017). Effect of Drying Conditions on Triticale Seed Germination and Rice Weevil Infestation. Transactions of ASABE, Vol. 60(2):571-575
  • Pourreza, A., Lee, W. S., Czarnecka, E., Verner, L., & Gurley, W. (2017). Feasibility of Using the Optical Sensing Techniques for Early Detection of Huanglongbing in Citrus Seedlings. Robotics, 6(2)
  • Shuaibu, M., Lee, W. S., Hong, Y. K., & Kim, S. (2017). Detection of Apple Marssonina Blotch Disease using Particle Swarm Optimization. Transactions of ASABE, Vol. 60(2): 303-312

2016

  • Ni, Z., Burks, T. F., & Lee, W. S. (2016). 3D Reconstruction of Plant/Tree Canopy Using Monocular and Binocular Vision. Journal of Imaging 2(4), 28.
  • Zhao, C., Lee, W. S., & He, D. (2016). Immature green citrus detection based on colour feature and sum of absolute transformed difference (SATD) using colour images in the citrus grove. Computers and Electronics in Agriculture, 124, 243-253.
  • Choi, D., Lee, W. S., Ehsani, R., Schueller, J., & Roka, F. M. (2016). Detection of dropped citrus fruit on the ground and evaluation of decay stages in varying illumination conditions. Computers and Electronics in Agriculture, 127, 109-119.
  • Li, H., Lee, W. S., & Wang, K. (2016). Immature green citrus fruit detection and counting based on fast normalized cross correlation (FNCC) using natural outdoor colour images. Precision Agriculture, 1-20.
  • Yun, H. S., Park, S. H., Kim, H. J., Lee, W. D., Do Lee, K., Hong, S. Y., & Jung, G. H. (2016). Use of Unmanned Aerial Vehicle for Multi-temporal Monitoring of Soybean Vegetation Fraction. Journal of Biosystems Engineering, 41(2), 126-137.
  • Cubero, S., Lee, W. S., Aleixos, N., Albert, F., & Blasco, J. (2016). Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest—a review. Food and Bioprocess Technology, 9(10), 1623-1639.

2015

  • Pourreza, Alireza, Lee, Won Suk, Reza Ehsani, Schueller, John K, and Raveh, Eran. An Optimum Method for Real-Time In-Field Detection of Huanglongbing Disease Using a Vision Sensor. (2015). Computers and Electronics in Agriculture, Elsevier, Vol. 110, 221–232. (doi: 10.1016/j.compag.2014.11.021)
  • Pourreza, Alireza, Lee, Won Suk, Etxeberria, Edgardo, and Banerjee, Arunava. An evaluation of a vision based sensor performance in Huanglongbing disease identification. (2015). Biosystems Engineering, Elsevier, Vol. 130, 13-22. (doi:10.1016/j.biosystemseng.2014.11.013)
  • Yang, Ce, Lee, Won Suk, and Gader, Paul. Blueberry maturity stage detection based on spectral-spatial detection of hyperspectral image using selected bands. (2015). 2015 ICRA
  • Pourreza, Alireza, Lee, Wonsuk, Combs, Rebekah , Roberts, Pamela, Ritenour, Mark. Spectral band selection to design a low cost sensor for citrus black spot disease detection.(2015). In Proceeding of the 2015 ASABE Annual International Meeting. New Orleans, Louisiana. (doi: 10.13031/aim.20152181312)
  • Choi, D., W. S. Lee, R. Ehsani, Schueller, John K, and Roka, Fritz. (2015). Machine vision system for early yield estimation of citrus in a site-specific manner. ASABE Paper No. 152181863 . St. Joseph, Mich.: ASABE.
  • Li, X., Lee, W. S., Li, M., Ehsani, R., Mishra, A. R., Yang, C., & Mangan, R. L. (2015). Feasibility study on Huanglongbing (citrus greening) detection based on WorldView-2 satellite imagery. Biosystems Engineering, Elsevier, 132, 28-38.
  • Lee, W. S., & Ehsani, R. (2015). Sensing systems for precision agriculture in Florida.Computers and Electronics in Agriculture, Elsevier, Vol. 112, 2-9.
  • Choi, D., W. S. Lee, R. Ehsani, Schueller, John K, and Roka, Fritz. (2014). A Machine Vision System for Quantification of Citrus Fruit Dropped on the Ground under the Canopy . Trans. ASABE, 58(4) 933-946.
  • Kweon, Giyoung, Lund, Eric D., Maxton, Chase, Lee, Won Suk, and Mengel, David B. (2014). Comparison of soil phosphorus measurements. Trans. ASABE, 58(2) 405-414.

2014

  • Pourreza, A., Lee W.S., Ehsani R. (2014). “A Vision Based Sensor for Huanglongbing Disease Detection under a Simulated Field Condition ,” In Proceeding of the 2014 ASABE Annual International Meeting. Montreal, Canada. (doi: 10.13031/aim.20141900251)
  • Pourreza, A., Lee W.S. (2014). “Effect Of Starch Accumulation In Huanglongbing Symptomatic Leaves On Reflecting Polarized Light,” In Proceeding of the 12th ICPA International Conference, Sacramento, California, USA.
  • Pourreza, A., Lee W.S., Etxeberria E. (2014). “Rapid in-field diagnosis of Huanglongbing disease using computer vision,” In Proceeding of the  127th Florida State Horticultural Society Annual Meeting, Clearwater, Florida, USA.
  • Pourreza, A., Lee, W. S., Raveh, E., Ehsani, R., & Etxeberria, E. (2014). Citrus Huanglongbing Disease Detection Using Narrow Band Imaging and Polarized Illumination. Trans. ASABE, 57(1).
  • Kurtulmus, F., W. S. Lee, and A. Vardar. 2014. Immature peach detection in colour images acquired in natural illumination conditions using statistical classifiers and neural network. Precision Agriculture 15: 57-79.
  • Sengupta, S., and W. S. Lee. 2014. Identification and determination of the number of immature green citrus fruit under different ambient light conditions. Biosystems Engineering 117: 51-61.

2013

  • Bansal, R., W. S. Lee, and S. Satish. 2013. Green citrus detection using Fast Fourier Transform (FFT) leakage. Precision Agriculture 14(1): 59-70.
  • Garcia-Ruiz, F., S. Sankaran, J. M. Maja, W. S. Lee, J. Rasmussen, and R. Ehsani. 2013. Comparison of two aerial imaging platforms for identification of Huanglongbing infected citrus trees. Computers and Electronics in Agriculture 91: 106-115.
  • Li, H., W. S. Lee, K. Wang, R. Ehsani, and C. Yang. 2013. ‘Extended spectral angle mapping (ESAM)’ for citrus greening disease detection using airborne hyperspectral imaging. Precision Agriculture.
  • Sengupta, S., and W. S. Lee. 2013. Identification and determination of the number of immature green citrus fruit under different ambient light conditions. Biosystems Engineering.
  • Yang, C. and W. S. Lee. 2013. Precision agricultural systems. In Agricultural automation: fundamentals and practices. Eds. Q. Zhang and F. J. Pierce. CRC Press.
  • Choi, D., W. S. Lee, R. Ehsani, and A. Banerjee. 2013. Detecting and counting citrus fruit on the ground using machine vision. ASABE Paper No. 131591603. St. Joseph, Mich.: ASABE.
  • Katti, A. R., W. S. Lee, and C. Yang. 2013. Laser weeding system for elimination of in-row weeds. In Proceedings of the 5th Asian Conference on Precision Agriculture (ACPA), June 25-28, 2013, Jeju, Korea.
  • Khedher Agha, M. K., W. S. Lee, C. Wang, R. W. Mankin, N. Bliznyuk, and R. A. Bucklin. 2013. Determination degrees of insect infestation in triticale seed using NIR spectroscopy. ASABE Paper No. 131592957. St. Joseph, Mich.: ASABE.
  • Khedher Agha, M. K., W. S. Lee, R. A. Bucklin, A. A. Teixeira, and A. Blount. 2013.Equilibrium moisture content equation for triticale seed. ASABE Paper No. 131620333. St. Joseph, Mich.: ASABE.
  • Li, H., W. S. Lee, and K. Wang. 2013. Airborne hyperspectral imaging based citrus greening disease detection using different dimension reduction methods. ASABE Paper No. 131592802. St. Joseph, Mich.: ASABE.
  • Li, H., W. S. Lee, and K. Wang. 2013. Spectral mixture analysis based citrus greening disease detection using satellite image of Florida. In Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). 25-28 June 2013, Gainesville, Florida, USA.
  • Pourreza, A., W. S. Lee, E. Raveh, Y. K. Hong, and H. J. Kim. 2013. Identification of citrus greening disease using a visible band image analysis. ASABE Paper No. 131591910. St. Joseph, Mich.: ASABE.
  • Saber, M., W. S. Lee, T. F. Burks, G. E. MacDonald, and G. Salvador. 2013.An automated mechanical weed control system for organic row crop production. ASABE Paper No. 131593595. St. Joseph, Mich.: ASABE.
  • Yang, C., W. S. Lee, and P. Gader. 2013. Band selection of hyperspectral imagery for the classification of blueberry fruit maturity stages and leaf. ASABE Paper No. 131593276. St. Joseph, Mich.: ASABE.
  • Yang, C., W. S. Lee, P. Gader, and H. Li. 2013. Hyperspectral band selection using Kullback-Leibler divergence for blueberry fruit detection. In Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). 25-28 June 2013, Gainesville, Florida, USA.

2012

  • Shin, J., W. S. Lee, and R. Ehsani. 2012. Postharvest citrus mass and size estimation using logistic classification model and watershed algorithm. Biosystems Engineering 113(1): 42-53.
  • Ruslan, R., R. Ehsani, and W. S. Lee. 2012. Quantification of total soluble solids and titratable acidity for citrus maturity using VIS-NIR spectroradiometer. Applied Engineering in Agriculture 28(5): 735-743.
  • Kumar, A., W. S. Lee, R. Ehsani, L. G. Albrigo, C. Yang, and R. L. Mangan. 2012. Citrus greening disease detection using aerial hyperspectral and multispectral imaging techniques. Journal of Applied Remote Sensing 6, 063542, http://link.aip.org/link/doi/10.1117/1.JRS.6.063542.
  • Mishra, A. R., D. Karimi, R. Ehsani and W. S. Lee. 2012. Identification of citrus greening (HLB) using a VIS-NIR spectroscopy technique. Trans. ASABE 55(2): 711-720.
  • Li, X., W. S. Lee, M. Li, R. Ehsani, A. Mishra, C. Yang, and R. L. Mangan. 2012. Spectral difference analysis and airborne imaging classification for citrus greening infected trees. Computers and Electronics in Agriculture 83: 32-46.
  • Sengupta, S., and W. S. Lee. 2012. Identification and determination of the number of green citrus fruit under different ambient light conditions. International Conference of Agricultural Engineering CIGR-AgEng2012, July 8-12, 2012, Valencia, Spain.
  • Li, H., W. S. Lee, K. Wang, R. Ehsani, and C. Yang. 2012. Spectral angle mapper (SAM) based citrus greening disease detection using airborne hyperspectral imaging. 11th International Conference on Precision Agriculture, Indianapolis, Indiana.
  • Lee, W. S. 2012. Sensing technologies for precision agriculture: current status and future needs. Proceedings of the 6th International Symposium on Machinery and Mechatronics for Agriculture and Biosystems Engineering (ISMAB), June 18-20, 2012, Jeonju, Korea.
  • Yang, C. and W. S. Lee. 2012. Blueberry fruit detection by Bayesian classifier and support vector machine based on visible to near-infrared multispectral imaging. ASABE Paper No. 12-1338433. St. Joseph, Mich.: ASABE.
  • Zheng, L., W. S. Lee, M. Li, A. Katti, C. Yang, and H. Li. 2012. Analysis of soil phosphorus concentration based on Raman spectroscopy. SPIE Asia-Pacific Remote Sensing 2012, Kyoto, Japan, 29 Oct. – 1 Nov., 2012.
  • Mason, A. D., R. Schnell, J. Ferrell, J. Sartain, and W. S. Lee. 2012. Comparing grid and directed zone soil sampling schemes for peanut production. ASA, CSSA, and SSSA International Annual Meetings, Oct. 21-24, 2012, Cincinnati, Ohio.
  • Khosro, F. A., J. M. Maja, R. Ehsani, and W. S. Lee. 2012. An automated tine control for tractor drawn citrus canopy shakers. ASABE 2012 Annual Meeting, July 29-Aug. 1, 2012, Dallas, Texas.
  • Li, H., W. S. Lee, K. Wang, R. Ehsani, and C. Yang. 2012. Spectral angle mapper (SAM) based citrus greening disease detection using airborne hyperspectral imaging. 11th International Conference on Precision Agriculture, Indianapolis, Indiana.

2011

  • Kurtulmus, F., W. S. Lee, and A. Vardar. 2011. Green citrus detection using eigenfruit, color and circular Gabor texture features under natural outdoor conditions. Computers and Electronics in Agriculture 78(2): 140-149.
  • Bansal, R., W. S. Lee, R. Shankar, and R. Ehsani. 2011. Automated debris mass estimation for citrus mechanical harvesting systems using machine vision. Applied Engineering in Agriculture 27(5): 673-685.
  • Han, Y., W. S. Lee, C. Lee, S. Park, K. Kim, and S. Kim. 2011. Entrapment of Mg-Al layered double hydroxide in calcium alginate beads for phosphate removal from aqueous solution. Desalination and Water Treatment. 36: 178-186.
  • Kurtulmus, F., W. S. Lee, and A. Vardar. 2011. An advanced green citrus detection algorithm using color images and neural networks. 11th International Congress on Mechanization and Energy in Agriculture, Sep. 21-23, 2011, Istanbul, Turkey. Journal of Agricultural Machinery Science, 7(2): 145-151.
  • Bansal, R., W. S. Lee and S. Satish. 2011. Green citrus detection using Fast Fourier Transform (FFT) leakage. 8th European Conference on Precision Agriculture, July 11-14, 2011, Prague, Czech Republic.
  • Kurtulmus, F., W. S. Lee, and A. Vardar. 2011. An advanced green citrus detection algorithm using color images and neural networks. 11th International Congress on Mechanization and Energy in Agriculture. Sep. 21-23, 2011, Istanbul, Turkey.
  • Yang, C. and W. S. Lee. 2011. Spectral signatures of blueberry fruits and leaves. ASABE Paper No. 1110582. St. Joseph, Mich.: ASABE.
  • Li, X., W. S. Lee, M. Li, R. Ehsani, A. Mishra, C. Yang, and R. Mangan. 2011. Comparison of different detection methods for citrus greening disease based on airborne multispectral and hyperspectral imagery. ASABE Paper No. 1110570. St. Joseph, Mich.: ASABE.

2010

  • Lee, W. S., V. Alchanatis, C. Yang, M. Hirafuji, D. Moshou, and C. Li. 2010. Sensing technologies for precision specialty crop production.Computers and Electronics in Agriculture 74(1): 2-33.
  • Jones, C. D., J. B. Jones, and W. S. Lee. 2010. Diagnosis of bacterial spot of tomato using spectral signatures.Computers and Electronics in Agriculture74(2):329-335.
  • Kumar, A., W. S. Lee, R. Ehsani, L. G. Albrigo, C. Yang, and R. L. Mangan. 2010. Citrus greening disease detection using airborne multispectral and hyperspectral imaging. 10th International Conference on Precision Agriculture. July 18-21, 2010, Hyatt Regency Tech Center, Denver, Colorado.
  • Patil, R., W. S. Lee, R. Ehsani, and F. Roka. 2010. Elimination of debris using de-stemmers on a continuous citrus canopy shake and catch harvester. ASABE Paper No. 1008384. St. Joseph, Mich.: ASABE.
  • Bansal, R., W. S. Lee, R. Shankar, and R. Ehsani. 2010. Automated trash estimation in a citrus canopy shake and catch harvester using machine vision. ASABE Paper No. FL10-123. St. Joseph, Mich.: ASABE.

2009

  • Patil, R., W. S. Lee, R. Shankar, and R. Ehsani. 2009. Detection and elimination of trash using machine vision and extended de-stemmer for a citrus canopy shake and catch harvester. ASABE Paper No. FL09-129. St. Joseph, Mich.: ASABE.
  • Chinchuluun, R., W. S. Lee, and R. Ehsani. 2009. Machine vision system for determining citrus count and size on a citrus canopy shake and catch harvester. Applied Engineering in Agriculture 25(4): 451-458.
  • Okamoto, H., and W. S. Lee. 2009. Green citrus detection using hyperspectral imaging. Computers and Electronics in Agriculture 66(2): 201-208.
  • Kumar, A., W. S. Lee, R. Ehsani, and L. G. Albrigo. 2009. Airborne hyperspectral imaging for citrus greening disease detection. In the Proceedings of the 3rd Asian Conference on Precision Agriculture, Beijing , China .
  • Okamoto, H., and W. S. Lee. 2009. Computer vision technique for green citrus recognition in tree image. In the Proceedings of the 4th IFAC International Workshop on Bio-Robotics, Information Technology, and Intelligent Control for Bioproduction Systems, September 10–11, 2009, I Hotel and Conference Center, Champaign, Illinois.

2008

  • Lee, W. S., R. Ehsani, and R. Shankar. 2008. Trash detection system for a citrus canopy shake and catch harvester using machine vision. ASABE Paper No. 084249. St. Joseph, Mich.: ASABE.
  • Lehtola, C. J. and W. S. Lee. 2008. U. S. agricultural safety issues and trends. 3rd Korea-Japan Joint Seminar on “Safety for agricultural machinery”. September, 23, 2008. National Institute of Agricultural Engineering, Rural Development Administration, Suwon, Korea.
  • Lee, W. S., R. Ehsani, and L. G. Albrigo. 2008. Citrus greening (Huanglongbing) detection using aerial hyperspectral imaging. 9th International Conference on Precision Agriculture. July 20-23, 2008, Hyatt Regency Tech Center, Denver, Colorado.
  • Lee, W. S. 2008. Precision agriculture: methods and applications. United Nations/Colombia/United States of America Workshop on the Applications of Global Navigation Satellite Systems. Medellin, Colombia, June 23-27, 2008.
  • Lee, W. S., L. Estrada, and R. Espinel. 2008. Precision agriculture in Ecuador. 2008 Florida Section ASABE Annual Conference and Tradeshow. June 12-13, 2008 – Duck Key, Florida.
  • Lee, W. S. 2008. Precision agriculture: methods and possibilities. Invited presentation at Escuela Superior Politécnica del Litoral (ESPOL), March 9-15, Guayaquil, Ecuador.
  • Lee, W. S., R. Chinchuluun, and R. Ehsani. 2008. Citrus fruit identification using machine vision for a canopy shake and catch harvester. International Symposium: “Application of precision agriculture for fruits and vegetables”. January 6-9, 2008. Grosvenor Resort, Orlando, Florida.
  • Chinchuluun, R., Lee, W., Bhorania, J., and Pardalos, P. M. 2008. Clustering and classification algorithms in food and agricultural applications: A survey. In Papajorgji, P. ed. "Advances in Modeling Agricultural Systems." Berlin : Springer.
  • Lee, W., Bogrekci, I. and Min, M. 2008. Modeling in nutrient sensing for agricultural and environmental applications." In Papajorgji, P. ed. "Advances in Modeling Agricultural Systems. Berlin : Springer.
  • Min, M., W. S. Lee, T. F. Burks, J. D. Jordan, A. W. Schumann, J. K. Schueller, and H. Xie. 2008. Design of a hyperspectral nitrogen sensing system for citrus. Computers and Electronics in Agriculture 63(2): 215-226.

2007

  • Chinchuluun, R., W. S. Lee, and R. Ehsani. 2007. Citrus yield mapping system on a canopy shake and catch harvester. ASABE Paper No. 073050. St. Joseph, Mich.: ASABE.
  • Kane, K. E., and W. S. Lee. 2007. Multispectral imaging for in-field green citrus identification. ASABE Paper No. 073025. St. Joseph, Mich.: ASABE.
  • Okamoto, H., W. S. Lee, and K. E. Kane. 2007. Hyperspectral imaging for green citrus fruit detection. 6th European Conference in Precision Agriculture and 2nd European Conference on Precision Livestock Farming, June 3-6, 2007, Skiathos , Greece .
  • Cohen, M. J., R. Mylavarapu, I. Bogrekci, W. S. Lee, and M. W. Clark. 2007. Reflectance Spectroscopy for Routine Agronomic Soil Analyses. Soil Science 172(6): 469-485.
  • Bogrekci, I. and W. S. Lee. 2007. Comparison of Ultraviolet, Visible, and Near Infrared Sensing for Soil Phosphorus. Biosystems Engineering 96(2): 293-299.

2006

  • Bogrekci, I., and W. S. Lee. 2006. Effects of soil moisture content on absorbance spectra of sandy soils in sensing phosphorus concentrations using UV-VIS-NIR spectroscopy. Trans. ASABE 49(4): 1175-1180.
  • Bogrekci, I., and W. S. Lee. 2006. The effect of particle size on sensing phosphorus by Raman spectroscopy. ASABE Paper No. 063048. St. Joseph, Mich.: ASABE.
  • Chinchuluun, R., and W. S. Lee. 2006. Citrus yield mapping system in natural outdoor scenes using the Watershed transform. ASABE Paper No. 063010. St. Joseph, Mich.: ASABE.
  • Kane, K. E., W. S. Lee. 2006. Spectral sensing of different citrus varieties for precision agriculture. ASABE Paper No. 061065. St. Joseph, Mich.: ASABE.
  • Min, M., and W. S. Lee. 2006. Design of a hyperspectral nitrogen sensing system for citrus. ASABE Paper No. 061061. St. Joseph, Mich.: ASABE.
  • MacArthur, D. K., J. K. Schueller, W. S. Lee, C. D. Crane, E. Z. MacArthur, and L. R. Parsons. 2006. Remotely-piloted helicopter citrus yield map estimation. ASABE Paper No. 063096. St. Joseph , Mich. : ASABE.
  • Min, M., W. S. Lee, Y. H. Kim, and R. A. Bucklin. 2006. Nondestructive detection of nitrogen in Chinese cabbage leaves using VIS- NIR spectroscopy. HortScience 41(1): 162-166.
  • Pydipati, R., T. F. Burks, and W. S. Lee. 2006. Identification of citrus disease using color texture features and discriminant analysis. Computers and electronics in agriculture 52(1): 49-59.

2005

  • Bogrekci, I., and W. S. Lee. 2005. Spectral measurement of common soil phosphates. Trans. ASAE. 48(6): 2371-2378.
  • Lee, W. S., J. K. Schueller, and T. F. Burks. 2005. Wagon-based silage yield mapping system. Agr. Engng. Intl. Vol. VII. Manuscript IT 05 003, website: cigr-ejournal.tamu.edu.
  • Bogrekci, I. , and W. S. Lee. 2005. Spectral soil signatures and sensing phosphorus. Biosystems Engineering 92(4): 527-533.
  • Pydipati, R., T. F. Burks, and W. S. Lee. 2005. Statistical and neural network classifiers for citrus disease detection using machine vision. Trans. ASAE. 48(5): 2007-2014.
  • Bogrekci, I., and W. S. Lee. 2005. Improving phosphorus sensing by eliminating soil particle size effect in spectral measurement. Trans. ASAE. 48(5): 1971-1978.
  • Shin, D. J., W. S. Lee, and S. Y. Na. 2005. Dynamic load estimation in silage harvesting. Trans. ASAE 48(4): 1131-1320.
  • Bogrekci, I., and W. S. Lee. 2005. A Raman sensor for phosphorus sensing in soil and vegetations. ASAE Paper No. 051040. St. Joseph, Mich.: ASAE.
  • Bogrekci, I., W. S. Lee, and J. D. Jordan. 2005. Multispectral image analysis for phosphorus measurement in Bahia grass. ASAE Paper No. 051067. St. Joseph, Mich.: ASAE.
  • Min, M., and W. S. Lee. 2005. Hyperspectral nitrogen sensing system for citrus. ASAE Paper No. 051068. St. Joseph, Mich.: ASAE.
  • Na, S. Y., W. S. Lee, D. J. Shin, J. Y. Kim, and B. H. Lee. 2005. Crop flow measurement using photosensors to reduce disturbance error in yield estimation. ASAE Paper No. 051131. St. Joseph, Mich.: ASAE.
  • Regunathan, M., and W. S. Lee. 2005. Citrus yield mapping and size determination using machine vision and ultrasonic sensors. ASAE Paper No. 053017. St. Joseph, Mich. ASAE.
  • Sevier, B. J., and W. S. Lee. 2005. Precision farming adoption in Florida citrus: A grower case study. ASAE Paper No. 051054. St. Joseph, Mich.: ASAE.
  • Bogrekci, I., W. S. Lee, and J. D. Jordan. 2005. Airborne hyperspectral imaging for sensing phosphorus concentrations in the Lake Okeechobee basins. In Proc. SPIE Defense & Security Symposium, Vol. 5795, p. 106-112, Chemical and Biological Sensing VI. P. J. Gardner ed. March 28-April 1, 2005. Gaylord Palms Resort and Convention Center, Orlando, FL.
  • Bogrekci, I. and W. S. Lee. 2005. Spectral phosphorus mapping using diffuse reflectance of soils and grass. Biosystems Engineering 91(3): 305-312.
  • Sevier, B. J., and W. S. Lee. 2005. Precision farming adoption by Florida citrus producers: probit model analysis. UF/IFAS Extension Circular 1461 - DLN AE283.
  • Min, M., and W. S. Lee. 2005. Determination of significant wavelengths and prediction of nitrogen content for citrus. Trans ASAE 48(2): 455-461.

2004

  • Annamalai, P., W. S. Lee, and T. F. Burks. 2004. Color vision system for estimating citrus yield in real-time. ASAE Paper No. 043054. St. Joseph, Mich.: ASAE.
  • Annamalai, P., and W. S. Lee. 2004. Identification of green citrus fruits using spectral characteristics. ASAE Paper No. FL04-1001. St. Joseph, Mich.: ASAE.
  • Bogrekci, I., W. S. Lee, and J. P. Herrera. 2004. Spectral signatures for the Lake Okeechobee soils using UV-VIS-NIR spectroscopy and predicting phosphorus concentrations. ASAE Paper No. 041076. St. Joseph, Mich.: ASAE.
  • Bogrekci, I., and W. S. Lee. 2004. Soil particle size effect on absorbance spectra of sandy soils in UV-VIS-NIR regions. ASAE Paper No. 043112. St. Joseph, Mich.: ASAE.
  • Shoup, W. D., W. S. Lee, and T. Harrison. 2004. Precision technologies for precision management. In Agricultural Systems Management: Optimizing Efficiency and Performance, 245-276. R. M. Peart and W. D. Shoup, eds. New York, N.Y.: Marcel Dekker.
  • Bogrekci, I., and W. S. Lee. 2004. Determining phosphorus concentration using spectral reflectance of grass and soil samples in the Lake Okeechobee basins in UV, VIS, and NIR regions. In Proc. 7th International Conference on Precision Agriculture.
  • Bogrekci, I., and W. S. Lee. 2004. The effects of soil moisture content on reflectance spectra of soils using UV-VIS-NIR spectroscopy. In Proc. 7th International Conference on Precision Agriculture.
  • Herrera, J. P., W. S. Lee, and I. Bogrekci. 2004. Spectral based phosphorus sensing in the Lake Okeechobee Basin. ASAE Paper No. 041077. St. Joseph, Mich.: ASAE.
  • Min, M., W. S. Lee, and I. Bogrekci. 2004. The effect of water and variety on nitrogen sensing of citrus leaf. ASAE Paper No. 041080. St. Joseph, Mich.: ASAE.
  • Lee, W. S., and D. C. Slaughter. 2004. Recognition of partially occluded plant leaves using a modified Watershed algorithm. Trans. ASAE 47(4): 1269-1280.
  • Sevier, B. J., and W. S. Lee. 2004. Precision agriculture in citrus: a Probit model analysis for technology adoption. ASAE Paper No. 041092. St. Joseph, Mich.: ASAE.
  • Shoup, W. D., W. S. Lee, and T. Harrison. 2004. Precision technologies for precision management. In Agricultural Systems Management: Optimizing Efficiency and Performance, 245-276. R. M. Peart and W. D. Shoup, eds. New York, N.Y.: Marcel Dekker.

2003

  • W. S. Lee, J. F. Sanchez, R. S. Mylavarapu, and J.S. Choe. 2003. Estimating chemical properties of Florida soils using spectral reflectance. Trans. ASAE 46(5): 1443-1453
  • "Citrus yield mapping system using machine vision", ASAE Paper No. 031002
  • "Adoption trends and attitudes towards precision agriculture in Florida citrus: preliminary results from a citrus producer survey", ASAE Paper No. 031100
  • "Spectral-based nitrogen sensing for citrus", ASAE Paper No. 031137
  • "Assessment of P-concentration in the Lake Okeechobee drainage basins with spectroscopic reflectance of VIS and NIR", ASAE Paper No. 031139
  • "Data fusion in yield maps to reduce errors using distinctive types of sensors", ASAE Paper No. 031035

2002

  • "Silage yield monitoring system", ASAE Paper No. 021165
  • "Temporal Variation of Soil Ca, Mg, and K using Precision Agriculture in Florida ", ASAE Paper No. FL 2002-19.
  • "Comparing interpolation methods for mapping soil properties: Ca, Mg, and K", ASAE Paper No. FL 2002-20.

2001

  • "Study on soil properties and spectral characteristics in Florida", ASAE Paper No. 011179

People

Matthew Boughton

Matthew Boughton

Undergraduate Volunteer Student

 
 
 
 
 
Zijing Huang

Zijing Huang

Ph.D. Student

 
 
 
 
 
Akash Kondaparthi

Akash Kondaparthi

OPS, Masters Student
Electrical and Computer Engineering, University of Florida

 
 
 
 
 
William "Alex" Kratochvil

William "Alex" Kratochvil

Undergraduate AI Scholar

 
 
 
 
 
Won Suk "Daniel" Lee

Won Suk "Daniel" Lee

Professor, Precision Agriculture
Agricultural and Biological Engineering, University of Florida
352-294-6721

 
 
 
 
 
Cara Li

Cara Li

Undergraduate Volunteer Student

 
 
 
 
 
Jessie Lin

Jessie Lin

Undergraduate Volunteer Student

 
 
 
 
 
Juseok Nam

Juseok Nam

Visiting Professor
Korea

 
 
 
 
 
Niteesh Takkellapati

Niteesh Takkellapati

OPS, Masters Student
Electrical and Computer Engineering, University of Florida

 
 
 
 
 
Ao Wang

Ao Wang

Graduate Volunteer Student

 
 
 
 
 
Anna Yang

Anna Yang

Undergraduate Volunteer Student

 
 
 
 
 

Past Members

Headshot of student Pranav Manglani

Pranav Manglani

Former OPS, Masters Student
 

Gabriella Conde

Former Undergraduate Volunteer Student
Headshot of student Xinyu Wang

Xinyu Wang

Former Undergraduate Volunteer Student

Dr. Congliang Zhou

Postdoc, Agricultural and Biological Engineering, University of Florida 
 

Ryan Morin

Former Bachelors Intern
 

Arth Patel

Former Masters Intern
 

Pranav Puranik

Former Masters Intern
 

Dr. Xue Zhou

Postdoc, Agricultural and Biological Engineering, University of Florida
 

Dr. Juan Wen

Former Visiting Scholar
 

Dr. Yushin Ha

Former Visiting Scholar
Yong-Joo Kim

Dr. Yong-Joo Kim

Professor, Chungnam National University, Korea
Research: Design and analysis of agricultural powertrain,Power analysis of smart tractor
Email: babina@cnu.ac.kr
Jay Patel

Jay Patel

M.S. Student. 2019-2020.
Research: Classification and counting of strawberry fruits and flowers using deep learning techniques.
Email: jaypatel1@ufl.edu
Jaehwan Kwon

Jaehwan Kwon

Senior Researcher, Rural Research Institute of Korea Rural Community Corporation, Korea
Research: The improvement of smart agricultural infrastructure by applying digitalization technology
Email: jhkwon@ekr.or.kr
Ikbal AYGÜN

Dr. Ikbal AYGÜN

Assistant Professor, Visiting Scholar from Ege University, Turkey
Research: Microwave weeding, Image processing and artificial intelligence
Email: ikbalaygun@gmail.com
Yun Zhao

Dr. Yun Zhao

Associate Professor, Visiting Scholar from ZheJiang University of Sicence and Technology, China
Research: Computer vision and artificial intelligence
Email: zy_super0201@163.com
Hak-jin Kim

Dr. Hak-jin Kim

Professor, Visiting Scholar from Seoul National University, Korea
Research: sensor and control system development for biosystems, indoor and farm automation, and UAV applications for precision agriculture
Email: kimhj69@snu.ac.kr
Hao Gan

Hao Gan

Ph.D. 2015-2019.
Current Position: Assistant Professor, University of Tennessee Research: Dectection of immature green citrus fruit using hyperspectral and thermal imaging.
Email: ganhao89@ufl.edu
 

Anushka Swarup

M.S. Student. 2018-2019.
Research: Strawberry miosture detection using machine vision.
Email: aswarup@ufl.edu
 

Cristian Dionisi

B.S. Student. 2018-2019.
Major: Mechanical Engineering.
Email: cristian1928@ufl.edu
Rui Lin

Rui Lin

Exchange M.S. Student, South China Agricutlure University, China. 2018-2019.
Research: Mahine vision and Image processing
Email: linrui@ufl.edu
Sirapoom Peanusaha

Sirapoom Peanusaha

B.S. Student. 2018-2019.
Major: Biological Engineering.
Email: animal2129@ufl.edu
Yang Chen

Yang Chen

Exchange Ph.D. Student, Zhejiang University, China. 2017-2018.
Research: UAV remote sensing and 3D reconstruction
Email: ychen2014@zju.edu.cn
Arumugam Kalaikannan

Arumugam Kalaikannan

M.S. Student. 2016-2018.
Research: Strawberry Yield Estimation using Machine Vision.
Email: akalaikannan@ufl.edu
Chanseok Ryu

Dr. Chanseok Ryu

Visiting Scholar from Gyeongsang National University, Korea
Research: Remote sensing, UAV, Hyperspectral imagery, GIS
Email: ryucs@gnu.ac.kr
Wansoo Kim

Wansoo Kim

Ph.D. Student, Chungnam National University, Korea
Research: Agricultural Power and Tractor
Email: ws6602@cnu.ac.kr
Yongming Chen

Dr. Yongming Chen

Assistant Professor, Yancheng Institute of Technology, Jiangsu, China
Research: Computer Vision, Pattern Recognition, Big Data Analysis.
Email: billrange007@gmail.com
Ping Lin

Dr. Ping Lin

Associate Professor, Yancheng Institute of Technology, Jiangsu, China
Research: Data Mining, Computer Vision, Pattern Recognition.
Email: binglvcha007@126.com
Chenglin Wang

Chenglin Wang

Exchange Ph.D. Student, South China Agricultural University, China. 2017-2018.
Research: Computer vision and image processing
Email: wangchenglin055@163.com
Kezhu Tan

Dr. Kezhu Tan

Associate Professor, Northeast Agricultural University, China
Research: Computer vision and deep learning in agricultural products detection
Email: kztanneau@126.com
Dr. Daeun Choi

Dr. Daeun Choi

Ph.D. 2013-2017.
Current Position: Assistant Professor, Penn State University Research: Detection of citrus fruit dropped on the ground using machine vision.
Email: ekdms663@gmail.com
Jun Lu

Dr. Yao Zhang

Exchange Ph.D. student, China Agriculture University, China. 2016
Research: Image processing and machine vision in agriculture
Email: zhycau@ufl.edu
Jun Lu

Dr. Jun Lu

Associate Professor, Huazhong Agricultural University, China.
Research: Image processing and machine vision in agriculture
Email: lujun5918@163.com
Amanda DeCanio

Amanda DeCanio

Bachelor's Student, Undergraduate Research Assistant, 2013-2016.
Research: Precision Agriculture.
Email: a.decanio@ufl.edu
Rohit Garg

Rohit Garg

Master's Student, 2013-2016.
Research: Design a software to automate Laser weed system by detecting weed plants through computer vision (OpenCV).
Future work: Field Robot Programming
Email: rohit.garg@ufl.edu
Leandro Durand

Leandro Durand

Master's Student, 2013-2016.
Research: Designing software for autonomous movement of Husky with a Kinect (ROS).
Email: Ldurand92@ufl.edu
Dr. Yong Hyeon Kim

Dr. Yong Hyeon Kim

Professor, Chonbuk National University, Korea
Research: Plant factory, Protected horticulture, Greenhouse engineering, Light application for plant production, and Space farming
Email: yhkim@jbnu.ac.kr
Dr. Daniel Queiroz

Dr. Daniel Queiroz

Professor, Universidade Federal de Viçosa (UFV), Brazil
Research: Agricultural Engineering, Grain Storage, Machine Vision, Coffee
Email: queiroz@ufv.br
Chuanyuan Zhao

Chuanyuan "Cynthia" Zhao

Exchange PhD student from Northwest A&F University, China. 2013-2015.
Research: Multispectral/hyperspectral imaging for citrus and blueberry detection.
Email: cynthiazcy@gmail.com
Dr. Yongjun Ding

Dr. Yongjun Ding

Associate professor, Lanzhou City University, China
Research: Agricultural Engineering, Machine Vision, Machine Learning
Email: lzdingyj@sina.com
Dr. Young Ki Hong

Dr. Young Ki Hong

Senior researcher
Research: Mechatronics in Agriculture, Remote sensing, Precision Agriculture
Email: sanm70@korea.kr
Alireza Pourreza

Dr. Alireza Pourreza

PhD 2011-2014
Current Position: Assistant CE Specialist of Agricultural Mechanization, UC Davis
Research: Citrus disease detection using machine vision
Email: apourreza@ufl.edu
Soo Hyun Park

Dr. Soo Hyun Park

PhD 2010-2014 (from Seoul National University)
Research: Non-Destructive Technology:
    • Image Processing, Spectroscopic Methods
      • Email:
 soohpark@ufl.edu
Barakat Shuaib

Mubarakat Shuaibu

Master's Student. 2014-2016.
Research: Detection of Marssonina Blotch disease in apples using hyperspectral imaging.
Email: mshuaibu@ufl.edu
Brianna B Posadas

Brianna B Posadas

Master's Student. 2014-2016.
Research: Detection of Marssonina Blotch disease in apples using hyperspectral imaging.
Email: bposadas@ufl.edu
Chuanyuan Zhao

Dr. Chuanqi Xie

Exchange PhD student from Zhejiang University, China. 2014-2015.
Research: Diseases detection on tomato and eggplant leaves using hyperspectral imaging technique.
Email: cqxie@zju.edu.cn
Revant shah

Revant shah

OPS Student, Undergraduate Student, 2013-2015.
Research: Weed Removal system using lasers and computer vision.
Email: revantshah2000@gmail.com
Mahmoud Agha

Dr. Mahmoud Agha

PhD 2010-2014.
Research: Detection and protection of triticale seed from infestation in a storage system.
Email: mahmoudagha@ufl.edu
Mazin Saber

Dr. Mazin Saber

PhD 2009-2014.
Research: Agricultural power machinery for precision agriculture.
Email: mazinsaber@ufl.edu
Ce Yang

Dr. Ce Yang

Ph.D. 2009-2013
Current Position: Assistant Professor, University of Minnesota Research: Blueberry yield mapping using hyperpsectral imaging. Post harvest citrus inspection on conveyor belt
Email: ycicj@ufl.edu
Anurag Katti

Anurag Katti

OPS Student, M.S. student in Electrical and Computer Engineering. 2011-2013.
Research: Weed control system using machine vision and laser.
Email: anuragkatti@gmail.com
Sudhir Vyasaraja

Sudhir Vyasaraja

OPS Student, M.S. student in Electrical and Computer Engineering. 2013-2014.
Research: Weed control system using machine vision and laser.
Email: sudhirv20@gmail.com
Kadeem Morrison

Kadeem Morrison

Bachelor’s Student, 2013-present.
Research: Citrus Black Spot (CBS) identification using spectroscopy.
Email: kadeemc84@gmail.com
Palani Annamalai

Palani Annamalai

M.S. Graduated Summer 2004.
Research: Silage Yield Mapping System. Research on Citrus Yield Mapping Using Machine Vision.
Rajneesh Bansal

Rajneesh Bansal

OPS student, M.S. Electrical and Computer Engineering. 2009-2010.
Research: Research: Citrus trash detection in a citrus canopy shake and catch harvester using machine vision.
Dr. Ismail Bogrekci

Dr. Ismail Bogrekci

Post Doctoral Research Associate, 2003-2006.
Research: Sensor development; Image acquisition, processing, and analysis; Precision Agriculture; Measurement and instrumentation.
Michael Brecht

Michael Brecht

M.S. student. Graduated Fall 2012.
Research: Evaluating Mechanical Damage of Vine-kill Harvested Potatoes.
Dr. Yuehua Chen

Dr. Yuehua Chen

Visiting scholar from Northeast Agricultural University, China, 2013-2014.
Research: Citrus fruit detection using machine vision.
Email: chyh20060206@hotmail.com
Radnaabazar Chinchuluun

Radnaabazar Chinchuluun

M.S. Graduated Summer, 2007. Currently Software Engineer at Medical Education Technologies, Inc.
Research: Citrus yield mapping using machine vision.
Dr. Jung Seob Choe

Dr. Jung Seob Choe

Visiting Professor, Sangju National University, Korea, 2001-2002.
Research: Estimation of chemical properties of Florida soils using spectral reflectance.
Juan Herrera

Juan Herrera

Graduated Spring 2004.
Research: Developing a P-sensing system for the Lake Okeechobee drainage basins.
Kevin Kane

Kevin Kane

Graduated Summer, 2007.
Research: Research on Green citrus yield mapping using machine vision and spectral characteristics.
Dr. Song-Bae Kim

Dr. Song-Bae Kim

Visiting scholar from Seoul National University, Korea, 2010-2011.
Research: Biocolloid transport and removal in porous media; Contaminant removal using functional media.
Han Li

Han Li

Ph.D. Exchange student from China Agricultural University, China, 2011-2013.
Research: Detection of citrus greening disease / Blueberry fruit detection.
Hao Ma

Hao Ma

Ph.D. Exchange student from China Agricultural University, China. 2012-2013.
Research: Citrus disease and nutrient detection using hyperspectral/multispectral imaging.
Dr. Yong Hyeon Kim

Dr. Yong Hyeon Kim

Visiting Professor, Department of Bioresource Mechanical Engineering, Chonbuk National University , Korea, 2003-2004.
Research: Nitrogen management of Chinese cabbage seedlings using NIR technique
Arun Kumar

Arun Kumar

M.S. Electrical and Computer Engineering. 2009-2010.
Research: Research: Citrus greening disease (Huanglongbing) detecting using airborne hyperspectral imaging.
Dr. Xiuhua Li

Dr. Xiuhua Li

Ph.D. exchange student from China Agricultural University. 2010-2011.
Research: Research: Citrus greening disease detection using airborne hyperspectral imaging.
Dr. Ferhat Kurtulmus

Dr. Ferhat Kurtulmus

Ph.D. exchange student from Uludag University in Turkey. 2010-2011.
Research: Research: Green citrus fruit detection using advanced image processing algorithm.
Dr. Min Min

Dr. Min Min

Graduated Spring 2006.
Research: Currently Postdoctoral Research Associate at University of Minnesota. Spectral-based N sensing for citrus
 

Dr. Seung You Na

Visiting Professor, Department of Electronics and Computer Engineering in Chonnam National University, Kwangju, Korea, 2002-2004.
Research: Dynamic load estimation in silage harvesting.
Dr. Hiroshi Okamoto

Dr. Hiroshi Okamoto

Visiting Professor, Hokkaido University, Japan, 2006-2007.
Research: Computer software design and development, hyperspectral imaging, machine vision, stereo vision system, precision agriculture, automatic control of agricultural machines.
Rohan Patil

Rohan Patil

M.S. Graduated Summer 2010.
Research: Trash detection and removal in a citrus canopy shake and catch harvester.
Dr. Eran Raveh

Dr. Eran Raveh

Visiting scholar from ARO, Israel, 2009-2010.
Research: Physiological aspect of citrus greening disease.
Murali Regunathan

Murali Regunathan

M.S. Student, 2005.
Research: Citrus yield mapping using machine vision
 

Arvind Saikumar

OPS student, M.S. Graduated Fall, 2008, Computer & Information Science & Engineering.
Research: Machine vision based green citrus fruit detection.
Dr. Brian Sevier

Dr. Brian Sevier

Ph.D. Graduated Spring 2005. Currently at Contracts and Grants @ IFAS at University of Florida.
Research: Adoption trend of precision agriculture technologies in Florida.
Email: bjse@ufl.edu
 

Ramya Shankar

OPS student, M.S. Graduated Summer, 2009, Electrical and Computer Engineering.
Research: Machine vision based trash detection in a citrus canopy shake and catch harvester Citrus greening disease (Huanglongbing) using airborne hyperspectral imaging.

Contact Us

Name E-mail Phone
Dr. Wonsuk "Daniel" Lee

wslee@ufl.edu

 352-294-6721
Precision Agriculture Laboratory - 352-294-6721

Address

Department of Agricultural and Biological Engineering
207 Frazier Rogers Hall, PO Box 110570 Gainesville, FL 32611

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1741 Museum Road, Gainesville, Florida 32611-0570
(352)392-1864/F(352) 392-4092

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