Alireza (Ali) Pourreza, Ph.D

UC Davis Biological and Agricultural Engineering BAE Cooperative Extension Specialist Alireza Ali Pourreza

Position Title
Assistant Cooperative Extension Specialist

Unit
Biological and Agricultural Engineering

3042 Bainer Hall
Bio

Research

Precision Agriculture/horticulture; Agricultural Mechanization; Remote Sensing and GIS; Machine Vision; Agricultural Robotics and Automation; Big Data; Hyperspectral/Multispectral Imaging.

Selected Publications

Referred Journal Articles

  1. Chaji, S., Pourreza, A., Pourreza, H., & Rouhani, M. (2018). Estimation of the camera spectral sensitivity function using neural learning and architecture. Journal of the Optical Society of America A, 35(6), 850-858. doi:10.1364/JOSAA.35.000850
  2. 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), 11.
  3. Pourreza, A., Lee, W. S., Ritenour, M. A., & Roberts, P. (2016). Spectral Characteristics of Citrus Black Spot Disease. HortTechnology, 26(3), 254-260.
  4. Pourreza, A., Lee, W. S., Etxeberria, E., & Zhang, Y. (2016). Identification of Citrus Huanglongbing Disease at the Pre-Symptomatic Stage Using Polarized Imaging Technique. Paper presented at the The 5th IFAC Conference on Sensing, Control and Automation for Agriculture, Seattle WA.
  5. Pourreza, A., Lee, W. S., Etxeberria, E., & Banerjee, A. (2015). An evaluation of a vision-based sensor performance in Huanglongbing disease identification. Biosystems Engineering, 130(0), 13-22. doi:http://dx.doi.org/10.1016/j.biosystemseng.2014.11.013
  6. Pourreza, A., Lee, W. S., Ehsani, R., Schueller, J. K., & Raveh, E. (2015). An optimum method for real-time in-field detection of Huanglongbing disease using a vision sensor. Computers and Electronics in Agriculture, 110(0), 221-232. doi:http://dx.doi.org/10.1016/j.compag.2014.11.021
  7. Pourreza, A., Lee, W. S., Raveh, E., Ehsani, R., & Etxeberria, E. (2014). Citrus Huanglongbing detection using narrow-band imaging and polarized illumination. ASABE, 57(1), 259-272.
  8. Pourreza, A., Pourreza, H., Abbaspour-Fard, M.-H., & Sadrnia, H. (2012). Identification of nine Iranian wheat seed varieties by textural analysis with image processing. Computers and Electronics in Agriculture, 83, 102-108. doi:10.1016/j.compag.2012.02.005
  9. Aghkhani, M. H., & Pourreza, A. (2007). Egg Sorting by Machine Vision Method. Journal of Agricultural Engineering Research, 8(3), 141-150.

Refereed Conference Papers

  1. Pourreza, A., Lee, W. S., Lu, J., & Roberts, P. (2016). Development of a Multiband Sensor for Citrus Black Spot Disease Detection. Paper presented at the 13th ICPA International Conference, St. Louis, Missouri, USA.
  2. Pourreza, A., Lee, W. S., Justice, D., Eva, C., Lance, V., & William, G. (2016). Early Diagnosis of Huanglongbing disease in Citrus Seedlings. Paper presented at the 129th Florida State Horticultural Society Annual Meeting, Stuart, Florida, USA.
  3. Pourreza, A., Lee, W. S., & Etxeberria, E. (2014). Rapid in-field diagnosis of Huanglongbing disease using computer vision. Paper presented at the 127th Florida State Horticultural Society Annual Meeting, Clearwater, Florida, USA.
  4. Pourreza, A., & Lee, W. S. (2014). Effect Of Starch Accumulation In Huanglongbing Symptomatic Leaves On Reflecting Polarized Light. Paper presented at the 12th ICPA International Conference, Sacramento, California, USA.
  5. Pourreza, A., Pourreza, H., & Hossein-Aghkhani, M. (2010). An automatic foreign materials detection of barberries using red-free image processing. Paper presented at the Third International Workshop on Advanced Computational Intelligence (IWACI).

Non-Refereed Conference Papers

  1. Pourreza, A., Lee, W. S., Pourreza, H., & Combs, R. (2015). Spectral band selection to design a low cost sensor for citrus black spot disease detection. Paper presented at the ASABE Annual Meeting, New Orleans, Louisiana, USA.
  2. Pourreza, A., Lee, W. S., & Ehsani, R. (2014). A Vision Based Sensor for Huanglongbing Disease Detection under a Simulated Field Condition. Paper presented at the ASABE Annual Meeting, Montreal, Quebec, Canada.
  3. Pourreza, A., Lee, W. S., Raveh, E., Hong, Y., & Kim, H.-J. (2013). Identification of citrus greening disease using a visible band image analysis. Paper presented at the ASABE Annual International Meeting, Kansas City, Missouri, USA.
  4. Abbaspour-Fard, M.-H., Pourreza, A., Pourreza, H., & Sadrnia, H. (2011). Wheat Class Identification Using LBP, LSP and LSN Textural Features and Monochrome Image. Paper presented at the 12th International Conference in Agricultural Engineering, Thailand.

Extension Publication

  1. Pourreza, A. (November 2017) Virtual Orchard, A New Tool to Better Understand Plant Needs. West Coast Nut Magazine.
  2. Pourreza, A. (April 2017) A Practical Solution to Address the Emergence of Citrus Greening Forecasting in California. CAPCA Advisors Magazine.
  3. Pourreza, A. (2016) Real-Time Sensor for Early Detection of Citrus Huanglongbing (HLB). Online Journal of Topics in Subtropics, UC-ANR.

Media Coverage

  1. Nick Papadopoulos, CropMobster TV (2017, December 5). Ali & The Drones, Huffington Post.
  2. Romero, D E. (2017, September 26). 3D Orchards: UC Researcher Turns Farms into Virtual Reality, NPR Valley Public Radio (KVPR).
  3. Northcutt, G. (2017, online on August 9 and hard copy on October 7) UC researcher aims to make virtual vineyards a reality, Western  Farm Press.
  4. Warnert, J. E. (2017, September 7) How Virtual Orchards Make Better Harvests
  5. Warnert, J. E. (2017, July 25) UC scientist gives orchards a whole new color scheme
  6. Grafton-Cardwell, E., Lemaux P. G., & Stelinski L. (2017, July 24) Starch accumulation sensor for early detection of HLB. Science for Citrus Health
  7. Newsmaker Conference, World Ag Expo (2017, Feb 14) Strategies to combat HLB in California.
  8. Buck, B. (2016, November 3) UF/IFAS imaging system can detect citrus greening before symptoms show
  9. Warnert, J. E. (2016, October 2) New Huanglongbing detection process wins UC advisor international prize
  10. Rusnak, P. (2015, January 30). Researchers Develop Electronic Citrus Greening Detector
  11. Wilmoth, K. (2015, January 28). UF researchers develop effective, inexpensive citrus greening detector    

Patent

  1. Raveh, Eran, Lee, Wonsuk, Pourreza, Alireza and Ehsani, Reza. “Method for Huanglongbing (HLB) Detection.” WO 2015/193885, 2015.

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