Digital Agriculture Lab Publications

Refereed Journal Papers

  1. Atsmon, G., Pourreza, A., Kamiya, Y., Mesgaran, M. B., Kizel, F., Eizenberg, H., & Lati, R. N. (2024). Clustering symptomatic pixels in broomrape-infected carrots facilitates targeted evaluations of alterations in host primary plant traits. Computers and Electronics in Agriculture, 220, 108893.
  2. Francisco Altimiras, Pavéz, L., Pourreza, A., Yáñez, O., González, L., García, J. A., Galaz, C., Leiva-Araos, A., Allende-Cid, H. Transcriptome data analysis applied to grapevine growth stages identification. Agronomy, 14(3), 613.
  3. Zhou, C., Lee, W. S., Zhang, S., Liburd, O. E., Pourreza, A., Schueller, J. K., & Ampatzidis, Y. A Smartphone Application for Site-Specific Pest Management Based on Deep Learning and Spatial Interpolation. Computers and Electronics in Agriculture, 218, 108726.
  4. Peanusaha, S., Pourreza, A., Kamiya, Y., Fidelibus, M., W., & Chakraborty, M. (2024). Nitrogen retrieval in grapevine (Vitis vinifera L.) leaves by hyperspectral sensing. Remote Sensing of Environment, 302, 113966.
  5. Scudiero, E., Corwin, D. L., Markley, P. T., Pourreza, A., Rounsaville, T., Bughici, T., Skaggs, T. H. (2024). A system for concurrent on-the-go soil apparent electrical conductivity and gamma-ray sensing in micro-irrigated orchards. Soil and Tillage Research, 235, 105899.
  6. Azizi, A., Zhang, Z., Rui, Z., Li, Y., Igathinathane, C., Flores, P., Mathew, J., Pourreza, A., Han, X. and Zhang, M. (2024). Comprehensive wheat lodging detection after initial lodging using UAV RGB images. Expert Systems with Applications, 121788.
  7. Chakraborty, M., Pourreza, A., Zhang, X., Jafarbiglu, H., Shackel, K. A., & DeJong, T. (2023). Early almond yield forecasting by bloom mapping using aerial imagery and deep learning. Computers and Electronics in Agriculture, 212, 108063.
  8. Yoosefzadeh-Najafabadi, M., Singh, K. D., Pourreza, A., Sandhu, K. S., Adak, A., Murray, S. C., ... & Rajcan, I. (2023). Remote and proximal sensing: How far has it come to help plant breeders?. Advances in Agronomy, 181, 279-315.
  9. Zhou, C., Lee, W.S., Liburd, O.E., Aygun, I., Zhou, X., Pourreza, A., Schueller, J.K. and Ampatzidis, Y., (2023). Detecting Two-spotted Spider Mites and Predatory Mites in Strawberry Using Deep Learning. Smart Agricultural Technology, 100229.
  10. Jafarbiglu, H., & Pourreza, A. (2023). Impact of sun-view geometry on canopy spectral reflectance variability. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 270-286.
  11. Jafarbiglu, H., & Pourreza, A. (2022). A comprehensive review of remote sensing platforms, sensors, and applications in nut crops. Computers and Electronics in Agriculture, 197, 106844.
  12. Omidi, R., Pourreza, A., Moghimi, A., Zuniga-Ramirez, G., Jafarbiglu, H., Maung, Z., & Westphal, A. (2022). A Semi-supervised approach to cluster symptomatic and asymptomatic leaves in root lesion nematode infected walnut trees. Computers and Electronics in Agriculture, 194, 106761.
  13. Zhang X, Pourreza A, Cheung KH, Zuniga-Ramirez G, Lampinen BD and Shackel KA (2021) Estimation of Fractional Photosynthetically Active Radiation From a Canopy 3D Model; Case Study: Almond Yield Prediction. Front. Plant Sci. 12:715361.
  14. Pourreza, A., Moghimi, A., Niederholzer, F. J., Larbi, P. A., Zuniga-Ramirez, G., Cheung, K. H., & Khorsandi, F. (2020). Spray Backstop: A Method to Reduce Orchard Spray Drift Potential without Limiting the Spray and Air Delivery. Sustainability, 12(21), 8862.
  15. Omidi, R., Moghimi, A., Pourreza, A., El-Hadedy, M., & Eddin, A. S. (2020). Ensemble Hyperspectral Band Selection for Detecting Nitrogen Status in Grape Leaves. arXiv preprint arXiv:2010.04225.
  16. Moghimi, A., Pourreza, A., Zuniga-Ramirez, G., Williams, L. E., & Fidelibus, M. W. (2020). A Novel Machine Learning Approach to Estimate Grapevine Leaf Nitrogen Concentration Using Aerial Multispectral Imagery. Remote Sensing, 12(21), 3515.
  17. Montazar, A., Krueger, R., Corwin, D., Pourreza, A., Little, C., Rios, S., & Snyder, R. L. (2020). Determination of Actual Evapotranspiration and Crop Coefficients of California Date Palms Using the Residual of Energy Balance Approach. Water, 12(8), 2253.
  18. 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.
  19. 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.

 

Previous Publications

Patent

  1. Pourreza, A. (2024). U.S. Patent No. 11,915,366. Washington, DC: U.S. Patent and Trademark Office.
  2. Raveh, Eran, Lee, Wonsuk, Pourreza, Alireza and Ehsani, Reza. “Method for Huanglongbing (HLB) Detection.” WO 2015/193885, 2015 and US20170131200A1, 2017.

Refereed Journal Papers

  1. Pourreza, A., Lee, W. S., Ritenour, M. A., & Roberts, P. (2016). Spectral Characteristics of Citrus Black Spot Disease. HortTechnology, 26(3), 254-260.
  2. Pourreza, A., Lee, W. S., Etxeberria, E., & Zhang, Y. (2016). Identification of Citrus Huanglongbing Disease at the Pre-Symptomatic Stage Using Polarized Imaging Technique. IFAC-PapersOnLine, 49(16), 110-115.
  3. 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
  4. 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.20111.021
  5. Pourreza, A., Lee, W. S., Raveh, E., Ehsani, R., & Etxeberria, E. (2014). Citrus Huanglongbing detection using narrow-band imaging and polarized illumination. Trans. ASABE, 57(1), 259-272.
  6. 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
  7. Aghkhani, M. H., & Pourreza, A. (2007). Egg Sorting by Machine Vision Method. Journal of Agricultural Engineering Research, 8(3), 141-150.