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Dr. Sindhuja Sankaran Phenomics Lab

Publications

Refereed Publications

2024

  • Zhi, Q., Shah, D.H., Sablani, S.S., Ross, C.F., Sankaran, S., and Tang, J., Thermal inactivation kinetics of Salmonella and Campylobacter in chicken livers. Poultry Science,
  • Veloo, K., Glenn, A.E., King, A.B., Smith, B.J., and Marleau, M.M, and Sankaran, S. 2024. Tuber Ruler: A mobile app for evaluating image-based potato tuber size. Journal of Food Measurement and Characterization, https://doi.org/10.1007/s11694-024-02542-6.
  • Yu, X., Yin, D., Xu, H., Pinto Espinosa, F., Schmidhalter, U., Nie, C., Bai, Y., Sankaran, S., Ming, B., Cui, N. Wu, W., and Jin, X. 2024. Maize tassel number and tasseling stage monitoring based on near-ground and UAV RGB images by improved YoloV8. Precision Agriculture, 1-39.
  • Sangjan, W., Carter, A.H., Pumphrey, M., Hagemeyer, K., Jitkov, V., and Sankaran, S. 2024. Effect of high-resolution satellite and UAV imagery plot pixel resolution in wheat crop yield prediction. International Journal of Remote Sensing, 45(5), 1678-1698.
  • Sangjan, W., McGee, R.J., and Sankaran, S. 2024. Evaluation of forage quality in a pea breeding program using a hyperspectral sensing system. Computer and Electronics in Agriculture, 212, 108052.
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Book Chapters

  • Zhang, C., and Sankaran, S. 2022. High-throughput extraction of seed traits using image acquisition and analysis. Editor: Lorence, A. Springer. In Methods in Molecular Biology, 2539:71-76, 10.1007/978-1-0716-2537-8_8, 71-76.
  • Sankaran, S., Khot, L.R., and Ehsani, R. 2019. Applies remote sensing systems in phytopathology. In ‘Precision phytopathology: Frontiers of Science’, Editors: Edson Luiz Furtado, Sérgio Florentino Pascholati, Waldir Cintra de Jesus Junior, Willian Bucker Moraes, Fundação de Estudos e Pesquisas Agrícolas e Florestais (FEPAF), Brazil, pp. 25-45.
  • Sankaran, S., Zhang, C., and Marzougui, A. 2017. Sensing for stress detection and high-throughput phenotyping in precision horticulture. In ‘Automation in tree fruit production: Principles and practice’, Editor: Zhang Q. CABI, pp. 28-42.
  • Sankaran, S., Khot, L.R., and Ehsani, R. 2014. Mid- and Far-infrared Imaging. In ‘Imaging with Electromagnetic Spectrum: Applications in Food and Agriculture’. Editors: Alahakoon, M.K., Annamalai, M., and Jayasuriya, H.P.W. Springer, 129-146.
  • Sankaran, S., and Ehsani, R. 2014. Introduction to the Electromagnetic Spectrum. In ‘Imaging with Electromagnetic Spectrum: Applications in Food and Agriculture’. Editors: Alahakoon, M.K., Annamalai, M., and Jayasuriya, H.P.W. Springer, 1-15.
  • Aksenov, A., Guaman, N.A.V., Sankaran, S., Fung, A.G., Pasamontes, A., Frederico, M., Cheung, W.H.K., Ehsani, R., Dandekar, A.M., and Davis, C.E. 2013. Volatile organic compounds (VOCs) for noninvasive plant diagnostics. In ‘Pest Management with Natural Products’. Editors, J.J. Beck, J.R. Coats, S.O. Duke, M.E. Koivunen. ACS Publications, doi: 10.1021/bk-2013-1141.fw001, pp. 73-95.
  • Van Leeuwen, J. (Hans), Rasmussen, M.L., Sankaran, S., Koza, C.R., Erickson, D.T., Mitra, D., and Jin, B. 2011. Fungal treatment of crop processing wastewaters with value-added co-products. In ‘Sustainable Bioenergy and Bioproducts’. Eds: Kasthurirangan Gopalakrishnan, Hans van Leeuwen, Robert C. Brown. Chapter II, Springer-Verlag Inc., pp. 13-44.

Proceeding Publications/Reports

  • Sangjan, W., Pukrongta, N., Carter, A. H., Pumphrey, M. O., and Sankaran, S. 2022. Development of IoT-based camera system for automated in-field monitoring to support crop breeding Programs. Authorea Preprints.
  • Sangjan, W., Carter, A. H., Pumphrey, M. O., and Sankaran, S. 2021. Development of sensor system for the internet of things (IoT)-based automated in-field monitoring to support crop improvement programs. Paper No. 2100696, In 2021 American Society of Agricultural and Biological Engineers (ASABE) Annual International Virtual Meeting (AIM), American Society of Agricultural and Biological Engineers.
  • Parhi, A., Sonar, C. R., Zhang, C., Rasco, B., Sankaran, S., Tang, J., and Sablani, S. S. 2020. Agar gel-based oxygen indicator for detection of defects in metal-oxide-coated multilayered food packaging films. Paper No. 2001337, In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.
  • Sankaran, S., Zhang, C., Hurst, P.J., Marzougui, A., Sivakumar, A.V.N., Li, J., Schnable, J., and Shi, Y. 2020. Investigating the potential of satellite imagery for high-throughput field phenotyping applications. In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V (Vol. 11414). International Society for Optics and Photonics (SPIE).
  • Zhang, C., Craine, W., Davis, J. B., Khot, L. R., Marzougui, A., Brown, J., Hulbert, S. H., and Sankaran, S. 2018. Detection of canola flowering using proximal and aerial remote sensing techniques. Proceeding SPIE 10664, Autonomous air and ground sensing systems for agricultural optimization and phenotyping (III).
  • Zhang, C., Pumphrey, M., Zhou, J., Gao, H., Zhang, Q., and Sankaran, S. 2017. Development of automated high-throughput phenotyping system for controlled environment studies, Paper No. 1700581, 2017 American Society of Agricultural and Biological Engineers (ASABE) Annual International Meeting (AIM), Spokane, WA.
  • Sankaran, S., Carter, A.H., Slaughter, D.C., Kirchhoff, H., Okamuro, J.K., Poland, J., and Kalcsits, L.A. 2016. Conference Summary Report on ‘Advances in Field-Based High-throughput Phenotyping and Data Management: Grains and Specialty Crops’.
  • Sankaran,  S., Khot, L.R., Quirós, J., Vandemark, G.J., and McGee, R.J. 2016. UAV-based high-throughput phenotyping in legume crops, Proceeding SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 98660G (May 17, 2016); doi: http://dx.doi.org/10.1117/12.2228550.
  • Zúñiga, C.E., Khot, L.R., Jacoby, P., and Sankaran, S. 2016. Remote sensing based water-use efficiency evaluation in sub-surface irrigated wine grape vines. Proceeding SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 98660O (May 17, 2016); doi: http://dx.doi.org/10.1117/12.2228791.
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