BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:Asia/Kolkata X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT UID:196@cds.iisc.ac.in DTSTART;TZID=Asia/Kolkata:20260528T160000 DTEND;TZID=Asia/Kolkata:20260528T170000 DTSTAMP:20260518T113936Z URL:https://cds.iisc.ac.in/events/seminar-cds-102-may-28th-0400-hyperspect ral-imaging-for-early-detection-of-plant-stress-in-soybean/ SUMMARY:{Seminar} @ CDS: #102\, May 28th: 04:00: "Hyperspectral Imaging for Early Detection of Plant Stress in Soybean." DESCRIPTION:Department of Computational and Data Sciences\nDepartment Semin ar\n\n\n\nSpeaker : Dr. Febina Mathew\, Associate Professor\, North Dakota State University\, Fargo\, ND\, USA\nTitle : Hyperspectral Imaging for Ea rly Detection of Plant Stress in Soybean\nDate &\; Time: May 28th\, 202 6 (Thursday)\, 04:00 PM\nVenue : # 102\, CDS Seminar Hall\n\n\n\nABSTRACT: \n\nSudden death syndrome (SDS) is one of the diseases affecting soybean ( Glycine max L.) production worldwide and can lead to severe yield losses. The pathogen infects soybean roots under wet soil conditions\, but plants often remain visually healthy during the initial stages of infection. Visi ble leaf symptoms generally appear much later in the growing season\, maki ng timely diagnosis difficult using conventional scouting methods. This st udy explored the use of hyperspectral imaging for detecting early physiolo gical changes associated with SDS before visible symptoms develop. Three s oybean genotypes were evaluated under controlled growth chamber conditions (23 ± 1 °C with a 16 h photoperiod). The potting mix was inoculated wit h the fungus\, F. virguliforme\, and soybean seeds were planted under cont rolled moisture conditions to promote disease development. Hyperspectral i mages of soybean leaves were collected 12 and 23 days after planting using a Specim IQ hyperspectral camera. The infected plants showed differences in spectral reflectance compared to healthy controls\, particularly in the visible\, red-edge\, and near-infrared wavelength regions. Increased refl ectance in the visible range is associated with reduced chlorophyll absorp tion\, while shifts in the red-edge region suggest physiological stress re sponses occurring before visible disease symptoms appear. These findings d emonstrate that hyperspectral sensing can capture changes in plants during the early stages of pathogen infection. The study highlights the potentia l of hyperspectral imaging for plant disease diagnosis\, enabling engineer s and researchers to develop automated sensing systems for crop stress ide ntification before symptoms are visible to the human eye.\n\nBIO:\nDr. Feb ina Mathew is a Plant Pathologist and an Associate Professor with the Depa rtment of Plant Pathology\, Microbiology\, and Biotechnology at North Dako ta State University\, Fargo\, ND\, USA. She earned a B.Tech. in Biotechnol ogy and Biochemical Engineering from the Indian Institute of Technology\, Kharagpur\, India\, followed by an M.S. in Plant Pathology and a Ph.D. in Plant Pathology from North Dakota State University.\n\nDr. Mathew has rece ived numerous honors and awards recognizing excellence in research\, teach ing\, communication\, and professional service. These include the APS Cert ificate of Achievement for International Plant Pathology Research\, Early Career Award from the American Phytopathological Society North Central Div ision\, the APS Schroth Faces of the Future Award (2017)\, the Innovation in Teaching Award from NDSU\, and multiple team awards for national and in ternational contributions in plant pathology and agricultural communicatio n.\nHer research program focuses on the biology of soybean pathogens and P homopsis stem canker of sunflower\, with an emphasis on understanding host –pathogen interactions and developing effective disease management strat egies.\n\nHost Faculty: Prof. Debnath Pal\n\n\n\nALL ARE WELCOME CATEGORIES:Events,Talks END:VEVENT BEGIN:VTIMEZONE TZID:Asia/Kolkata X-LIC-LOCATION:Asia/Kolkata BEGIN:STANDARD DTSTART:20250528T160000 TZOFFSETFROM:+0530 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE END:VCALENDAR