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UID:196@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20260526T160000
DTEND;TZID=Asia/Kolkata:20260526T170000
DTSTAMP:20260523T144320Z
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:Change in Date : {Seminar} @ CDS: #102\, May 28th: 04:00: "Hyperspe
 ctral 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 &amp\; Time: May 26th\, 202
 6 (Tuesday)\, 04:00 PM\nVenue : # 102\, CDS Seminar Hall\n\n\n\nABSTRACT:\
 n\nSudden death syndrome (SDS) is one of the diseases affecting soybean (G
 lycine max L.) production worldwide and can lead to severe yield losses. T
 he pathogen infects soybean roots under wet soil conditions\, but plants o
 ften remain visually healthy during the initial stages of infection. Visib
 le leaf symptoms generally appear much later in the growing season\, makin
 g timely diagnosis difficult using conventional scouting methods. This stu
 dy explored the use of hyperspectral imaging for detecting early physiolog
 ical changes associated with SDS before visible symptoms develop. Three so
 ybean genotypes were evaluated under controlled growth chamber conditions 
 (23 ± 1 °C with a 16 h photoperiod). The potting mix was inoculated with
  the fungus\, F. virguliforme\, and soybean seeds were planted under contr
 olled moisture conditions to promote disease development. Hyperspectral im
 ages of soybean leaves were collected 12 and 23 days after planting using 
 a Specim IQ hyperspectral camera. The infected plants showed differences i
 n spectral reflectance compared to healthy controls\, particularly in the 
 visible\, red-edge\, and near-infrared wavelength regions. Increased refle
 ctance in the visible range is associated with reduced chlorophyll absorpt
 ion\, while shifts in the red-edge region suggest physiological stress res
 ponses occurring before visible disease symptoms appear. These findings de
 monstrate that hyperspectral sensing can capture changes in plants during 
 the early stages of pathogen infection. The study highlights the potential
  of hyperspectral imaging for plant disease diagnosis\, enabling engineers
  and researchers to develop automated sensing systems for crop stress iden
 tification before symptoms are visible to the human eye.\n\nBIO:\nDr. Febi
 na Mathew is a Plant Pathologist and an Associate Professor with the Depar
 tment of Plant Pathology\, Microbiology\, and Biotechnology at North Dakot
 a State University\, Fargo\, ND\, USA. She earned a B.Tech. in Biotechnolo
 gy and Biochemical Engineering from the Indian Institute of Technology\, K
 haragpur\, India\, followed by an M.S. in Plant Pathology and a Ph.D. in P
 lant Pathology from North Dakota State University.\n\nDr. Mathew has recei
 ved numerous honors and awards recognizing excellence in research\, teachi
 ng\, communication\, and professional service. These include the APS Certi
 ficate of Achievement for International Plant Pathology Research\, Early C
 areer Award from the American Phytopathological Society North Central Divi
 sion\, the APS Schroth Faces of the Future Award (2017)\, the Innovation i
 n Teaching Award from NDSU\, and multiple team awards for national and int
 ernational contributions in plant pathology and agricultural communication
 .\nHer research program focuses on the biology of soybean pathogens and Ph
 omopsis 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
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DTSTART:20250526T160000
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