Detection of the tulip breaking virus (TBV) in tulips using optical sensors

Detection of the tulip breaking virus (TBV) in tulips using optical sensors The tulip breaking virus (TBV) causes severe economic losses for countries that export tulips such as the Netherlands. Infected plants have to be removed from the field as soon as possible. There is an urgent need for a rapid and objective method of screening. In this study, four proximal optical sensing techniques for the detection of TBV in tulip plants were evaluated and compared with a visual assessment by crop experts as well as with an ELISA (enzyme immunoassay) analysis of the same plants. The optical sensor techniques used were an RGB color camera, a spectrophotometer measuring from 350 to 2500 nm, a spectral imaging camera covering a spectral range from 400 to 900 nm and a chlorophyll fluorescence imaging system that measures the photosynthetic activity. Linear discriminant classification was used to compare the results of these optical techniques and the visual assessment with the ELISA score. The spectral imaging system was the best optical technique and its error was only slightly larger than the visual assessment error. The experimental results appear to be promising, and they have led to further research to develop an autonomous robot for the detection and removal of diseased tulip plants in the open field. The application of this robot system will reduce the amount of insecticides and the considerable pressure on labor for selecting diseased plants by the crop expert. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Detection of the tulip breaking virus (TBV) in tulips using optical sensors

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Publisher
Springer US
Copyright
Copyright © 2010 by The Author(s)
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-010-9169-2
Publisher site
See Article on Publisher Site

References

  • Using spectral information from the NIR water absorption features for the retrieval of canopy water content
    Clevers, JGPW; Kooistra, L; Schaepman, ME
  • Remote sensing of the xanthophyll cycle and chlorophyll fluorescence in sunflower leaves and canopies
    Gamon, JA; Field, CB; Bilger, W; Björkman, O; Fredeen, AL; Peñuelas, J
  • Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins
    Gómez-Sanchis, J; Gómez-Chova, L; Aleixos, N; Camps-Valls, G; Montesinos-Herrero, C; Moltó, E; Blasco, J

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