OSA's Digital Library

Applied Spectroscopy

Applied Spectroscopy

| PUBLISHED BY SAS — AVAILABLE FROM SAS AND OSA

  • Vol. 65, Iss. 1 — Jan. 1, 2011
  • pp: 10–19

Discrimination of Corn from Monocotyledonous Weeds with Ultraviolet (UV) Induced Fluorescence

Bernard Panneton, Serge Guillaume, Guy Samson, and Jean-Michel Roger

Applied Spectroscopy, Vol. 65, Issue 1, pp. 10-19 (2011)


View Full Text Article

Acrobat PDF (2938 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations
  • Export Citation/Save Click for help

Abstract

In production agriculture, savings in herbicides can be achieved if weeds can be discriminated from crop, allowing the targeting of weed control to weed-infested areas only. Previous studies demonstrated the potential of ultraviolet (UV) induced fluorescence to discriminate corn from weeds and recently, robust models have been obtained for the discrimination between monocots (including corn) and dicots. Here, we developed a new approach to achieve robust discrimination of monocot weeds from corn. To this end, four corn hybrids (Elite 60T05, Monsanto DKC 26-78, Pioneer 39Y85 (RR), and Syngenta N2555 (Bt, LL)) and four monocot weeds (Digitaria ischaemum (Schreb.) I, Echinochloa crus-galli (L.) Beauv., Panicum capillare (L.), and Setaria glauca (L.) Beauv.) were grown either in a greenhouse or in a growth cabinet and UV (327 nm) induced fluorescence spectra (400 to 755 nm) were measured under controlled or uncontrolled ambient light intensity and temperature. This resulted in three contrasting data sets suitable for testing the robustness of discrimination models. In the blue-green region (400 to 550 nm), the shape of the spectra did not contain any useful information for discrimination. Therefore, the integral of the blue-green region (415 to 455 nm) was used as a normalizing factor for the red fluorescence intensity (670 to 755 nm). The shape of the normalized red fluorescence spectra did not contribute to the discrimination and in the end, only the integral of the normalized red fluorescence intensity was left as a single discriminant variable. Applying a threshold on this variable minimizing the classification error resulted in calibration errors ranging from 14.2% to 15.8%, but this threshold varied largely between data sets. Therefore, to achieve robustness, a model calibration scheme was developed based on the collection of a calibration data set from 75 corn plants. From this set, a new threshold can be estimated as the 85% quantile on the cumulative frequency curve of the integral of the normalized red fluorescence. With this approach the classification error was nearly constant (16.0% to 18.5%), thereby indicating the potential of UV-induced fluorescence to reliably discriminate corn from monocot weeds.

Virtual Issues
Vol. 6, Iss. 2 Virtual Journal for Biomedical Optics

Citation
Bernard Panneton, Serge Guillaume, Guy Samson, and Jean-Michel Roger, "Discrimination of Corn from Monocotyledonous Weeds with Ultraviolet (UV) Induced Fluorescence," Appl. Spectrosc. 65, 10-19 (2011)
http://www.opticsinfobase.org/as/abstract.cfm?URI=as-65-1-10


Sort:  Journal  |  Reset

References

References are not available for this paper.

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited