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Light Reflectance and Remote Sensing of Weeds in Agronomic and Horticultural Crops

Published online by Cambridge University Press:  12 June 2017

R. M. Menges ,
P. R. Nixon  and
A. J. Richardson
R. M. Menges
Affiliation:
Agric. Res., Sci. Ed. Admin., U.S. Dep. Agric., Weslaco, TX 78596
P. R. Nixon
Affiliation:
Agric. Res., Sci. Ed. Admin., U.S. Dep. Agric., Weslaco, TX 78596
A. J. Richardson
Affiliation:
Agric. Res., Sci. Ed. Admin., U.S. Dep. Agric., Weslaco, TX 78596
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Abstract

Plant canopy reflectance over the 0.45- to 1.25-μm wavelength (WL) of weed species and crops was recorded with a field spectroradiometer to evaluate the possible use of remote sensing to distinguish weeds from crops. Weed and weed-crop species reflectance differences were generally greater at the 0.85 μm WL in the near-infrared spectral region than at the 0.55 μm WL in the visible region, indicating that color infrared (CIR) aerial photography may be useful to detect weed populations in crops. Canopy reflectance data were more directly related to photographic differences in weed-crop images than were single leaf or inflorescence reflectance data. Aerial photography at altitudes of 610 to 3050 m distinguished climbing milkweed (Sarcostemma cyancboides ♯ SAZCY) in orange [Citrus sinensis (L.) Osbeck. ‘Valencia’) trees; ragweed parthenium (Parthenium hysterophorus L. ♯ PTNHY) in carrot (Daucus carota L., var. sativa ‘Long Imperator’); johnsongrass [Sorghum halepense (L.) Pers. ♯ SORHA) in cotton (Gossypium hirsutum L. ‘CP 3774’) and in sorghum (Sorghum bicolor L. Moench. ‘Oro’); London rocket (Sisymbrium irio L. ♯ SSYIR) in cabbage; and Palmer amaranth (Amaranthus palmeri S. Wats. ♯ AMAPA) in cotton. Johnsongrass was also detectable with CIR film in maturing grain sorghum from 18 290 m. Detection of weed species in crops was aided by differential stages of inflorescence and senescence, and by the chlorophyll content, color, area, intercellular space, and surface characteristics of the leaves. Discrete plant community areas were determined by computer-based image analyses from a 1:8000-scale positive transparency with the efficiency of 82, 81, 68, and 100% for Palmer amaranth, johnsongrass, sorghum, and cotton, respectively. The computer analyses should permit discrete aerial surveys of weed-crop communities that are necessary for integrated crop management systems.

Keywords

Leaf reflectanceleaf characteristicsphotomicrographySAZCYPTNHYSORHASSYIRAMAPA
Type
Special Topics
Information
Weed Science , Volume 33 , Issue 4 , July 1985 , pp. 569 - 581
Copyright
Copyright © 1985 by the Weed Science Society of America 

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References

Literature Cited

1. Benton, A. R. Jr. and Newnan, R. M. 1976. Color aerial photography for aquatic plant monitoring. J. Aquat. Plant Manage. 14:14–16.Google Scholar
2. Bogucki, J., Swendling, G. K., and Madden, M. 1980. Remote sensing to monitor water chestnut growth in Lake Champlain. J. Soil and Water Conserv. Pages 79–81.Google Scholar
3. Esau, K. 1977. Anatomy of seed plants. John Wiley & Sons, New York. 555 pp.Google Scholar
4. Everitt, J. W., Ingle, S. J., Gausman, H. W., and Mayeux, H. S. Jr. 1984. Detection of false broomweed (Ericameria austrotexana) by aerial photography. Weed Sci. 32:621–624.Google Scholar
5. Gausman, H. W., Allen, W. A., Cardenas, R., and Richardson, A. J. 1970. Relation of light reflectance to histological and physical evaluations of cotton leaf maturity (Gossypium hirsutum L.). Appl. Opt. 9:545–552.Google Scholar
6. Gausman, H. W. and Allen, W. A. 1973. Optical parameters of leaves and their structure. Remote Sens. Environ. 1:19–22.Google Scholar
7. Gausman, H. W., Allen, W. A., and Wiegand, C. L. 1972. Plant factors affecting electromagnetic radiation. Soil and Water Conservation Res. Div., Agric. Res. Serv., U.S. Dep. Agric. Rpt. 432. 41 pp.Google Scholar
8. Gausman, H. W. and Allen, W. A. 1973. Optical parameters of leaves of 30 plant species. Plant Physiol. 32:57–62.Google Scholar
9. Gausman, H. W., Menges, R. M., Escobar, D. E., Everitt, J. H., and Bowen, R. L. 1977. Pubescence effects spectra and imagery of silverleaf sunflower (Helianthus argophyllus Torr. & Gray). Weed Sci. 25:437–440.Google Scholar
10. Gausman, H. W., Menges, R. M., Richardson, A. J., Walter, H., Rodriquez, R. R., and Tamez, S. 1981. Optical parameters of leaves of seven weed species. Weed Sci. 29:24–26.Google Scholar
11. Hart, W. G. 1978. Remote sensing in horticulture. Proc. Int. Soc. Citric. Pages 168–171.Google Scholar
12. Jacobsen, B. J. and Hooper, H. J. 1981. Influence of herbicides on Aphanomyces root rot of peas. Plant Dis. 65(1):11–16.Google Scholar
13. Jensen, W. A. 1962. Botantical histochemistry. 408 pp. W. H. Freeman & Co., San Francisco, CA.Google Scholar
14. Kondrat, K. Ya. and Fedchenko, P. P. 1979. Spectral reflectivity of weeds and useful plants. Dokl. 248(6): 1318–1320.Google Scholar
15. Levitt, J. 1975. Effects of small water stresses on cell turgor and intercellular space. Physiol Plant. 34:273–279.Google Scholar
16. Martyn, R. D. and Snell, W. W. 1982. Lake Conroe aquatic vegetation survey. I. Aerial color infrared photography-baseline map. 1979. TAES MP-1502.Google Scholar
17. Moss, R. A. 1951. Absorption spectra of leaves. Ph.D. Thesis. Iowa State Univ., Ames.Google Scholar
18. Pearman, G. I. 1966. The reflection of visible radiation from leaves of some western Australian species. Aust. J. Biol. Sci. 19:97–103.CrossRefGoogle Scholar
19. Richardson, A. J., Weigand, C. L., Gausman, H. W., Cuellar, J. A., and Gerberman, A. H. 1975. Plant, soil, and shadow reflectance components of row crops. Photogram. Engin. 1401–1407.Google Scholar
20. Richardson, A. J., Escobar, D. E., Gausman, H. W., and Everitt, J. H. 1981. Use of LANDSAT-2 data technique to estimate silverleaf sunflower infestation. Machine Processing of Remotely Sensed Data Symposium, Purdue Univ. Pages 676–683.Google Scholar
21. Richardson, A. J. 1981. Measurement of reflectance factors under daily and intermittent irradiance variations. Appl. Opt. 20(6):3336–3340.CrossRefGoogle ScholarPubMed
22. Richardson, A. J., Menges, R. M., and Nixon, P. R., 1985. Detection of noxious weed infestations in crops using video remote sensing. Photogram, Eng. and Remote Sens. (In press).Google Scholar
23. Sinclair, T. R., Hoffer, R. M., and Schreiber, M. M. 1971. Reflectance and internal structure of leaves from several crops during the growing season. Agron. J. 63:864–868.Google Scholar
24. Walter, H. and Koch, W. 1981. Optical parameters of leaves of crops and weeds. Int'l. Coloquium-Int'l Soc. Photogram, and Remote Sens. Avignon, France. 225–232.Google Scholar
25. Willstatter, R. and Stoll, A. 1918. Untersuchungen uber die Assimilation der Kohlensaure. Springer-Verlag, Berlin. Page 122.Google Scholar
26. Wooley, J. T. 1971. Reflectance and transmittance of light by leaves. Plant Physiol. 47:656–662.Google Scholar