Hostname: page-component-745bb68f8f-b6zl4 Total loading time: 0 Render date: 2025-01-08T07:52:27.932Z Has data issue: false hasContentIssue false
  • English
  • Français

Non-destructive Measurements of Biomass in Millet, Cowpea, Groundnut, Weeds and Grass Swards using Reflectance, and their Application for Growth Analysis

Published online by Cambridge University Press:  03 October 2008

A. Buerkert ,
P. R. Lawrence ,
J. H. Williams  and
H. Marschner
A. Buerkert
Affiliation:
International Centre for Research in the Semi-Arid Tropics (ICRISAT) Sahelian Centre, BP 12404, Niamey, Niger
P. R. Lawrence
Affiliation:
International Centre for Research in the Semi-Arid Tropics (ICRISAT) Sahelian Centre, BP 12404, Niamey, Niger
J. H. Williams
Affiliation:
International Centre for Research in the Semi-Arid Tropics (ICRISAT) Sahelian Centre, BP 12404, Niamey, Niger
H. Marschner
Affiliation:
International Centre for Research in the Semi-Arid Tropics (ICRISAT) Sahelian Centre, BP 12404, Niamey, Niger
Get access Rights & Permissions [Opens in a new window]

Summary

A simple hand-held reflectometer was used to estimate the shoot dry matter of pearl millet (Pennisetum glaucum), groundnut (Arachis hypogaea), cowpea (Vigna unguiculata), weeds and grass swards non-destructively. While the instrument was able to predict shoot dry matter well for single, standing millet and cowpea plants and proved useful for a growth analysis of millet, its reliability was unsatisfactory for groundnut. For millet, the slope of two separate regressions between the difference of reflectance ratios and shoot dry matter, taken 10 days apart, was almost identical. This suggests a possible simplification in future crop growth models. The usefulness of the instrument for estimating dry matter in natural species mixtures such as weeds and grasses depended on the homogeneity of the mixture and the uniformity of their physiological state.

Medición de la biomasa utilizando la reflexión

Type
Research Article
Information
Experimental Agriculture , Volume 31 , Issue 1 , January 1995 , pp. 1 - 11
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aase, J. K. & Tanaka, D. L. (1991). Reflectances from four wheat residue cover densities as influenced by three soil backgrounds. Agronomy Journal 83:753–757.CrossRefGoogle Scholar
Asrar, G., Fuchs, M., Kanemasu, E. T. & Hatfield, J. L. (1984). Estimating absorbed photosyntheticradiation and leaf area index from spectral reflectance in wheat. Agronomy Journal 76:300–306.Google Scholar
Colwell, J. E. (1974). Vegetation canopy reflectance. Remote Sensing of Environment 3:175–183.CrossRefGoogle Scholar
Food and Agriculture Organization of the United Nations-United Nations Education Scientific and Cultural Organization (1988). Soil Map of the World. Paris: UNESCO.Google Scholar
Frederiksen, P. & Lawesson, J. E. (1992). Vegetation types and patterns in Senegal based on multivariate analysis of field and NOAA-AVHRR satellite data. Journal of Vegetation Science 3:535–544.CrossRefGoogle Scholar
Lawes Agricultural Trust (1987). GENSTAT 5 Reference Manual. Oxford: Oxford University Press.Google Scholar
Mayhew, P. W., Burns, M. D. & Houston, D. C. (1984). An inexpensive and simple spectrophotometer for measuring grass biomass in the field. Oikos 43:62–67.CrossRefGoogle Scholar
Michels, K., Sivakumar, M. V. K. & Allison, B. E. (1993). Wind erosion and induced damage to pearl millet production in the Southern Sahelian Zone. Agricultural and Forest Meteorology 67:65–77.CrossRefGoogle Scholar
Mitchell, A. R., Pinter, P. J., Guerrero, J. N., Fernandez, C. B. & Marble, V. L. (1990). Spectral reflectance measurements of alfalfa under sheep grazing. Agronomy Journal 82:1098–1103.CrossRefGoogle Scholar
Nageswara, R. C., Williams, J. H., Rao, V. M. & Wadia, K. D. R. (1992). A hand-held red-infrared radiometer for measuring radiation interception by crop canopies. Field Crops Research 29:353–360.Google Scholar
Nutter, F. W. (1989). Detection and measurement of plant disease gradients in peanut with a multispectral radiometer. Phytopathology 79:958–963.Google Scholar
Payne, W. A., Wendt, C. W., Hossner, L. R. & Gates, C. E. (1991). Estimating pearl millet leaf area and specific leaf area. Agronomy Journal 83:937–941.CrossRefGoogle Scholar
Soil Management Support Services (1988). Keys to Soil Taxonomy. Technical Monograph 6. Ithaca, NY: Department of Agronomy, Cornell University.Google Scholar
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8:127–150.CrossRefGoogle Scholar
Tucker, C. J., Elgin, J. H., McMurtrey, J. E., Fan, C. J. (1979). Monitoring corn and soybean crop development with hand-held radiometer spectral data. Remote Sensing of Environment 8:237–248.Google Scholar
Tucker, C. J. & Sellers, P. J. (1986). Satellite remote sensing of primary production. International Journal of Remote Sensing 7:1395–1416.Google Scholar
West, L. T., Wilding, L. P., Landeck, J. K. & Calhoun, F. G. (1984). Soil Survey of the ICRJSAT Sahelian Center, Niger, West Agrica. College Station, Texas: Soil and Crop Sciences Department/TropSoils, Texas A&M University System.Google Scholar
Zhu, Z. & Evans, D. L. (1992). Mapping midsouth forest distributions. Journal of Forestry 90(12):27–30.Google Scholar