Measurements of Mouldboard Plow Draft: I. Spectrum Analysis and Filtering

Measurements of Mouldboard Plow Draft: I. Spectrum Analysis and Filtering Measurements of mouldboard plow draft can potentially provide a useful tool for continuously mapping, as a surrogate variable, crop limiting soil properties such as soil strength/compaction. Numerous researchers have shown that loading on tillage tools can be periodic. One source of higher frequency periodic loading has been related to failure modes in the soil. Lower frequency periodic loading on tillage tools, assuming tillage depth is relatively constant, more often reflects local spatial variability in soil physical properties such as soil moisture, soil texture, organic matter, and/or soil strength/compaction. This study presents a spectrum and cross-spectrum analysis of mouldboard draft recorded during normal fall plowing operations along adjacent transects. One objective of this study was to determine the dominant periodic components in order to elucidate meaningful frequencies which might be better related to variation in soil physical properties. Spectral densities were generally dominated by signals with a few cycles per 300-m transect. The cross-amplitude and squared coherency between draft recorded on adjacent transects provided further indication of the frequencies which characterized the signals because they provide an indication of correlation as a function of frequency. Spatial dependence in the data was quantified using spatial autocorrelation and cross-correlation. An additional objective was to use the spectral information to help design more physically meaningful filters for the raw draft data. Taking the Fast Fourier Transform of the raw draft data and filtering in the frequency domain using an optimal filter informed via the spectrum and cross-spectrum analysis, provided a convenient method for isolating a more physically meaningful signal. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Measurements of Mouldboard Plow Draft: I. Spectrum Analysis and Filtering

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Publisher
Springer Journals
Copyright
Copyright © 2002 by Kluwer Academic Publishers
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.
10.1023/A:1015502924508
Publisher site
See Article on Publisher Site

Abstract

Measurements of mouldboard plow draft can potentially provide a useful tool for continuously mapping, as a surrogate variable, crop limiting soil properties such as soil strength/compaction. Numerous researchers have shown that loading on tillage tools can be periodic. One source of higher frequency periodic loading has been related to failure modes in the soil. Lower frequency periodic loading on tillage tools, assuming tillage depth is relatively constant, more often reflects local spatial variability in soil physical properties such as soil moisture, soil texture, organic matter, and/or soil strength/compaction. This study presents a spectrum and cross-spectrum analysis of mouldboard draft recorded during normal fall plowing operations along adjacent transects. One objective of this study was to determine the dominant periodic components in order to elucidate meaningful frequencies which might be better related to variation in soil physical properties. Spectral densities were generally dominated by signals with a few cycles per 300-m transect. The cross-amplitude and squared coherency between draft recorded on adjacent transects provided further indication of the frequencies which characterized the signals because they provide an indication of correlation as a function of frequency. Spatial dependence in the data was quantified using spatial autocorrelation and cross-correlation. An additional objective was to use the spectral information to help design more physically meaningful filters for the raw draft data. Taking the Fast Fourier Transform of the raw draft data and filtering in the frequency domain using an optimal filter informed via the spectrum and cross-spectrum analysis, provided a convenient method for isolating a more physically meaningful signal.

Journal

Precision AgricultureSpringer Journals

Published: Oct 8, 2004

References

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