|Hively, Wells - Dean|
|VAN ES, H|
Submitted to: Soil and Tillage Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/11/2007
Publication Date: N/A
Interpretive Summary: Soil analysis traditionally relies upon expensive and time consuming lab chemistry to provide information on soil properties relating to fertility and soil quality. Recently, hyperspectral sensing techniques have been applied to soils, in which the reflectance of light in the visible and near infrared have been used to predict soil chemical content based upon correlation with known lab data. This method shows great potential for the rapid analysis of soil properties. Our project applied this principle to the analysis of traditional agronomic experiments, using hyperspectral reflectance data to analyze the effects of tillage on soil properties. We used traditional analysis of variance techniques, applied to both reflectance data in 1-nm wavelength increments, and to lad chemistry data. Results demonstrated that reflectance measurements detected highly significant differences between long-term plow-till and no-till management, mainly related to differences in organic matter content, Al, Mn, and pH. Hyperspectral sensing appears to provide an additional tool for the analysis ofr traditional agronomic experiments.
Technical Abstract: Visible-near infrared diffuse reflectance spectroscopy (VNIRDRS) is emerging as an effective method for rapid evaluation of soil properties and may be promising for the simultaneous determination of soil quality indicators. This study employed VNIRDRS to analyze treatment effects associated with long-term tillage experiments (plow-till vs. no-till) at three sites in New York State. Dried, ground soil samples collected from field plots were analyzed for VNIR reflectance as well as ten chemical and two physical parameters. Traditional analysis of variance (ANOVA) for complete block experiments was applied to reflectance data from each sequential 1-nm waveband from 420 to 2500 nm. Results revealed highly significant differences in soil brightness associated with tillage treatments at two of three sites, with no-till soils averaging 4% darker than plowed soils across measured wavelengths. ANOVA analysis of reflectance first derivatives demonstrated significant tillage-related variation in the shape of adsorption features. Physical analysis of the samples revealed increased organic matter, P, K, Mg and Mn, decreased Al, Ca, Cu, and Fe, lower pH, and increased small aggregate stability in the no-till treatments. Partial least squares regression (PLS) analysis was used to determine predictive relations between VNIRDRS data and measured soil parameters. Results indicated that soil organic matter, Al, Mn, and pH had the strongest association with tillage-related variability in VNIR reflectance. VNIRDRS shows promise for the assessment of important soil quality indicators, especially if based on larger calibration data sets.