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Evaluation of CAI Method of Crop Residue Assessment as a Tool for Soil and Water Conservation Management in the Dryland Agriculture of the Northern Great Plains

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1008529.(doi:10.13031/2013.29639)
Authors:   Jonathan P Aguilar, Robert G Evans, Craig S.T Daughtry
Keywords:   crop residue, remote sensing, CAI, cellulose absorption index, residue cover, NGP, Northern Great Plains, spectral properties

The USDA Agricultural Research Station-Hydrology and Remote Sensing Laboratory (ARS-HRSL) had developed a remote sensing method capable of measuring crop residue cover. This method utilized the cellulose absorption index (CAI) at the short wave infrared region of the spectrum to differentiate soil from plant residues. The method worked well in humid areas in Iowa, where it was calibrated and tested, but it had not been tested in the ecologically fragile, semi-arid conditions of the Northern Great Plains (NGP) region. The effectiveness of CAI in differentiating crop residue from soil was affected by different soil and residue moisture levels and soil spectral properties, and needed to be evaluated in the NGP agricultural setting. This study aimed to assess the applicability of the CAI method in the NGP region across various dryland crops and soil types. Dryland crops, such as malting barley, spring wheat, durum, peas and fallow under conventional and ecological tillage systems were evaluated using a multispectral camera. CAI values were compared to visual measurements of crop residue cover. Initial results showed that the CAI method can effectively differentiate a bare soil from the various crop residues. Further analyses are being conducted to evaluate and relate CAI values with percent area of crop residue cover with respect to primary tillage systems. The results of this study could improve rapid assessment of soil and water conservation practices in the NGP, as well as other regions, especially if used with aerial and satellite multispectral imagery.

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