Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/16/2011
Publication Date: 5/1/2012
Citation: Aguilar, J.P., Evans, R.G., Daughtry, C.S. 2012. Performance assessment of the cellulose absorption index method for estimating crop residue cover. Journal of Soil and Water Conservation. 67(3): 202-210.
Interpretive Summary: The cellulose absorption index (CAI) is one of the best performing remote sensing techniques for estimating crop residue cover in the Midwest. The objective of this research is to assess the performance CAI in the Pacific Northwest and Central and Northern Great Plains regions on field pea, wheat, durum and barley residues including fallow field. Using field and laboratory set-up, CAI values were derived with varying percent crop residue cover and soil types. The authors found that CAI could distinguish crop residue cover from bare soil with good level of confidence. The CAI estimates percent coverage of field pea and fallow residues better than small grain crop residues. The performance of CAI was affected by the type of crop rather than by location and soil type in the regions. In addition, CAI shows some capability of estimating the amount of residue in the field. The results of this research improve the tools needed in effectively managing crop residue in the region for carbon sequestration, biofuel production, soil and water conservation, fertilizer and tillage management, and similar applications.
Technical Abstract: Accurate and quick field estimation of crop residues are important for carbon sequestration and biofuel production programs. Landscape-scale assessment of this vital information has promoted the use of remote sensing technology. The cellulose absorption index (CAI) technique has outperformed other indices for discriminating bare soil and crop residue in the Midwest, but has not been done in the Pacific Northwest and the Central and Northern Great Plains regions of the USA. The objective is to assess the performance of CAI in these regions. Malting barley (Hordeum vulgare L.), spring wheat (Triticum aestivum L.), durum (Triticum turgidum L.) and field pea (Pisum sativum L.), and fallow following spring wheat and proso millet (Panicum miliaceum L.) were used in the assessment. Using a portable ground-based spectroradiometer, transect line and photo-grid methods, crop residue cover was measured after 2009 harvest season. Samples were collected for laboratory analyses. Linear regression analysis showed CAI explained 58-72% of the variation in the residue cover. Field pea and fallow residue cover had better correlation with CAI than did small grain crop residues. Field and laboratory measurement of CAI showed that varying pea residue cover responded significantly different with other crop residues. The performance of CAI was affected by the type of crop rather than by location and soil type in the region. Among other measured parameters, percent crop residue cover, hemicellulose, and residue amount were most correlated with CAI. Results document CAI can quickly and effectively estimate percent residue cover in the regions.