Performance assessment of the cellulose absorption index method for estimating crop residue cover

Abstract

Accurate and quick field estimation of crop residues is important for carbon sequestration and biofuel production programs. Landscape-scale assessment of this vital information has resorted to 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 tested in the Pacific Northwest and the Central and Northern Great Plains regions of the United States. The objective of this study is to assess the performance of CAI in these regions. Malting barley (Hordeum vulgare L.), spring wheat (Triticum aestivum L.), durum (Triticum turgidum L.), 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, as well as transect line and photo-grid methods, crop residue cover was measured after the 2009 harvest season. Samples were collected for laboratory analyses. Linear regression analysis showed CAI explained 41% to 55% 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 than other crop residues. The performance of CAI was affected by the type of crop rather than by location and soil type in the regions. Among other measured parameters, percentage crop residue cover, hemicellulose, and residue amount were most correlated with CAI. Results document that CAI can quickly and effectively estimate percentage of residue cover in the regions.