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International Journal of Agronomy
Volume 2017, Article ID 4813147, 9 pages
Research Article

Prediction of Canola Residue Characteristics Using Near-Infrared Spectroscopy

1Department of Crop and Soil Sciences, Washington State University, 115 Johnson Hall, Pullman, WA 99164-6420, USA
2Northwest Sustainable Agroecosystems Research Unit, USDA-ARS, 215 Johnson Hall, Pullman, WA 99164-6421, USA

Correspondence should be addressed to Tami L. Stubbs; ude.usw@sbbutslt

Received 27 January 2017; Accepted 8 March 2017; Published 5 April 2017

Academic Editor: Manuel Tejada

Copyright © 2017 Tami L. Stubbs and Ann C. Kennedy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Little work has been done to characterize and quantify the residue traits affecting decomposition of winter and spring canola (Brassica napus L.) residue in dryland farming systems of the Pacific Northwest United States. Traditional methods of characterizing residue fiber and nutrients are time-consuming and expensive and require large quantities of chemical reagents. The goal of this research was to determine whether near-infrared spectroscopy (NIRS) could accurately predict neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), carbon (C), and nitrogen (N) of canola stems, litter, and roots and decomposition of canola stems. Canola residue varied in decomposition, fiber, and nutrients by year, location, and type. NIRS predictions were successful for NDF and ADF in 2011 (standard error of prediction ; ) and NDF, ADF, and N in 2012 (; ). Other predictions for residue fiber and nutrient characteristics were considered moderately successful. Prediction of canola residue decomposition with NIRS was useful for screening purposes. Near-infrared spectroscopy shows promise for rapidly and reproducibly predicting some canola residue fiber and nutrient traits and may be useful for estimating residue decomposition potential in dryland conservation cropping systems.