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ARS Home » Plains Area » Mandan, North Dakota » Northern Great Plains Research Laboratory » Research » Publications at this Location » Publication #305564

Title: Identification of nodes and internodes of chopped biomass stems by Image analysis using profile curvature and slope

item POTHULA, A - North Dakota State University
item IGATHINATHANE, C - North Dakota State University
item Kronberg, Scott
item Hendrickson, John

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 2/23/2014
Publication Date: 3/28/2014
Citation: Pothula, A.K., Igathinathane, C., Kronberg, S.L., Hendrickson, J.R. 2014. Identification of nodes and internodes of chopped biomass stems by Image analysis using profile curvature and slope. Meeting Proceedings. Paper Number: SD14-054.

Interpretive Summary:

Technical Abstract: Morphological components of biomass stems vary in their chemical composition and they can be better utilized when processed after segregation. Within the stem, nodes and internodes have significantly different compositions. The internodes have low ash content and are a better feedstock for bioenergy and biofuel application than are the nodes. With chopped stems, nodes and internodes are difficult to segregate by simpler mechanical means, even though they are clearly different in visual appearance. Digital image analysis can be used to extract the total profile of chopped stems laid out as a single layer. Analysis of the profile identifies the presence or absence of protrusions and, hence, the identification of nodes and internodes. Two algorithms, namely (1) Fourier analysis based curvature, and (2) analytical geometry based slope were developed in a MATLAB environment and tested with chopped stems of big bluestem. Digital images of the samples were obtained using a digital scanner at 600 DPI resolution. Both algorithms transformed the object profile into curves or slopes that resulted in peaks indicating the presence of corners (major peaks) and nodular ring bumps (minor peaks). Presence of two or more peaks indicated nodes and otherwise internodes. Both methods successfully identified the nodes and internodes without any misclassification and produced similar results; however, the geometric slope method is direct, simpler, and probably allows for faster computation.