According to the Bioenergy Technologies Office (BETO), creating a robust next-generation domestic bioenergy industry is an essential pathway for providing sustainable renewable energy alternatives. Using non-food feedstocks, like corn-stover and forest residue, in the biorefineries doesn't affect the food supply chain. In the commercial-scale bioenergy operations, a significant development in the technological advancements is required to determine the biomass feedstock quality at the preprocessing stage. The penetrating ability of the x-rays helps study the big biomass bales, but the feedstock heterogeneity—physical size, shape, and chemical composition—poses a significant challenge during milling, conveyance, feeding, and biofuel conversion processes. The inherent complexity introduced during harvesting and bailing makes the reconstruction and interpretation of baled biomass materials from x-ray data time consuming, laborious, and expensive. The presence of similar low-dense materials showed a small contrast difference in the x-ray images, which makes the characterization based on the x-ray attenuation values not promising. This paper focuses on using the shape and texture properties extracted with image processing techniques to characterize the different tissue samples in the biomass bales.
This document was originally published in AIChE Annual Meeting, Conference Proceedings, 2020 by the American Institute of Chemical Engineers. Copyright restrictions may apply.
Kancharla, Rahul Reddy; Smith, William A.; Barney Smith, Elisa H.; and Klinger, Jordan L.. (2020). "Anatomical Fraction Segmentation in the Biomass Bales". AIChE Annual Meeting, Conference Proceedings, 2020, .