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Forest Products Laboratory
One Gifford Pinchot Drive
Madison, WI 53726-2398
Phone: (608) 231-9200
Fax: (608) 231-9592


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Title: Assessing plant biomass properties for their handling and conversion performances using machine learning

Source: Res. in Prog. FPL-RIP- 4851-024. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory. 2 p.

Author(s)Mani, Sudhagar ; Bergman, Richard ; Sahoo, Kamalakanta

Publication Year: 2020  View PDF »

Related Publications: view

Category: Research In Progress

Abstract: The fields of machine learning and data analytics have led to advances in linking vast data sets into useful information for improved efficiency and reduced cost. Major challenges in effectively utilizing and standardizing plant biomass are spatial variability and natural heterogeneity of biomass structures. This variability causes poor flowability, inconsistent conversion yields, and operational bottlenecks at the biorefinery (Li et al. 2016). In this project, we propose to develop a robust machine learning modeling framework to relate plant biomass property variability at the tissue levels by a system linking rapid near-infrared (NIR) spectroscopy and hyperspectral imaging (HSI) (Schimleck et al. 2018) with feedstock handling and conversion performances. The system will be designed to optimize conversion-ready feedstock for a biorefinery and its successful operation.

Keywords: Machine Learning; Artificial Neural Network (ANN); biofuel/bioproducts; spectroscopy-hyperspectral imaging (HSI); handling properties; biomass conversion; biorefinery

Publication Review Process: Non-Refereed (Other)

File size: 448 kb(s)

Date posted: 04/09/2020
RITS Product ID: 97530
Current FPL Scientist associated with this product
Bergman, Richard
Research Forest Products Technologist

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