The Identification of Forest Bio-Product Process Components through Near-Infrared Spectroscopy

UMaine Alert

Posted: April 19, 2024 - 1:32 PM

At approximately 9:24 a.m. on Friday, April 19, a University of Maine graduate student was struck by a university vehicle on Long Road at the University of Maine campus in Orono. The student reports that they are at a local hospital with minor injuries.

Emergency services, including the Orono Fire Department, University Volunteer Ambulance Corps, University of Maine Police Department, Orono Police Department and Penobscot County Sheriff’s Office responded to the scene.

The university vehicle involved in the incident was a Chevrolet Express van. It was being operated by a university employee.

Counseling services and support are available for students, faculty or staff who may have been affected. The Counseling Center can be reached at 207-581-1392 and the Dean of Students Office can be reached at 207-581-1406.

The scene has been cleared and Long Road is now accessible. An investigation is being conducted by the University of Maine Police Department with assistance from the Penobscot County Sheriff’s Office Crash Reconstruction Unit. Any witnesses to the incident are encouraged to contact Lt. Noel Santiago at noel.santiago@maine.edu.

Published: 2008

Author(s):

Darrell Donahue

Abstract:

Near-infrared spectroscopy (NIRS) has the potential to advance the productivity of the forest bio-refinery process by rapid identification of process bio-products, including the liquid extract and woody biomass. The potential exists so that composition identification via NIRS can be performed as an in-line process control operation. Before this technology is applied to the forest bio-refinery process, a NIR spectral database of solid wood chips and liquid extract solutions must be collected, developed and analyzed. Along with spectral data, physical differences of the woody biomass, including surface color, grain size and thickness were considered. The effects of viscosity, the amount of liquid scanned and the type of solvent used in solution were also investigated.

After developing the database of spectra, partial least squares (PLS) techniques were used in combination with selected pretreatments to develop calibration models. The calibration models were tested by scanning actual wood chips and liquid extracts removed during a laboratory-scale bio-refining process.

Wood chip spectra prior to pretreatment showed the most variation within the 1000-1350 nm range. Variation in the liquid extract spectra (high water content) was evident in the same range. Significant differences were seen when a water spectrum was subtracted from the liquid extract spectra. Initial calibrations based on known woody biomass components indicate positive validation results. These outcomes confirm the possibility for identification of extract components via NIRS, leading to the development of techniques that can be further tested in industry.

Keywords: Biofuels, Chemometrics, Data Analysis, Near Infrared

This research was supported by the NSF grants EPS-05-54545 and EEC-0734288.