IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i4p800-d1335225.html
   My bibliography  Save this article

NIR Spectroscopy as an Alternative to Thermogravimetric Analyzer for Biomass Proximate Analysis: Comparison of Chip and Ground Biomass Models

Author

Listed:
  • Bijendra Shrestha

    (Department of Agricultural Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Jetsada Posom

    (Department of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Panmanas Sirisomboon

    (Department of Agricultural Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Bim Prasad Shrestha

    (Department of Mechanical Engineering, School of Engineering, Kathmandu University, Dhulikhel P.O. Box 6250, Nepal
    Department of Bioengineering, University of Washington, Seattle, William H. Foege Building 3720, 15th Ave. NE, Seattle, WA 98195-5061, USA)

  • Pimpen Pornchaloempong

    (Department of Food Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Axel Funke

    (Institute of Catalysis Research and Technology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany)

Abstract

This study investigates the non-destructive analysis of proximate parameters (moisture content, MC; volatile matter, VM; fixed carbon, FC; ash content) in various chipped and ground biomass using a combination of destructive thermogravimetric analysis (TGA) and non-destructive near-infrared spectroscopy (NIRS) with partial least squares regression (PLSR). The thermogravimetric method determines proximate analysis data through TG and DTG curves, tracking biomass mass loss over time or temperature. NIRS scans chipped biomass in diffuse reflectance, and ground biomass in transflectance mode, covering the wavenumber range from 3595 to 12,489 cm −1 . PLSR-based models (Full-PLSR, GA-PLSR, SPA-PLSR, MP PLSR 5-range method, and MP PLSR 3-range method) are developed and evaluated based on R 2 P, RMSEP, and RPD. MC and FC models for chip biomass exhibit satisfactory performance, making them cautiously applicable in various applications, including research. Optimal models for MC and FC in chip biomass, constructed using GA-PLSR with the second derivative and Full-PLSR with a constant offset, yield high R 2 P values (0.8654 and 0.8773), low RMSEP values (0.85% and 2.12%), and high RPD values (2.9 and 3.0), indicating applicative capabilities. Other parameters such as MC and FC in ground biomass, as well as VM and ash content in both chip and ground biomass, are found suitable for rough screening. Model sensitivity, assessed by calculating LOQ, indicates high sensitivity for VM in both chip and ground biomass and FC in chip biomass, as the calculated LOQ value is lower than the minimum reference values used during model development. However, for the remaining parameters, LOQ values surpass the established minimum reference value, suggesting limitations in predicting samples below the calibration range. Continuous model enhancement incorporating an ample number of representative biomass samples and consistent validation with unknown samples are imperative for ensuring accurate predictions.

Suggested Citation

  • Bijendra Shrestha & Jetsada Posom & Panmanas Sirisomboon & Bim Prasad Shrestha & Pimpen Pornchaloempong & Axel Funke, 2024. "NIR Spectroscopy as an Alternative to Thermogravimetric Analyzer for Biomass Proximate Analysis: Comparison of Chip and Ground Biomass Models," Energies, MDPI, vol. 17(4), pages 1-27, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:800-:d:1335225
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/4/800/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/4/800/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bijendra Shrestha & Jetsada Posom & Panmanas Sirisomboon & Bim Prasad Shrestha, 2023. "Comprehensive Assessment of Biomass Properties for Energy Usage Using Near-Infrared Spectroscopy and Spectral Multi-Preprocessing Techniques," Energies, MDPI, vol. 16(14), pages 1-26, July.
    2. Sirisomboon, Panmanas & Funke, Axel & Posom, Jetsada, 2020. "Improvement of proximate data and calorific value assessment of bamboo through near infrared wood chips acquisition," Renewable Energy, Elsevier, vol. 147(P1), pages 1921-1931.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bijendra Shrestha & Jetsada Posom & Panmanas Sirisomboon & Bim Prasad Shrestha & Axel Funke, 2024. "Effect of Combined Non-Wood and Wood Spectra of Biomass Chips on Rapid Prediction of Ultimate Analysis Parameters Using near Infrared Spectroscopy," Energies, MDPI, vol. 17(2), pages 1-22, January.
    2. Pitak, Lakkana & Sirisomboon, Panmanas & Saengprachatanarug, Khwantri & Wongpichet, Seree & Posom, Jetsada, 2021. "Rapid elemental composition measurement of commercial pellets using line-scan hyperspectral imaging analysis," Energy, Elsevier, vol. 220(C).
    3. Aleksandra Minajeva & Algirdas Jasinskas & Rolandas Domeika & Edvardas Vaiciukevičius & Egidijus Lemanas & Stanisław Bielski, 2021. "The Study of the Faba Bean Waste and Potato Peels Recycling for Pellet Production and Usage for Energy Conversion," Energies, MDPI, vol. 14(10), pages 1-14, May.
    4. Bijendra Shrestha & Jetsada Posom & Panmanas Sirisomboon & Bim Prasad Shrestha, 2023. "Comprehensive Assessment of Biomass Properties for Energy Usage Using Near-Infrared Spectroscopy and Spectral Multi-Preprocessing Techniques," Energies, MDPI, vol. 16(14), pages 1-26, July.
    5. Bijendra Shrestha & Jetsada Posom & Pimpen Pornchaloempong & Panmanas Sirisomboon & Bim Prasad Shrestha & Hidayah Ariffin, 2024. "Near-Infrared Spectroscopy Modeling of Combustion Characteristics in Chip and Ground Biomass from Fast-Growing Trees and Agricultural Residue," Energies, MDPI, vol. 17(6), pages 1-27, March.
    6. Jeong, So-Yeon & Lee, Eun-Ju & Ban, Se-Eun & Lee, Jae-Won, 2021. "Near infrared spectroscopy model for analyzing chemical composition of biomass subjected to Fenton oxidation and hydrothermal treatment," Renewable Energy, Elsevier, vol. 172(C), pages 1341-1350.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:800-:d:1335225. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.