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Improvement of proximate data and calorific value assessment of bamboo through near infrared wood chips acquisition

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  • Sirisomboon, Panmanas
  • Funke, Axel
  • Posom, Jetsada

Abstract

In a previous study, a near infrared (NIR) spectroscopy model was developed using a spectra of ground bamboo samples. Although the previous report on ground bamboo described a good performance, operation in the power plant was found to be inconvenient due to preparation costs and labour required for the necessary preparation of ground samples. Thus, this study presents the comparison of the performance of an NIR model that was developed by direct scanning of bamboo chips to the previously developed model for ground samples. Special emphasis is put on the comparison of the spectral reproducibility. Bamboo chip models were developed based on PLS regression with variable selection methods in order to achieve the optimal model. The moisture content (MC) and ash content (A) of the developed bamboo chip models could be applied toward quality assurance. The volatile matter (VM) and fixed carbon (FC) models could be used for approximating predictions. The gross and net calorific value (GCV and NCV) models could be used for most applications. The root mean square (RMS) value of pre-treated spectra of different particle size had no statistically significant differences. The study’s findings indicate that the model developed using NIR spectroscopy protocol with wood chips spectra can be used as a classification tool and is an effective method for estimating bamboo chip energy quality. The big particle size of wood chips affect negatively the prediction model, however, it could be solved through spectral pre-processing technique, thus eliminating the need for grinding feedstock samples.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:147:y:2020:i:p1:p:1921-1931
    DOI: 10.1016/j.renene.2019.09.128
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    References listed on IDEAS

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    1. Gillespie, Gary D. & Everard, Colm D. & McDonnell, Kevin P., 2015. "Prediction of biomass pellet quality indices using near infrared spectroscopy," Energy, Elsevier, vol. 80(C), pages 582-588.
    2. Posom, Jetsada & Sirisomboon, Panmanas, 2017. "Evaluation of lower heating value and elemental composition of bamboo using near infrared spectroscopy," Energy, Elsevier, vol. 121(C), pages 147-158.
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    6. Posom, Jetsada & Shrestha, Amrit & Saechua, Wanphut & Sirisomboon, Panmanas, 2016. "Rapid non-destructive evaluation of moisture content and higher heating value of Leucaena leucocephala pellets using near infrared spectroscopy," Energy, Elsevier, vol. 107(C), pages 464-472.
    7. Pizzi, A. & Toscano, G. & Foppa Pedretti, E. & Duca, D. & Rossini, G. & Mengarelli, C. & Ilari, A. & Renzi, A. & Mancini, M., 2018. "Energy characteristics assessment of olive pomace by means of FT-NIR spectroscopy," Energy, Elsevier, vol. 147(C), pages 51-58.
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    Citations

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    Cited by:

    1. 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).
    2. 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.
    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 & 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.
    5. 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.
    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.

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