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Near Infrared Reflectance Spectroscopy (NIRS) for rapid determination of biochemical methane potential of plant biomass

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  • Triolo, Jin M.
  • Ward, Alastair J.
  • Pedersen, Lene
  • Løkke, Mette M.
  • Qu, Haiyan
  • Sommer, Sven G.

Abstract

Determination of biochemical methane potential (BMP) by fermentation tests is time-consuming and costly, and therefore not useful for operators of full-scale biogas digesters. A great advantage of NIRS in determining BMP is the reduction in measurement time from at least one month for chemical determination to a couple of minutes for production of near infrared spectroscopy (NIRS) spectra. An innovative NIRS method that can be used as an alternative to current BMP tests was developed in this study. We tested the Partial Least Squares (PLS) model for a rapid determination of BMP using NIRS by applying a series of pre-processing methods with caution. A total of 88 plant biomass samples of a wide variety were used for model prediction. The standard error of the best PLS model was 37 CH4 NLkg−1 VS, where BMP of the test set was between 136.2 and 477.9 CH4 NLkg−1 VS. Coefficient of determination (R2) and residual prediction deviation (RPD) were 0.84 and 2.49, respectively. This shows that the new NIRS model is moderately successful in application and could be an alternative modern tool to overcome the problems of current BMP methods.

Suggested Citation

  • Triolo, Jin M. & Ward, Alastair J. & Pedersen, Lene & Løkke, Mette M. & Qu, Haiyan & Sommer, Sven G., 2014. "Near Infrared Reflectance Spectroscopy (NIRS) for rapid determination of biochemical methane potential of plant biomass," Applied Energy, Elsevier, vol. 116(C), pages 52-57.
    • Handle: RePEc:eee:appene:v:116:y:2014:i:c:p:52-57
    DOI: 10.1016/j.apenergy.2013.11.006
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    References listed on IDEAS

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    2. Posom, Jetsada & Saechua, Wanphut & Sirisomboon, Panmanas, 2017. "Evaluation of pyrolysis characteristics of milled bamboo using near-infrared spectroscopy," Renewable Energy, Elsevier, vol. 103(C), pages 653-665.
    3. Peng, Wei & Beggio, Giovanni & Pivato, Alberto & Zhang, Hua & Lü, Fan & He, Pinjing, 2022. "Applications of near infrared spectroscopy and hyperspectral imaging techniques in anaerobic digestion of bio-wastes: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    4. Sohoo, Ihsanullah & Ritzkowski, Marco & Heerenklage, Jörn & Kuchta, Kerstin, 2021. "Biochemical methane potential assessment of municipal solid waste generated in Asian cities: A case study of Karachi, Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Catenacci, Arianna & Santus, Anna & Malpei, Francesca & Ferretti, Gianni, 2022. "Early prediction of BMP tests: A step response method for estimating first-order model parameters," Renewable Energy, Elsevier, vol. 188(C), pages 184-194.
    6. Wu, Di & Li, Lei & Zhao, Xiaofei & Peng, Yun & Yang, Pingjin & Peng, Xuya, 2019. "Anaerobic digestion: A review on process monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 1-12.
    7. Dandikas, Vasilis & Heuwinkel, Hauke & Lichti, Fabian & Eckl, Thomas & Drewes, Jörg E. & Koch, Konrad, 2018. "Correlation between hydrolysis rate constant and chemical composition of energy crops," Renewable Energy, Elsevier, vol. 118(C), pages 34-42.
    8. Jinming Liu & Changhao Zeng & Na Wang & Jianfei Shi & Bo Zhang & Changyu Liu & Yong Sun, 2021. "Rapid Biochemical Methane Potential Evaluation of Anaerobic Co-Digestion Feedstocks Based on Near Infrared Spectroscopy and Chemometrics," Energies, MDPI, vol. 14(5), pages 1-17, March.

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