Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass...
Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data
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Publisher
Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid anal...
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Full title
Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8071563
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8071563
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ISSN
1422-0067,1661-6596
E-ISSN
1422-0067
DOI
10.3390/ijms22084107
