Neural Network Prediction of Corn Stover Saccharification Based on Its Structural Features Article Swipe
Le Gao
,
Shulin Chen
,
Dongyuan Zhang
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1155/2018/9167508
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1155/2018/9167508
The classic assay for a large population biomass is time-consuming, labor intensive, and chemically expensive. This paper would find out a rapid assay for predicting biomass digestibility from biomass structural features without hydrolysis. We examined the 62 representative corn stover accessions that displayed a diverse cell-wall composition and varied biomass digestibility. Correlation analysis was firstly to detect effects of cell-wall compositions and wall polymer features on corn stover digestibility. Based on the dependable relationship of structural features and digestibility, a neural networks model has been developed and successfully predicted the corn stover saccharification based on the features without enzymatic hydrolysis. The actual measured and net-simulated predicted corn stover saccharification had good results as mean square error of 1.80E-05, coefficient of determination of 0.942 and average relative deviation of 3.95. The trained networks satisfactorily predicted the saccharification results based on the features of corn stover. Predicting the corn stover saccharification without hydrolysis will reduce capital and operational costs for corn stover purchasing and storage.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2018/9167508
- https://downloads.hindawi.com/journals/bmri/2018/9167508.pdf
- OA Status
- hybrid
- Cited By
- 4
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2886317180
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2886317180Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/2018/9167508Digital Object Identifier
- Title
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Neural Network Prediction of Corn Stover Saccharification Based on Its Structural FeaturesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-08-12Full publication date if available
- Authors
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Le Gao, Shulin Chen, Dongyuan ZhangList of authors in order
- Landing page
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https://doi.org/10.1155/2018/9167508Publisher landing page
- PDF URL
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https://downloads.hindawi.com/journals/bmri/2018/9167508.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://downloads.hindawi.com/journals/bmri/2018/9167508.pdfDirect OA link when available
- Concepts
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Corn stover, Stover, Biomass (ecology), Hydrolysis, Agronomy, Mathematics, Chemistry, Pulp and paper industry, Biology, Biochemistry, Engineering, Field experimentTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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