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Record W4310137282 · doi:10.1016/j.jobab.2022.11.005

Development and characterization of mycelium bio-composites by utilization of different agricultural residual byproducts

2022· article· en· W4310137282 on OpenAlexvenueno aff
Liucheng Peng, Jing Yi, Xinyu Yang, Jing Xie, Chenwei Chen

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsnot available
FundersScience and Technology Commission of Shanghai MunicipalityMinistry of Science and Technology of the People's Republic of China
KeywordsBagasseSawdustMyceliumMaterials scienceStrawComposite materialCoirFlexural strengthScanning electron microscopeHuskUltimate tensile strengthCellulosePulp and paper industryChemistryBotany

Abstract

fetched live from OpenAlex

Mycelium bio-composites was developed by incubating Pleurotus ostreatus fungi on different substrates from agricultural residual byproducts, including rice straw, bagasse, coir-pith, sawdust, and corn straw. The scanning electron microscope (SEM) results showed that the hypha of composite derived from bagasse was the densest, and the diameter of hypha was the biggest (0.77 µm), which was presumably due to the existence of cellulose in bagasse in the form of dextran and xylan. The maximum and minimum compression strength for sawdust substrate and corn straw substrate were 456.70 and 270.31 kPa, respectively. The flexural strength for bagasse substrate and rice straw substrate were 0.54 and 0.16 MPa, respectively. The two composites derived from rice straw and bagasse exhibited higher hydrophobic properties than others. In comparison, mycelium bio-composite derived from bagasse showed the best comprehensive properties. Except for a little worse anti-creep ability and waterproof performance, other properties of mycelium bio-composites could be comparable to commercially expanded polystyrene (EPS) packaging material. Derived from this study, mycelium material provided a good way to use agricultural residual byproducts and could be a good alternative to non-biodegradable materials for packaging applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.186
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations61
Published2022
Admission routes1
Has abstractyes

Explore more

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