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Record W4361861615 · doi:10.26599/pbm.2023.9260005

Biodegradation Behavior of Starch in Simulated White Water System of Old Corrugated Cardboard Pulping Process

2023· article· en· W4361861615 on OpenAlexaff
Jinhuan Guo, Liqin Liu, Xiaohong Zhang, Zhengbai Cheng, Shuangxi Nie, Haibing Cao, Na Li, Md Manik Mian, Xingye An, Hongbin Liu

Bibliographic record

VenuePaper and Biomaterials · 2023
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of New Brunswick
FundersTianjin UniversityChina Postdoctoral Science FoundationGuangxi UniversityNational Natural Science Foundation of China
KeywordsBiodegradationStarchHydrolysisChemistryDegradation (telecommunications)AmylaseChromatographyChemical engineeringMaterials scienceFood scienceOrganic chemistryEnzyme

Abstract

fetched live from OpenAlex

Considering the serious barriers/issues induced by the accumulated starch generated in white water system of old corrugated cardboard (OCC) pulping process, large amounts of accumulated starch in white water would be decomposed by microorganisms and could not be utilized, thereby resulting in severe resource wastage and environmental pollution. This study mainly explored the effects of biodegradation/hydrolysis conditions of the two types of starch substrates (native starch and enzymatically (<i>α‍</i>-amylase) hydrolyzed starch), which were treated via microorganism degradation within the simulated white water from OCC pulping system and their biodegradation products on the key properties were characterized via X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and gel permeation chromatography (GPC) technologies. The effects of system temperature, pH value, starch concentration, and biodegradation time on starch biodegradation ratio and the characteristics of obtained biodegradated products from the two types of starches were studied. In addition, the effect of <i>α‍</i>-amylase dosage on the biodegradation ratio of enzymatically hydrolyzed starch and its properties was investigated. It was found that the native starch presented a maximal degradation ratio at a system temperature of 55 ℃ and pH value range of 5-7, respectively, the corresponding starch concentration within simulated white water system was 200 mg/L. Whereas the enzymatically hydrolyzed starch exhibited a highest degradation ratio at a system temperature of 50 ℃ and pH value of 5.5, respectively, and the corresponding starch concentration within simulated white water system was 100 mg/L. It was verified that native starch is more readily bio-hydrolyzed and biodegradation-susceptive by microorganisms in simulated white water system of OCC pulping process, while the enzymatically hydrolyzed starch exhibits better biodegradation/hydrolysis resistance to the microbial degradation than that of native starch. This study provides a practical and interesting approach to investigate the starch hydrolysis or biodegradation behaviors in white water system of OCC pulping process, which would greatly contribute to the full recycling and valorized application of starch as a versatile additive during paperboard production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.024
GPT teacher head0.275
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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