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Kitchen Waste Residues asKitchen Waste Residues as Potential Renewable Biomass Resources for the Production of Multiple Fungal Carbohydrases and Second Generation Bioethanol

2013· article· en· W3150862862 on OpenAlexvenueno aff
Chetna Janveja, Susheel Singh Rana, Sanjeev Kumar Soni

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2013
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsBiofuelBiomass (ecology)Renewable energyRenewable resourceWaste managementProduction (economics)Environmental sciencePulp and paper industryChemistryEngineeringBiologyAgronomyEcologyEconomics

Abstract

fetched live from OpenAlex

Utilization of kitchen waste, the major portion of municipal solid waste for the coproduction of multiple carbohydrases and bioethanol was investigated in this study. Solid-state fermentation was performed to evaluate the potential of various steam pretreated kitchen waste residues as substrates for the coproduction of cellulolytic, hemicellulolytic, pectinolytic, amylolytic enzymes by a locally isolated strain of Aspergillus niger CJ-5. All the kitchen waste residues simply moistened with water, without the supplementation of exogenous nutrients proved good for the induction of all the enzyme components of a cocktail after 96 h incubation. Of all the substrates evaluated, steam pretreated potato peels induced maximum yields corresponding to 69.0±1.92U CMCase, 16.5±0.54U FPase, 44.0±1.28U β-glucosidase, 999.0±28.90U xylanase, 58.2±2.12U mannanase, 120.0±3.72U pectinase, 31520.0±375.78U α-amylase, 482.8±9.82U glucoamylase/g dry substrate (gds). Saccharification of residues using inhouse produced crude enzyme cocktail resulted in the release of 610±10.56, 570±8.89, 435±6.54, 475±4.56, 445±4.27, 385±4.49, 370±6.89, 490±10.45 mg of total reducing sugars/g of dried potato peels, orange peels, pineapple peels, mausami peels, onion peels, banana stalks, pea pods and composite mixture respectively revealing carbohydrate conversion efficiencies in the range of 97.0-99.4%. After fermentation of released hexoses, alcohol yields ranging from 80±1.069 - 262±7.86 µL/gds were obtained.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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