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Record W2006142214 · doi:10.1007/s10295-006-0164-6

Dissolved oxygen as principal parameter for conidia production of biocontrol fungi Trichoderma viride in non-Newtonian wastewater

2006· article· en· W2006142214 on OpenAlexafffund
M. Verma, Satinder Kaur Brar, R. D. Tyagi, Rao Y. Surampalli, José R. Lerma Valero

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2006
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsUniversité du QuébecInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIndustrial fermentationAerationFermentationTrichoderma virideLaboratory flaskFood scienceMyceliumBioreactorBiologyChemistryBotanyEcology

Abstract

fetched live from OpenAlex

Dissolved oxygen (DO) concentration was selected as a principal parameter for translating results of shake flask fermentation of Trichoderma viride (biocontrol fungi) to a fermenter scale. All fermentations were carried out in a 7.5 l automated fermenter with a working volume of 4 l. Fermentation performance parameters such as volumetric oxygen transfer coefficient (k (L) a), oxygen uptake rate (OUR), rheology, conidia concentration, glucose consumption, soluble chemical oxygen demand, entomotoxicity and inhibition index were measured. The conidia concentration, entomotoxicity and inhibition index were either stable or improved at lower DO concentration (30%). Variation of OUR aided in assessing the oxygen supply capacity of the fermenter and biomass growth. Meanwhile, rheological profiles demonstrated the variability of wastewater during fermentation due to mycelial growth and conidiation. In order to estimate power consumption, the agitation and the aeration requirements were quantified in terms of area under the curves, agitation vs. time (rpm h), and aeration vs. time (lpm h). This simple and novel strategy of fermenter operation proved to be highly successful which can be adopted to other biocontrol fungi.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
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 head0.259
Teacher spread0.243 · 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.

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

Citations24
Published2006
Admission routes2
Has abstractyes

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