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Record W2003181959 · doi:10.1094/cchem-03-11-0026

Protein Extraction from Triticale Distillers Grains

2011· article· en· W2003181959 on OpenAlexafffundabout
Nandika Bandara, Lingyun Chen

Bibliographic record

VenueCereal Chemistry · 2011
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Alberta
FundersAlberta InnovatesAlberta Livestock and Meat Agency
KeywordsTriticaleChemistryDistillers grainsExtraction (chemistry)Acetic acidCoproductRaw materialFood scienceFractionationEthanolEthanol fuelBiofuelChromatographyAgronomyBiochemistryFermentationBiotechnologyOrganic chemistryBiology

Abstract

fetched live from OpenAlex

ABSTRACT Triticale is being actively explored as a feedstock for bioethanol production in Western Canada. Triticale distillers grains, an important coproduct of the bioethanol industry, are used mainly as animal feed. This study aims to develop methods of protein extraction from triticale distillers wet grains and distillers dried grains with solubles. Osborne fractionation showed low protein extractability because excessive protein denaturation occurred during sample preparation. Five methods were used to extract proteins: pH shifting, 60% ethanol, alkaline‐ethanol solution, glacial acetic acid, and enzyme‐aided extraction. Extracts obtained with the alkaline‐ethanol and glacial acetic acid methods showed comparatively higher protein contents (≈61–65%) when compared with the other extraction methods (≈35–57%). Enzyme‐aided extraction with Protex 6L yielded 75–82% protein at a content of 43–57%, depending on the types of raw materials. Establishing methods of protein extraction from triticale distillers grains would facilitate further studies on new uses of triticale proteins.

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 categoriesInsufficient payload (model declined to judge)
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 score0.152
Threshold uncertainty score0.999

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)0.0020.000

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 head0.037
GPT teacher head0.247
Teacher spread0.210 · 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

Citations21
Published2011
Admission routes3
Has abstractyes

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