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Record W1978734663 · doi:10.1007/s11746-006-1177-z

Production of mustard protein isolates from oriental mustard seed (<i>Brassica juncea</i> L.)

2006· article· en· W1978734663 on OpenAlex
Rebecca Marnoch, Levente L. Diósady

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBrassicaRapeseedMustard seedSoy proteinUltrafiltration (renal)ChemistryDiafiltrationFood scienceMealProtein purificationResidue (chemistry)ChromatographyBiologyBotanyBiochemistryMembraneMicrofiltration

Abstract

fetched live from OpenAlex

Abstract A membrane‐based process to produce protein isolates from seeds of oriental mustard ( Brassica juncea ) was developed by modifying a method originally developed for rapeseed. The optimized process consisted of extraction at pH 11, ultrafiltration with concentration factor 4, diafiltration with diavolume 3, and precipitation at pH 5. The process, based on defatted oriental mustard seed containing 45–50% protein, recovered 81% of the protein in useful products: 47.3% in precipitated protein isolate (PPI), 3.8% in soluble protein isolate (SPI), and 13% in meal residue. Mass yields were 21.9% in PPI, 2.8% in SPI, and 38.4% in meal residue. The losses in the system included ∼10% loss of nonprotein nitrogen, and &lt;9% into permeate and transfer losses. The PPI compared favorably with soy protein isolate in typical meat products in terms of color, texture, and flavor. The work confirms that oriental mustard is a potentially useful source of edible protein.

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.

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 score0.053
Threshold uncertainty score0.173

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 head0.005
GPT teacher head0.188
Teacher spread0.182 · 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