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Record W2892773191 · doi:10.5539/jas.v10n11p16

Effect of Processing on Mungbean (Vigna radiata) Flour Nutritional Properties and Protein Composition

2018· article· en· W2892773191 on OpenAlexvenueno aff
Daniel J. Skylas, Mark P. Molloy, Robert D. Willows, Hayfa Salman, Christopher Blanchard, Ken Quail

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
FundersAustralian Government
KeywordsVignaRoastingFood scienceAmyloseStarchGerminationComposition (language)RadiataPlant proteinWheat flourChemistryResistant starchDietary fibreStarch gelatinizationWater contentVicia fabaBiologyAgronomy

Abstract

fetched live from OpenAlex

Pulses are traditionally processed prior to consumption, providing opportunities for modifying nutritional composition, dependant on the type of pulse and method used. In this study, we investigated the effect of whole seed, dehulling (dahl), germination and roasting on changes in mungbean flour nutritional properties, protein composition and relative protein abundance. Processed flours were analysed and compared for protein content, moisture, fat, ash, dietary fibre, total starch and amylose. Significant differences were imparted on dietary fibre content, with roasting and germination increasing the ratio of insoluble/soluble fibre as well as resistant starch. Comparative proteomic analysis resulted in a combined total of 539 protein identifications, searching against the Mungbean reference genome (NCBI Vigna radiata Annotation Release 100). Normalised spectral abundance factors were used as a measure of relative abundance and statistical analysis was applied (Students’ T-Test), where proteins with a p-value of < 0.05 considered significantly different. Processing imparted considerable changes to nutritional composition and should be further exploited for food applications. The comparative proteomic analyses carried out in this study proved useful for investigating the effect of processing on subsequent changes in protein composition and relative abundance.

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)0.000
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 score0.383
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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
Published2018
Admission routes1
Has abstractyes

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