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Record W2911949408 · doi:10.1139/cjps-2018-0134

Free asparagine concentrations in Canadian hard red spring wheat cultivars

2019· article· en· W2911949408 on OpenAlexaffvenueabout
Lovemore Nkhata Malunga, Nancy Ames, M. Tugrul Masatcioglu, Ali Salimi Khorshidi, Sijo Joseph Thandapilly, Richard D. Cuthbert, Elaine Sopiwnyk, Martin G. Scanlon

Bibliographic record

VenueCanadian Journal of Plant Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsUniversity of ManitobaCanadian International Grains InstituteAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAsparagineCultivarLimitingAcrylamideFood scienceChemistryAgronomyWinter wheatAmino acidHorticultureBiologyBiochemistryPolymer

Abstract

fetched live from OpenAlex

The amino acid asparagine is considered the rate limiting precursor in the formation of acrylamide in cereal-based baked foods. However, there are no data on the quantity of this precursor in Canadian wheat. Wholemeal and white flour samples obtained from 30 Canadian hard red spring wheat grown in the Prairie provinces were analysed for asparagine content by liquid chromatography. The asparagine content varied from 302 to 965 and 116 to 336 μg g −1 for wholemeal and white flour, respectively. Therefore, wheat grown in Canada has similar asparagine levels to wheat grown in other parts of the world. Analysis of variance suggested that asparagine content is significantly affected by genotype (p < 0.001), suggesting that breeding strategies could be investigated to produce cultivars with lower levels of this amino acid. Few significant correlations were observed between wheat and flour quality parameters and asparagine content, although there was a tendency towards weaker dough strength indices with increasing asparagine content.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.224
Teacher spread0.198 · 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 designObservational
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

Citations17
Published2019
Admission routes3
Has abstractyes

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