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Record W2330654579 · doi:10.4141/p03-205

Effect of durum wheat (<i>Triticum turgidum</i> L. var. <i>durum</i>) semolina extraction rate on semolina refinement, strength indicators and pasta properties

2004· article· en· W2330654579 on OpenAlexaffvenueabout
J. E. Dexter, M. A. Doust, C.N. Raciti, Grazia Lombardo, F. R. Clarke, J. M. Clarke, B. A. Marchylo, L. Schlichting, D. W. Hatcher

Bibliographic record

VenueCanadian Journal of Plant Science · 2004
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food Canada
FundersScheme for Promotion of Academic and Research Collaboration
KeywordsGlutenCultivarExtraction (chemistry)AgronomyFarinographFood scienceMathematicsHorticultureChemistryBiology

Abstract

fetched live from OpenAlex

Since the 1980s, there have been general trends in the durum wheat milling industry to higher semolina extraction rate, and in the pasta processing industry to the use of higher drying temperatures. During this time, specification of gluten strength by gluten index, mixograph mixing properties and alveograph parameters has also become widespread. These trends prompted this study of the appropriateness of protocols for quality testing of Canadian durum wheat breeding lines. Four cultivars with intrinsic differences in yellow pigment levels and gluten strength were grown in field plots in Swift Current, Saskatchewan for three consecutive years. A laboratory-scale milling procedure was modified to produce semolina at extraction rates from about 65% to about 80%. Milling to extraction rates above 65%, the extraction rate used routinely in quality testing of Canadian durum wheat breeding lines, had a major impact on semolina ash content and colour, but did not offer any advantage in ranking cultivars for either semolina yield or semolina refinement. Gluten strength, as measured by gluten index, was independent of semolina extraction rate. Dough strength, as measured by mixograph properties and alveograph properties, showed a tendency to weakening at high extraction, particularly for strong cultivars. Semolina was processed into spaghetti using low-temperature (LT), high-temperature (HT) and ultra-high-temperature (UHT) drying cycles. The firmness of cooked spaghetti was predominantly influenced by protein content. As a result, cultivars generally ranked in spaghetti firmness according to protein content. Regardless of drying cycle or cultivar, spaghetti firmness increased as drying temperature increased. Spaghetti dried at LT was less yellow than spaghetti dried at HT or UHT, probably due to thermal inactivation of the bleaching enzyme lipoxygenase at HT and UHT. Regardless of drying cycle, spaghetti became duller, more red and less yellow as extraction rate increased. For each spaghetti trait, cultivar ranking remained relatively constant regardless of extraction rate or drying temperature. On the basis of these results, there appears to be no advantage to increasing semolina extraction rate beyond 65% for evaluation of durum wheat milling performance, gluten strength or pasta properties. In addition, it appears that one drying cycle is adequate to reliably evaluate durum wheat lines for spaghetti colour and firmness. Key words: Durum wheat (Triticum turgidum L. var durum), milling, semolina, pasta, quality screening, gluten strength, colour, texture

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2004
Admission routes3
Has abstractyes

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