Molecular breeding of durum wheat cultivars for pasta quality
Bibliographic record
Abstract
The quality of durum wheat (Triticum durum) is defined as its degree of suitability for pasta production. In order to meet the demand of pasta industry for high quality raw material, existing durum varieties should be first improved in terms of quality-associated genes or quantitative trait loci (QTLs). In this study, important QTLs (Gli-B1 locus encoding γ-gliadin 45 protein and Glu-B3 locus encoding LMW-2 type glutenins) that affect cooking quality of pasta were transferred to two durum wheat cultivars (Salihli-92 and Kızıltan-91) through marker-assisted selection (MAS) and backcross breeding. A Canadian durum wheat cultivar with a high quality, Kyle, was used as the donor parent. Each F1 and backcross (BC) plants were backcrossed four times to the recurrent parents, and backcrosses carrying the targeted QTLs were selected by linked molecular markers, i.e. DNA markers, acidic polyacrylamide gel electrophoresis (A-PAGE) and sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Quality analyses were performed on the kernels and semolinas of inbred backcross lines (BC4F4) and of parental cultivars to assess the effects of the transferred QTLs. Both advanced breeding lines (ABLs) had higher protein contents (14.9 and 15.8%) than their recurrent parents (14.0-14.8%). Also, SDS-sedimentation volumes (32.7 and 28.2 ml) of the ABLs were significantly higher (P<0.05) than their parents. It was found that the transfer of Gli-B1 locus containing γ-gliadin 45 and Glu-B3 locus containing LMW-2 type glutenins to the advanced breeding lines led to increases in their pasta-quality associated properties.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".