Application of Brachypodium to the genetic improvement of wheat roots
Bibliographic record
Abstract
To meet the demands of a larger and more affluent global population, wheat yields must increase faster this century than last, with less irrigation, fertilizer, and land. Modelling and experiments consistently demonstrate a large potential for increasing wheat productivity by improving root systems; however, application of research to new varieties is slow because of the inherent difficulties associated with working underground. This review makes the case for the use of the model grass Brachypodium distachyon to simplify root research and accelerate the identification of genes underlying wheat root improvement. Brachypodium is a small temperate grass with many genomic, genetic, and experimental resources that make it a tractable model plant. Brachypodium and wheat have very similar root anatomies which are distinct from rice root anatomy that is specialized to help it overcome anaerobic conditions associated with submerged roots. As a dicotyledonous plant, Arabidopsis has an even more divergent root system that features a tap root system and cambia with secondary growth, both of which are lacking in the grasses. The major advantage of Brachypodium is its small stature that allows the adult grass root system to be readily phenotyped, unlike rice and maize. This will facilitate the identification of genes in adult roots that greatly influence yield by modulating water uptake during flowering and grain development. A summary of the advantages of Brachypodium for root studies is presented, including the adult root system architecture and root growth during grain development. Routes to translate discoveries from Brachypodium to wheat are also discussed.
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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 | 0.000 | 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 | 0.001 | 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".