Relationships between roots, the stay‐green phenotype, and agronomic performance in barley and wheat grown in semi‐arid conditions
Bibliographic record
Abstract
Abstract Stay‐green is a phenotype that crop breeders could use to improve drought adaptation. It increases the duration of grain fill in several species including barley ( Hordeum vulgare L.) and wheat ( Triticum aestivum L.), maintaining yield in semi‐arid conditions. Evidence from controlled environment experiments suggests a connection between stay‐green and root systems. These belowground structures are understudied and thus represent opportunity for crop improvement if relationships to agronomics can be understood. Minirhizotrons facilitate study of these relationships by allowing repeated nondestructive root measurements in field conditions. However, this is time‐consuming, and proxies would be useful for increasing throughput capacity of root research. Here we present results from field trials with minirhizotrons in a semi‐arid environment, as well as greenhouse seedling assays conducted on stay‐green and non‐stay‐green barley and wheat lines. In barley, stay‐green and greater yield were primarily associated with greater deep root length and delayed root senescence, whereas in wheat, yield was most strongly correlated with total root length, and root system differences for stay‐green were not as apparent. We speculate that the physiology of stay‐green is different between these two species, and that barley may use a more efficient root system to withstand drought whereas wheat relies on a larger one. Several seedling traits related consistently to field root traits, but correlation directions were often opposite between barley and wheat. The connections between traits presented here could be useful for breeders seeking to improve crop adaptation to drought, but more genotypes and environments will need to be tested.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".