Constitutive basis of root system architecture: uncovering a promising trait for breeding nutrient- and drought-resilient crops
Bibliographic record
Abstract
Root system architecture (RSA) plays a pivotal role in efficient uptake of essential nutrients, such as phosphorous (P), nitrogen (N), and water. In soils with heterogeneous nutrient distribution, root plasticity can optimize acquisition and plant growth. Here, we present evidence that a constitutive RSA can confer benefits for sorghum grown under both sufficient and limiting growth conditions. Our studies, using P efficient SC103 and inefficient BTx635 sorghum cultivars, identified significant differences in root traits, with SC103 developing a larger root system with more and longer lateral roots, and enhanced shoot biomass, under both nutrient sufficient and deficient conditions. In addition to this constitutive attribute, under P deficiency, both cultivars exhibited an initial increase in lateral root development; however, SC103 still maintained the larger root biomass. Although N deficiency and drought stress inhibited both root and shoot growth, for both sorghum cultivars, SC103 again maintained the better performance. These findings reveal that SC103, a P efficient sorghum cultivar, also exhibited enhanced growth performance under N deficiency and drought. Our results provide evidence that this constitutive nature of RSA can provide an avenue for breeding nutrient- and drought-resilient crops. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-023-00112-w.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".