Root specific plasticity induced by paclobutrazol confers improved deficit irrigation tolerance and agronomic performance in maize
Bibliographic record
Abstract
Abstract Drought stress in maize often results in poor growth and reduced yield. Antioxidants play vital role in management of abiotic stresses. Drought or water deficit are detrimental to young seedlings establishment and transition from vegetative to reproductive growth in maize. Paclobutrazol (PBZ) has been widely used to confer abiotic stress tolerance in plants, however, its impact on root developmental attributes in maize and their relevance in drought management are least understood. Comprehensive experiments over a three year period (2017-2019) under early deficit (EDI) and terminal deficit (TDI) irrigation with or without paclobutrazol (PBZ) were conducted on five maize varieties (DDKL, DKC-9144, PG-2475, PG-2320 and Bio-9621). Plant shoot and root growth kinetics, phenological changes and physiological perturbations including antioxidant profile coupled with molecular regulation of root traits, showed DKC-9144 as best variety in terms of plant fitness and reproductive performance under deficit irrigation. Root developmental rates were key contributors towards improved plant biomass and cob yield under deficit irrigation tolerance. Structural equation modelling (SEM) demonstrated specific contribution of different root types (crown, brace and seminal roots) in maize towards improving water use efficiency, cob yield and plant height. From SEM, seminal root surface area and root length are proposed desired traits to improve water use efficiency and cob yield in DKC-9144 under deficit irrigation. Bi-variate analyses of twenty key traits of plant fitness and agronomic importance showed a strong correlation ( r ) between root traits and improved growth performance and yield stability indices.
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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 | 0.000 | 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".