Water relations and yield in<i>Azospirillum-</i>inoculated wheat exposed to drought in the field
Bibliographic record
Abstract
There are scarce data connecting water relations in Azospirillum-inoculated wheat suffering drought during anthesis with the yield and mineral content of grains. Azospirillum brasilense Sp245-inoculated seeds of Triticum aestivum 'Pro INTA Oasis' were sown in nonirrigated and control plots. Water potential, water content, and relative water content were determined on flag leaves. Plant water status was calculated from pressurevolume curves. At maturity, grain yield and its components were determined. P, Ca, Mg, K, Fe, Cu, and Zn were determined in dried grains. Even though the cultivar underwent osmotic adjustment, significantly higher water content, relative water content, water potential, apoplastic water fraction, and lower cell wall modulus of elasticity values were obtained in Azospirillum-inoculated plants suffering drought. Grain yield loss to drought was 26.5% and 14.1% in noninoculated and Azospirillum-inoculated plants, respectively. Grain Mg and K diminished in nonirrigated, noninoculated plots. However, grains harvested from Azospirillum-inoculated plants had significantly higher Mg, K, and Ca than noninoculated plants. Neither drought nor inoculation changed grain P, Cu, Fe, and Zn contents. A better water status and an additional "elastic adjustment" in Azospirillum-inoculated wheat plants could be crucial in promoting higher grain yield and mineral quality at harvest, particularly when drought strikes during anthesis.Key words: Azospirillum, wheat, drought, pressurevolume curves, yield, mineral content.
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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) | 0.001 | 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".