Reparation of aged lettuce (<i>Lactuca sativa</i>) seeds by osmotic priming and<i>Azospirillum brasilense</i>inoculation
Bibliographic record
Abstract
Although Azospirillum spp. are considered to be important plant growth promoting bacteria, their possible effects on germination and vigor of aged lettuce seeds has not been previously evaluated. In fact, there is a paucity of published data about inoculation effects on seed germination. The aim of this work was to evaluate seed quality of one-year aged lettuce (Lactuca sativa L. cv. Crimor INTA) seeds after Azospirillum brasilense Sp245 inoculation with or without an osmopriming pretreatment. Fresh lettuce seeds were stored in the dark in a dry chamber for one year and then subjected to inoculation with A. brasilense Sp245, to osmotic priming with 0.37 mol/L MgSO4, or to both combined treatments. Seed germination, seed vigor, and seedlings emergence percentages were determined, and the abnormal seedling fraction was characterized. Azospirillum brasilense inoculation without a previous osmopriming enhanced seed vigor and seedling emergence percentages and decreased the fraction of abnormal seedlings. There was an additional effect of osmopriming as a previous treatment on germination percentage. We concluded that the use of A. brasilense inoculation alone or after an osmopriming treatment would contribute to overcome the negative effects of ageing on lettuce cv. Crimor INTA seeds.
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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".