Germination and Seedling Growth of Genotypes Crambe abyssinica Submitted to Water Deficit
Bibliographic record
Abstract
Determining drought tolerance in plants is an increasingly important feature due to the reduction of water resources, since water stress is one of the main environmental factors that limit agricultural growth and productivity. The objective of this study was to evaluate the tolerance of crambe (Crambe abyssinica Hochst) genotypes submitted to water stress induced by polyethylene glycol during germination and early growth of seedlings. A randomized block experimental design was used in a factorial scheme consisting of five crambe genotypes (FMS Brilhante, FMS CR 1203, 1307, 1312 and 1326) and five levels of osmotic potential [0.0 (control), -0.2, -0.4, -0.5 and -0.6 MPa] in five replicates of 40 seeds. Germination rate (%), normal seedling development (%), germination speed index, root and shoot length, total fresh matter, and water content of seedlings (%) were analyzed. Physiological quality of seeds and initial development of crambe genotypes was improved in the group submitted to Ψw = -0.2 MPa. Germination and vigor index of crambe seeds were hampered by reduction of the potential to -0.4 MPa. The genotype FMS CR 1203 was the most tolerant to water stress, whereas FMS CR 1307 and 1312 were the most sensitive, as corroborated by PCA.
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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 | 0.001 |
| 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".