Seed Priming with Devosia sp. Cell-Free Supernatant (CFS) and Citrus Bioflavonoids Enhance Canola and Soybean Seed Germination
Bibliographic record
Abstract
Climate change, environmental pollution and associated abiotic stresses are beginning to meaningfully affect agricultural production worldwide. Salt stress is, however, one of the most important threats that significantly impairs plant growth and development. Plants in their early growth stages such as seed germination, seed emergence and early seedling growth are very sensitive to salt stress. Among the range of sustainable techniques adopted to improve seed germination and early plant growth is seed priming; however, with the use of ecofriendly substances, this is one of the most effective and economically viable techniques to improve seed tolerance against such environmental stresses. For instance, priming with appropriate non-synthetic compounds including microbial biostimulants are prominent ways to sustainably address these challenges. Therefore, in this research, by using the “priming technique”, two biostimulants were tested for their potential as sustainable approaches to improve canola and soybean seed germination under salt stress and optimal growth conditions. Canola and soybean seeds were primed with flavonoids extracted from citrus fruits (flavopriming) and cell-free supernatant (CFS; produced by a novel strain of Devosia sp.—SL43), alone and in combination, and exposed to low–higher levels of salt stress and ideal growth conditions. Both biostimulants showed promising effects by significantly improving seed germination of soybean and canola under both ideal and stressful conditions. However, increases in seed germination were greater under salinity stress as flavonoids and CFS with stress amelioration effects showed substantial and statistically significant improvements in seed germination under varying levels of salt stress. In addition, combinations (mixtures) of both biostimulants were tested to determine if their effects might be more additive or multiplicative than the individual applications. However, results suggested incompatibility of both biostimulants as none of the combinations showed better results than that of the individual applications of either flavonoids or CFS. Conceivably, the use of flavonoids and this novel Devosia sp. CFS could be significant plant growth enhancers, perhaps much better than the few other biostimulants and bacterial-based compounds currently in use.
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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".