Cell-Free Supernatant of Bacillus Strains can Improve Seed Vigor Index of Corn (Zea mays L.) Under Salinity Stress
Bibliographic record
Abstract
Currently, salinity is the second biggest challenge in the world after drought and affects all stages of plant growth. The use of environmentally friendly methods such as microorganisms and their derivatives can reduce the destructive effects of salinity stress. A growth chamber experiment was conducted to determine the effects of cell-free supernatant (CFS) from Bacillus strains on germination of corn under salinity stress. Corn seeds were subjected to three salinity levels (0, 100 and 150 mM of NaCl), cell-free supernatant of Bacillus strains (U35, U47, U48, U49, and U50) at two levels of dilution (1:50 and 1:250). Germination percentage and rate decreased with increasing salinity toward 150 mM NaCl all together leading to suppressed growth variables for corn seed seedlings including fresh and dry weight of radicle (47.71 and 52.63%, respectively), and shoot (49.52 and 49.25%, respectively), radicle and shoot lengths (39.90 and 66.07%, respectively). Seed vigor index also decreased by 63.04% at 150 mM NaCl. Contrary to salinity, the CFSs of Bacillus strains increased all the growth traits of corn seeds and reduced the negative effects of salinity, especially severe salinity. Ratios of 1:50 and 1: 250 gave best performance for CFSs from U35 and U50, respectively. In general, the highest seed vigor index was obtained by application of 1: 250 CFS from U50. Most germination traits and seed vigor index correlated significantly positive; however, mean germination time was negatively and significantly correlated with the seed vigor index of corn. The results showed that cell-free supernatant use, may as well-helped in changing the ratios of phytohormones, ROS, the activity of antioxidant enzymes and osmotic proteins, hence reduce the negative effects of salinity and improve seed vigor index which eventually increases the ability of plant seedling establishment under saline conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".