Cell-Free Supernatant (CFS) from Bacillus subtilis EB2004S and Lactobacillus helveticus EL2006H Cultured at a Range of pH Levels Modulates Potato Plant Growth under Greenhouse Conditions
Bibliographic record
Abstract
Agriculture involving industrial fertilizers is another major human made contributing factor to soil pH variation after natural factors such as soil parent rock, weathering time span, climate, and vegetation. The current study assessed the potential effect of cell-free supernatant (CFS) obtained from Bacillus subtilis EB2004S and Lactobacillus helveticus EL2006H cultured at three pH levels (5, 7, and 8) on potato (var Goldrush) growth enhancement in a greenhouse pot experiment. The results showed that CFSs obtained from B. subtilis EB2004S and L. helveticus EL2006H cultured at pH 5 significantly improved photosynthetic rates, stomatal conductance, root fresh weight, and whole plant fresh weight. interactive effects of pot pH and that of CFSs obtained from pH 5 influenced chlorophyll, plant height, and shoot and whole plant fresh weight. Moreover, treatment 52EB2004S~0.4% initiated early tuberization for potato grown at pH 7 and 8. Potato grown at pH 5, which received a 72EB2004S~0.4% CFS treatment, had greater whole plant fresh and dry weight than that treated with L. helveticus EL2006H CFS and a positive control. Taken together, the findings of this study are unique in that it probed the effect of CFS produced under differing pH conditions which revealed a new possibility to mitigate stresses in plants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".