Effects of Combination of Growth-promoting Rhizobacteria from Pseudostellaria heterophyllaon Seed Vigor and Seedling Growth of Intercropping Maize
Bibliographic record
Abstract
To explore the effects of growth-promoting rhizobacteria from Pseudostellaria heterophylla on the seed germination and seedling growth of intercropping maize,the experiments with 25 factorial design were carried out at constant temperature. The results showed that strain combinations,A1B1C2D2E2,A2B1C1D2E1( or A2B2C1D1E1),A1B1C1D1E1,A1B2C2D2E2,A1B1C2D2E2,A1B2C2D2E1,A2B2C2D1E1,A1B1C2D1E2 and A1B2C2D2E2had the most obvious effects on germination potential,germination rate,dehydrogenase activity,seedling length,radicule length,hypocotyls length,the number of fibrous roots,dry weight of seedlings and dry weight of roots,respectively. There existed the interactions among five growth-promoting rhizobacteria on seedling length,radicule length,hypocotyls length,the number of fibrous roots,dry weight of seedlings and dry weight of roots. The combination of A1B1C1D2E1 could increase the dry weights of seedlings and roots and promote the seedling growth,which would be used in the production of microbial fertilizer of Pseudostellaria heterophylla.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".