Effect of Various Carriers and Storage Temperatures on Survival of Azotobacter vinelandii NDD-CK-1 in Powder Inoculant
Bibliographic record
Abstract
A study was carried out for determining the effect of various carriers and storage temperatures on survival of Azotobacter vinelandii NDD-CK-1. The experiment was laid out using a 4 x 5 factorial treatment arrangement in a Completely Randomized Design with three replications. The first factor is carrier with four kinds, viz. peat (Pt), peat mixed with corn stubble compost (PtCC), peat mixed with golden flamboyant leaf compost (PtLC), and Pt mixed with mushroom waste compost (PtMC). The second factor is storage temperature with five levels, viz. -16 oC, 5 oC, 25 ± 2 oC, 30 ± 2 oC and 37.5 ± 2.5 oC. Inoculum of Azotobacter vinelandii NDD-CK-1 was produced by a standard method using various carriers. The results revealed that types of carrier, storage temperatures and interaction between them showed significant effect on survival of azotobacter during 7 to 90 days. The survival rate was the highest in PtLC, followed by PtCC, PtMC, and Pt which gave the log number of bacterial viable cell of 6.41, 6.02, 5.67 and 5.50, respectively. The proliferation of azotobacter decreased with time and increasing temperature. The appropriate storage temperature at 7 to 15 days was -16 oC, while the most suitable temperatures for longer term (30 to 90 days) was 5 oC; followed by -16 oC, 25 ± 2 oC, 30 ± 2 oC and 37.5 ± 2.5 oC. The highest survival of azotobacter was found in PtCC at -16 oC (9.98 log cfu/g), similar to PtCC at 5 oC, PtLC at -16 oC, and PtLC at 5 oC (9.92, 9.85 and 9.77 log cfu/g, respectively).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".