Costeffective formulation of bio-fertilizer using agricultural residues as carriers and determination of shelflife of bio-fertilizer inoculants
Bibliographic record
Abstract
Traditionally, inorganic chemical-based fertilizers is used for soil management strategies, which can cause public health and environmental threats. Alternatively, bio-fertilizer can be used to increase the productivity and sustainability of soil without causing environmental pollution. The present study aimed to cost-effectively produce bio-fertilizer using agricultural residues and determine the shelflife and efficacy of the bioinoculants. We used sterilized rice husk ash and alluvial soil (1:2) to prepare cost-effective carriers. Rhizobium sp., Azotobacter sp., and Trichoderma sp. were grown in a newly designed culture medium for economic production as bio-inoculants. The efficacy of the formulated bio-fertilizer was tested on a small scale, where it significantly improved the growth of the sponge gourd (Luffa aegyptiaca) plant (p<0.01). The formulated bio-fertilizers were stored at room temperature for one year. Initially, the total viable count of microorganisms was 8.0×107 CFU/g in the formulated bio-fertilizer. The total viable count of the bio-inoculants increased significantly after one month (2.2×108 CFU/g) and one year (2.2×109 CFU/g). Rice husk ash might have supported the growth and survival of the bioinoculants under room temperature (25°C) because of its nutrient retention capacity, adsorptive capability, and high content of silica. Therefore, this study suggests that sterile rice husk ash combined with alluvial soil can be used as a carrier for bio-fertilizers formulation with Rhizobium sp., Azotobacter sp., and Trichoderma sp. bioinoculants. Dhaka Univ. J. Biol. Sci. 32(2): 189-199, 2023 (July)
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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 | 0.000 |
| 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 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".