Bioencapsulation of Microbial Inoculants: Mechanisms, Formulation Types and Application Techniques
Bibliographic record
Abstract
The excessive use of agrochemicals in the field to increase production and counteract the negative effects caused by biotic and abiotic factors has led to a deterioration in soil fertility, plus an increment in negative impacts on the environment and human health. Therefore, the application of beneficial microorganisms as bioinoculants is an eco-friendly alternative to agrochemicals. Plant growth-promoting bacteria and fungi have been effective in promoting plant growth and production, as well as reducing the action of pathogens in multiple crops. However, successful application of such beneficial microorganisms in the agricultural field has faced several difficulties, such as survival, colonization efficiency and short periods of shelf storage. Therefore, it is essential to explore novel ways to encapsulate, formulate and apply bioinoculants. To obtain the expected quality in bioencapsulated products, it is essential to determine the type of polymer, capsule size, encapsulation technique and use the correct chemical and physical cofactors involved in the production process. Thus, this review highlights the various formulation types and application techniques, as well as discussing the multiple advantages of using microbial encapsulates to have better results in agricultural production.
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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) | 0.000 | 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 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".