Self-Assembled Nanocoatings Protect Microbial Fertilizers for Climate-Resilient Agriculture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Chemical fertilizers have been crucial for sustaining the current global population by supplementing overused farmland to support consistent food production, but their use is unsustainable. Pseudomonas chlororaphis is a nitrogen-fixing bacterium that could be used as a fertilizer replacement, but this microbe is delicate. It is sensitive to stressors, such as freeze-drying and high temperatures. Here, we demonstrate protection of P. chlororaphis from freeze-drying, high temperatures (50 o C), and high humidity using self-assembling metal-phenolic network (MPN) coatings. The composition of the MPN is found to significantly impact its protective efficacy, and with optimized compositions, no viability loss is observed for MPN-coated microbes under conditions where uncoated cells do not survive. Further, we demonstrate that MPN-coated microbes improve germination of seeds by 150% as compared to those treated with fresh P. chlororaphis . Taken together, these results demonstrate the protective capabilities of MPNs against environmental stressors and represent a critical step towards enabling the production and storage of delicate microbes under nonideal conditions.
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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 | 0.001 |
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 it