Use of nanotechnology to improve plant performance in boreal forest ecosystem
Bibliographic record
Abstract
Nano-priming has been shown to significantly improve the total germination percentage and seedling vigor of different plant seeds including agricultural crops. In these applications, seeds primed with Carbon nanotubes (CNTs) exhibited dramatic improvements in germination rate and seedling vigor (root and stem lengths). Herein, we applied this technique to non-agriculture crop species in an attempt to resolve several different seeds dormancies hindering their propagation and field establishment. Specifically, the seeds of boreal forest plant species with embryo and seed coat dormancy were nano-primed with several carbon-based nanoparticles, as part of a strategy to overcome seed dormancy. Carboxylic acid functionalized multi-walled carbon nanoparticle (-COOH biomolecule coated) was the most effective in breaking physical (seed coat) and morphological dormancy (embryo), as well as increase the germination rate in combination with stratification in green alder (Alnus viridis L.), bog birch (Betula pumila), and labrador tea (Rhododendron groenlandicum). Conversely, a combination of carbon nanoparticles (CNPs), especially the multiwall carbon nanoparticles functionalized with carboxylic acid (MWCNT-COOH), cold stratification, mechanical scarification and hormonal priming (gibberellic acid) was effective in overcoming embryo and hard seed coat dormancy present in buffalo berry seeds (Shepherdia canadensis L.). A concomitant increase in the seedling vigor index and the number of normal seedlings was observed in the nano-primed germinated seedlings, indicating its superior ability to be established across a range of environmental sites. The improvement in germination rate and resolution of both embryo and seed coat dormancy appears to be associated with the remodeling of several membrane lipids as indicated by the segregation of these molecular species in the same quadrant of the biplot as germination rate (GR) and seedling vigor index (SVI), following redundancy analysis. Phosphatidylcholine (PC) (18:1/18:3), phosphatidylglycerol (PG) (16:1/18:3), phosphatidylethanolamine (PE) (18:3/18:2), and digalactosyldiacylglycerol (DGDG) (18:3/18:3) lipids classes were observed to be highly correlated with increased seed germination percentages and the enhanced seedling vigor observed in this study for the evaluated species. Mechanistically, it appears that carbon nano-primed seeds following stratification is effective in mediating seed dormancy by remodeling the seed membrane lipids {Phosphatidylcholine (PC), phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylserine (PS), phosphatidic acid (PA) and digalactosylglycerol (DG)} in both peatland and upland boreal forest species. These findings suggest that nanopriming (20 μgmL⁻¹ or 40 μgmL⁻¹) may be a useful approach to resolve seed dormancy issues and improve seed germination in non-resource boreal forest species ideally suited for forest reclamation following resource mining.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".