Plant Growth Promotion, Phytohormone Production and Genomics of the Rhizosphere-Associated Microalga, Micractinium rhizosphaerae sp. nov.
Bibliographic record
Abstract
Microalgae are important members of the soil and plant microbiomes, playing key roles in the maintenance of soil and plant health as well as in the promotion of plant growth. However, not much is understood regarding the potential of different microalgae strains in augmenting plant growth, or the mechanisms involved in such activities. In this work, the functional and genomic characterization of strain NFX-FRZ, a eukaryotic microalga belonging to the Micractinium genus that was isolated from the rhizosphere of a plant growing in a natural environment in Portugal, is presented and analyzed. The results obtained demonstrate that strain NFX-FRZ (i) belongs to a novel species, termed Micractinium rhizosphaerae sp. nov.; (ii) can effectively bind to tomato plant tissues and promote its growth; (iii) can synthesize a wide range of plant growth-promoting compounds, including phytohormones such as indole-3-acetic acid, salicylic acid, jasmonic acid and abscisic acid; and (iv) contains multiple genes involved in phytohormone biosynthesis and signaling. This study provides new insights regarding the relevance of eukaryotic microalgae as plant growth-promoting agents and helps to build a foundation for future studies regarding the origin and evolution of phytohormone biosynthesis and signaling, as well as other plant colonization and plant growth-promoting mechanisms in soil/plant-associated Micractinium.
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 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".