Humic acids as drivers of plant growth: regulating root development and photobiology through redox modulation
Bibliographic record
Abstract
Abstract Background Humic acids (HA) influence plant growth and development through various mechanisms that depend on the source and concentration of HA, as well as the specific plant organ and its developmental stage. Acting as biostimulants, these substances elicit stress-like responses and trigger physiological, biochemical, and molecular changes in plants that involve redox homeostasis. Therefore, we aimed to understand how purified HA derived from oxidized sub-bituminous coal impacts growth, redox states and photobiology in plants. After identifying the optimal HA dosage, plants were evaluated for their growth and photobiological responses, enzyme activities, reactive oxygen species (ROS) levels, and selected gene expression. Results An HA concentration of 20 mg L −1 of carbon significantly enhanced most morphological and photobiological parameters. HA modulated the electron transport across the thylakoid membrane, thereby influencing the proton motive force and ATP synthesis. We also observed improved root growth within finer root diameter classes, which enhances foraging capacity and contributes to better nutrient absorption. HA stimulated fast ROS production, enhanced antioxidant enzyme activities, and increased H + -ATPase activity in roots. In addition, HA induced the expression of the roothairless5 ( rth5 ) gene, which is involved in root hair growth. Furthermore, HA promoted the activity of H + -ATPase, RBOH and NADH oxidases, and changed the expression of genes, such as ZmSOD4 , ZmCAT3 , ZmPIN1b , ZmEXPA4 , ZmLAX3 , ZmHA2 , and ZmTOR . Conclusions These findings suggest that HA promote plant development in roots by modulating oxidative stress through the RBOH/ROS/auxin/H + -ATPase pathways while potentially influencing photobiological processes via their electron-donating and accepting properties. These effects may be attributed to the interplay between the pro-oxidant (e.g., quinones and semiquinone radicals) and the antioxidant functionalities (e.g., polyphenols) inherent in HA, both contributing to the observed eustress response. The coordinated action of the RBOH, H + -ATPase, and TOR pathways likely help maintain a positive membrane oxidative balance, supporting root growth and development. Graphical abstract
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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) | 0.001 | 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".