Cork Oak Seedling Growth under Different Soil Conditions from Fertilisation, Mycorrhizal Fungi and Amino Acid Application
Bibliographic record
Abstract
<p class="TESE">Regeneration process deals with some constrains related with the livestock management, pasture rotations, and dependence of a sequence of favourable climatic years, among others, which can lead to a continuous delay in the initiation of the regeneration process. The purpose of this study is to promote an increase of cork oak seedling growth in order to decrease the time required for regeneration and also to contribute to avoid the effect of post-transplant stress on cork oak. With this objective, a study was carried out on a greenhouse, where the effect of fertilisation, mycorrhizal fungi inoculation, and amino acid supply were tested. Results showed that cork oak seedling capability to growth, expressed as total seedling dry weight, was positively affected by treatments, except when only fertilisation was applied. We verified that cork oak seedlings inoculated with mycorrhizal fungi presented better results in terms of aerial structures growth. Any of the treatments was suitable to contribute positively for tap root and total belowground dry weight accumulation. Only fine roots structures were sensitive to treatments effects; it was verified that both inoculated and non-inoculated seedlings subjected to fertilisation were capable to invest largely on the production of these structures (33 and 30%, respectively). To reinforce the cork oak seedling growth, the equilibrium between fertilisers and mycorrhizal fungi inoculation would probably be the better option to enhance the cork oak regeneration process. Thus, the balance between shoot and root systems growth would be guaranteed, fertilisation mainly for root system and mycorrhizal fungi inoculation for shoot growth.</p>
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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 | 0.001 |
| 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".