Blueberry Propagation by Minicuttings in Response to Substrates and Indolebutyric Acid Application Methods
Bibliographic record
Abstract
The nursery plants supply is one of the most important factors that limites blueberries production in some areas, due to some propagation difficulties observed on this species. In this way, this study aimed to evaluate substrates and IBA application methods on ‘Powderblue’ blueberries (Vaccinium ashei) minicuttings rooting, as well as to verify the rooting development in different periods. The study was divided in two experiments. The first one aimed to evaluate ‘Powderblue’ blueberry minicuttings rooting in three substrates (pine bark, carbonized rice husk and vermiculite) in response to two indolebutyric acid (IBA) application methods: 50% alcohol solution and talc. The second experiment aimed to evaluate ‘Powderblue’ blueberry minicuttings rooting using the best substrate recorded in the first trial (pine bark) and two IBA application methods associated to three periods of rooting access, in order to obtain the ideal rooting period and root development. In the first experiment the rooting percentage presented significant difference among the substrates; the higher percentage of rooted minicuttings occurred in pine bark substrate (68%). Regarding the methods used to IBA application, the talc method was more efficient to promote minicuttings rooting. In the second experiment, it was observed an increase in cutting rooting percentage from 55 to 84%, according to the evaluated seasons; however, the IBA application method did not influence the rooting percentage. Therefore, to produce ‘Powderblue’ blueberry plants from minicuttings it is recommended to use pine bark as substrate and talc as method to IBA application, transplanting the nurseries at 110 days after planting.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".