Physical characterization of Euterpe precatoria Mart. seeds and the influence of ultrasound on seedling emergence
Bibliographic record
Abstract
The irregular and slow seedling emergence of Euterpe precatoria Mart. is a challenge in seedling production. Therefore, this study aimed to characterize the physical aspects of the seeds and evaluate the potential of ultrasound to stimulate emergence. The seeds were treated using a total of 36 treatments (frequencies of 1 and 3 MHz; intensities of 0.5, 1.0, 1.5, and 2.0 W/cm², and times of 3, 5, 7, and 9 minutes) in a completely randomized research design. Morphological characteristics, viability, moisture content, and 1,000-seed weight were evaluated. The variables analyzed included emergence, speed index, and mean emergence time. Overall, the seeds had rounded shapes, with an average length of 15.09±0.24 mm, width of 12.45±0.83 mm, area of 144.34±4.02 mm2, perimeter of 48.32±1.78 mm, circularity of 0.79±0.03 and roundness of 0.84±0.08. The viability was 97.00%, moisture content of 16.05% and weight of one thousand seeds of 923.55 g, characterizing them as large. The 1MHz-1.0W/cm² treatment at 5 and 7 minutes reached 86.00±5.29% and 93.00±1.00% emergence, respectively, with high-speed indexes of 0.58±0.02 and 0.61±0.01 seeds/day, respectively. In addition, low average emergence times of 37.55±1.07 and 38.51±0.67 days after 5 and 7 minutes of ultrasound treatment were obtained respectively. It is concluded that the use of ultrasound is promising to accelerate the emergence of Euterpe precataria Mart. seedlings, representing a green sustainable alternative for forest nurseries and restoration projects in the Amazon.
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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 | 0.000 |
| 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 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".