Emergence and Initial Growth of the Seedlings of Euterpe oleracea Mart. Seeds of Different Ecotypes in Function on the Substrate
Bibliographic record
Abstract
In Brazil, the assai (Euterpe oleracea Mart.) is a native palm of the Amazon biome, being exploited in an extractive and predatory way to obtain palm heart and processed pulp. In recent years, there has been an increase in the exploitation of commercial plantations in the country, since extractivism and management of native areas are not able to meet growing demand. In this way, companies of the sector and public institutions have invested in new technologies, such as the improvement of plants, which has increased the demand for good quality seeds, coming from natural ecotypes. Thus, the objective of this work was to evaluate seeds of E. oleracea from three ecotypes regarding the emergence and initial growth of the seedlings in different substrates to guide future plant selection. Seed lots from three assai berry ecotypes were evaluated for water content, seedling emergence, first count, seedling emergence speed index, seedling length and dry mass. The experimental design was completely randomized, with four repetitions of 50 seeds, sown on different substrates. In the physiological characteristics of the seeds and seedlings, there are differences of the three E. oleracea ecotypes. These ecotypes make it possible to identify and select assai palm’s mother plants of Luiz Domingues (IG) and Maracanã (V) natives of areas of the igapó and várzea, respectively, as producers of better quality seeds and seedlings in an alternative substrate (composed of sand, agricultural soil and cattle manure in a proportion of 2:2:1) and, commercial substrate (FORTH® compound of pinus and gray bark), respectively.
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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".