Propagation and Vegetative Development of Portulaca oleracea Linn. in Different Substrates
Bibliographic record
Abstract
UFP’s are unconventional food plants, which can be included in food and feed, but underutilized because they are few known and/or researched. Portulaca oleracea Linn, known as a wigworm, is considered a weed due to its easy spread in different places, has potential to be included in the diet of people, so that they can take advantage of its medicinal, nutritional and landscape benefits. In view of the above, the objective of this research was to evaluate the vegetative development of the bollworm cultivated in different substrates to obtain a better production of green mass besides adding higher medicinal and/or nutritional contents. The experimental design was a completely randomized design with 6 treatments: 1-Barranco soil (Witness), 2-Soil + Bovine manure, 3-Soil + Commercial substrate, 4-Soil + Charred rice straw, 5-Soil + Bovine manure + Charred rice straw, 6-Soil + Bovine manure + Commercial substrate and 5 replicates. The seed germination rate was evaluated at five, ten and 15 days after sowing (DAS). At 70 DAS the total fresh mass of the plants and total dry mass in grams, plant height, main root length and number of leaves were evaluated. The substrate composed of ravine soil + bovine manure + charcoal rice straw provided the best indices of development of the bollworm plant. The combination of three components for the formation of a substrate favored fresh and dry biomass.
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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) | 0.001 | 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 | 0.001 |
| 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".