Seaweed Extract Ascophyllum nodosum (L.) on the Growth of Watermelon Plants
Bibliographic record
Abstract
Aims: The objective of the research was to evaluate the influence of the seaweed extract applications, Ascophyllum nodosum (L.) to the productive development and quality of watermelon plants.
 Study Design: Two experiments were carried out. For experiments I and II, the completely randomized design was applyed in factorial schemes 2x6 and 2x4, respectively, with five replications each.
 Place and Duration of Study: The experiments were carried out at the Department of Plant Sciences (DPS) of the Rural Federal University of Semi-Arid (UFERSA), Campus Mossoró – RN, from January to May 2014.
 Methodology: Experiment I consisted on seed treatments [soaking in potable water and Acadian®] and application of six doses (0, 1, 2, 3, 4 and 5 mL L-1); experiment II, a combination of two seed treatments [soaking in potable water and Acadian®] and four periods (0, 7, 10 and 14 days) under the dose of 3.0 mL L-1.
 Results: The interaction between seed treatment and application of different doses, presented highest values observed for the variables, plant height, fresh shoot weight and fresh root weight were for A. nodosum (L.). More effects for seed treatment when there is no application of Acadian® is observed. It can be inferred that there is interaction among the factors, since the different parts of the plant respond in different ways to the treatment of seeds and the different periods of application. Also highlighted, when submitted to applications with Acadian®, watermelon plants had a similar effect, with closer values, excluding only the applications spaced in 7 days, which showed more interaction factors.
 Conclusion: Seed treatment with Acadian® and the doses of 3.0 and 4 mL L-1 were more efficient in the watermelon seedlings production. Applications in intervals of 7, 10 and 14 days were most promising, regardless the seed treatment.
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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 | 0.001 | 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 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".