Multidimensional Analysis Associated With Growth Analysis in the Selection of Organic Substrates for the Production of Tomato Seedlings
Bibliographic record
Abstract
Tomato (Solanum lycopersicum L.) is a crop whose cultivation is of great importance in economic and social aspects. However, the development of efficient and low-cost technologies is essential for the growth of agricultural activity in the region. Among the most studied technologies, the production of quality seedlings in organic substrates is highlighted. In this context, the objective was to evaluate the development of tomato seedlings produced with organic substrates, using the decomposed stem of babassu palm and goat manure, using the multidimensional technique with the help of canonical functions associated with growth analysis. The treatments consisted of 25%, 50% and 75% sand aggregates, 25% to 50% sand addition, 25% to 50% sand and commercial substrate, established in a completely randomized design with 28 treatments and four replications in a 7 × 4 factorial scheme, the first factor consisting of seven substrates and the second of four evaluation periods (7, 14, 21, 28 days after emergence). Were analyzed shoot length and main root length; dry mass of the aerial part and of the root system and leaf area. These variables were analyzed through multidimensional analysis with the help of canonical functions and growth analysis. In general, the substrates consisting of goat manure and sand were superior to the substrates consisting of the decomposed palm tree stem and the commercial substrate. The alternative substrate formed by the mixture of goat manure, in the proportion of 25% of sterilized sand + 75% goat manure, constitutes the best option for the production of tomato seedlings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.009 |
| 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".