Vegetative Development and Nutrient Absorption March of Sorrel (Rumex acetosa L.)
Bibliographic record
Abstract
Sorrel (Rumex acetosa L.) is an unconventional food plant. It is a perennial herbaceous plant that forms thickets. There are studies related to the accumulation of nutrients in sorrel, but there is no information on its absorption march and vegetative development. The objective of this study is to determine macronutrient absorption and biometric parameters of sorrel during 60 days after seedling transplantation (DAT) of seedlings. The experiment was completely randomized with eight treatments and four replications. It was conducted in a greenhouse. The treatments consisted of plant collection times, performed at 15, 20, 25, 30, 35, 40, 50 and 60 DAT. Plants’ biometric parameters (leaf blade length, relative leaf area, and shoot fresh and dry matter) and macronutrient absorption march were evaluated. Biomass, leaf blade length and relative leaf area of sorrel plants increased over time and, more markedly, after 35 DAT. The maximum levels of macronutrients accumulated in sorrel shoots, in descending order, were K > N > Ca > Mg > P > S. There was no significant difference in Ca and S contents among collection times, that is, the absorption and accumulation of these nutrients by sorrel did not vary throughout the evaluation time.
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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 | 0.001 |
| 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".