New Leafy Greens—Plant Age Effects on Perilla Leaves
Bibliographic record
Abstract
Given that, not much is known about potential yields and nutritional quality of perilla [Perilla frutescens (L.) Britton, Lamiaceae] for production in eastern USA as food, we evaluated fresh leaves of five accessions during 2021. The seeds were germinated in a greenhouse and about 15-day old seedlings were transplanted to the field on black-plastic covered raised beds. Leaves were harvested for analyses at 69 and 85 days after transplanting. Four accessions with green-colored leaves performed better than one with purple leaves. Leaf fresh weights varied from 105 to 279 g per plant whereas number of leaves per plant varied from 368 to 465. Concentrations (g/100 g) of protein, fat, fiber, Ca, P, K, Mg, and S in fresh perilla leaves produced in Virginia contained 17.9, 4.2, 7.3, 1.3, 0.39, 2.0, 0.40, and 0.17, respectively whereas mean values (mg kg-1) for Fe, Cu, Zn, and Mn were 291, 19.9, 40.5, and 56.2. Leaves of perilla produced in Virginia contained considerable more protein (about 4 times more), fiber and fat than literature values demonstrating location differences. Effects of plant age were significant on all plant and leaf physical traits—values from 85 day old plants were significantly higher than those from 69 day old plants. Based on our preliminary results, we have identified PI481701 as the optimal accession. We concluded that perilla is a potential niche crop for Virginia farmers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".