Evaluation of shade tolerance of one annual and five perennial <i>Medicago</i> species under different artificial shade levels
Bibliographic record
Abstract
ABSTRACT The objective of this study was to evaluate the shade tolerance of one annual and five perennial Medicago genotypes under different artificial shade levels and determine the shade tolerant candidates for an intercropping system. The results showed that shade significantly affected branch number and plant dry weight, but not plant height and leaf area. The mean branch number and dry weight plant −1 (g) across the tested genotypes were 42.5 and 2.2 under non‐shade condition, decreased to 39.5 and 2.0 at 25% shade level, and were further reduced to 17.2 and 0.4 at 75% shade level, respectively. The mean chlorophyll content (mg g −1 ) and maximum quantum yield of Photosystem II (F v /F m ) across the tested genotypes at 75% shade level (38.8; 0.6) were significantly lower than other shade levels (46.6–47.3; 0.69–0.70). Antioxidant enzyme activity and malondialdehyde production in Medicago leaves increased concomitantly with increased shade levels compared to non‐shade control. The evaluation showed that annual M. polymorpha ‘Jinhuacai’ (range of mean: 0.97–5.97 g) significantly out‐yielded those perennials (range of mean: 0.26–2.57 g) by a wide margin at all shade levels. This study would provide baseline information on shade tolerance of Medicago species for the selection of intercropped candidates in an intercropping system.
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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 | 0.000 |
| 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 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".