Growth and Molecular Expression of Okra Seeds Interacted with Fourteen Mango Cultivars in Mixed Cropping System
Bibliographic record
Abstract
The present study was accomplished to study the effect of fourteen cultivars (Keitt, Ewais, White Succari, Tommy Atkins, Fajri Klan, Zebda, Alphonso, Sedeek, Naomi, Mesk, Baladi Dabsha, Baladi Arnaba, Cobania and Totapuri) of Mangifera indica L. leaves aqueous extracts (MILAE) on germination and some growth parameters as well as seedling protein profile of Hibiscus esculentus L. (okra seeds) in mixed cropping system. The study was extented to characterize and discriminate among the aforementioned cultivars. The allelopathic potential of fourteen cultivars of M. indica leaves aqueous extracts (MILAE) on germination efficiency and growth parameters of H. esculantus L. seeds (as a recipient bioassay material) was completely studied. Hypocotyl length (HL) was more sensitive than radicle length (RL) for all studied cultivars. At the all concentrations level, Mesk cultivar exerted the highest allelopathic effect, while Totapuri cultivar showed the lowest one on the germination percentage (GP), inhibition percentage (IP), the time to get 50% germination (T50), mean germination time (MGT), germination energy (GE), seed germination index (SGI), emergence percentage (EP), mean emergence time (MET), seedling emergence index (EI), seedling vigour index (SVI), hypocotyl (HL) and radicle (RL) lengths, seedling fresh (SFW) and dry (SDW) weights.Seedling protein electrophoresis data revealed that Tommy Atkins cultivar attained the minimum values for both the number of bands and the percentage of polymorphism, 6 bands and 27%, respectively. On the other hand, the maximum values were achieved from both Naomi and Totapuri cultivars, 11 bands and 51%. Reversibly, the genomic template stability (GTS %) oscillated from 32% in Cobania cultivar to 64% in specimen Tommy Atkins cultivar. The resulted dendrograms by using allelopathic and molecular data as well as seedling protein electophoresis ascertains three aggregations. The first assembly includes Sedeek, Naomi and Mesk cultivars. The second gathers Keitt and Ewais cultivars. While, the third clusters Fajri Klan, Zebda and Alphonso cultivars.
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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) | 0.000 | 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 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".