Impact of Seed Size on the Seedling Vigour, Dry Matter Yield and Oil Content of Jatropha (Jatropha curcas L.)
Bibliographic record
Abstract
Seed size is a trait of the plant that affects seed germination and seedling survival. This study aims to assess the growth response of J. curcas to different seed sizes. A pot experiment was conducted to evaluate the effects of J. curcas seed sizes on the seedling vigour and seed component. The seeds were fractioned into three sizes visually into: large, medium and small and by 1000 seeds weight (SW). Seedling vigour was assessed by: germination % (G%), seedling length cm (SL), seedling vigour index, SVI, seedling growth rate, SGR, and speed of germination, SOG as well as proportion of cake, shell and oil content (OC) expressed as% of the seed. Results obtained shows that G% and the SOG were not affected by seed sizes but by other factors within the seed. However, seedling vigour expressed as SL, SVI and SGR increased significantly (P ≤ 0.05) with increase in seed sizes. Proportion of cake, shell and oil component of J. curcas seeds increased with increasing seed sizes while 60% of the seed is made up of the cake from where the oil is extracted. Dry matter yield, DMY significantly (P ≤ 0.05) increased with increase in seed size from 6.41 g/plant in large seeds to 2.61 g/plant in small seeds. There is positive and strong significant correlation between, SW and DMY (r = 0.91**), yield increase (r = 0.82**), OC (r = 0.85**), % cake (r = 0.94**). Findings revealed that larger seed had higher potential of producing vigorous plants with eventual high crop yield and higher OC.
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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".