Assessment of Sap Production Parameters From Spathes of Four Coconut (Cocos nucifera L.) Cultivars in Côte d’Ivoire
Bibliographic record
Abstract
Several palm plants have social and economic roles worldwide by providing drinks from their sap. In Côte d’Ivoire, management of the coconut sap is not yet practiced. In this study, parameters related to production of sap have been assessed from four coconut cultivars namely PB 113+ and PB 121+ hybrids and WAT and MYD varieties. From all the unopened inflorescences (spathes) studied into the coconut crown, whose ranks varied from 7 to 9, that of rank 8 yielded the highest volume of sap. From this spathe, the PB113+ hybrid provided the best yield of sap (61.81 ± 20.41 l). Most important proportion of that sap volume was recorded at the morning harvesting. The sap production duration of a spathe varied from 24 ± 1.87 days (MYD) to 46.78 ± 1.86 days (PB 113+). That duration depended on the length of spathes and regular sap flow allowed by them. Furthermore, the PB 113+ had the highest number of fruits (NBF = 174.33 ± 78.45 fruits). The results showed that volume of sap available is closely related to the length of production (r = 0.78) and the cultivar’s nut yield (r = 0.82). The use of PB 113+ hybrid which provided highest quantity of sap is recommended for promoting the production of coconut sap in Côte d’Ivoire in order to improve the benefits derived from this plant.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".