Nontimber Forest Product Yield and Income from<i>Thaumatococcus daniellii</i>under a Mixed Tree Plantation System in Ghana
Bibliographic record
Abstract
Thaumatococcus danielliiis a wild sourced tropical understorey herb that is harvested for its foliage and fruits from which thaumatin—a proteinous sweetener—is extracted. With increased demand for natural sweeteners, uncontrolled harvesting ofT. danielliifrom the wild is suggested to be neither sustainable nor match industrial demands. This study determined the implication of controlled foliage harvesting ofT. danielliiunder a mixed indigenous tree plantation stand.T. danielliiplants within plots of dimension 3 m × 4 m were thinned to uniform foliage population of about 12 leaves/m2and subsequently harvested at 16 weeks interval for 64 weeks at four different foliage harvesting intensities: (i) no harvesting (control), (ii) 25% harvest, (iii) 50% harvest, and (iv) 75% harvest. Data on agronomic characters and total income from the sale of fruit and harvested foliage were collected and analysed. We found that foliage harvest intensity affected (P<0.001) number of flowers in the order: 18 (control) > 6 (25%) ≥ 1 (50%) and 0 (75%). Foliage harvest intensity also significantly (P=0.036) influenced fruit number and ranged from 11458/ha for the control to 4583/ha for the 75% harvest. Total income from fruit and foliage sales was greatest for the 50% harvest (US $ 17,191.32), followed by 75% harvest (US $ 12, 310.24) and lowest for the no harvest treatment (US $ 107.44). Thus, proper management ofT. danielliithrough controlled harvesting of the foliage under mixed tree plantation system could promote sustainable yield and income to farmers.
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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".