Vegetative Propagation of Cashew (Anacardium occidentale L.) by Softwood Grafting in Ghana
Bibliographic record
Abstract
An investigation was done to assess the graft success on seedlings and canopy substitution using grafting techniques, retention of basal leaves on the rootstock, age of rootstock and period of grafting in a randomize complete block design with twenty plants per treatment and replicated three times. Young vigorously growing cashew seedlings were used for grafting whilst poor performing cashew trees (in yield and young trees) were stumped to produce shoots for the top working. Significantly (p < 0.05) higher grafting success was obtained for softwood grafting technique in the month of July with October recording the lowest for canopy substitution. Grafting on 60 days old seedlings with the retention of four (4) matured basal leaves on the rootstocks significantly (p < 0.05) gave high success in graft union whilst the root stocks without basal leaves recorded low graft successes. However, there was significant (p < 0.05) off-shoots development below the graft union of the rootstock. Softwood grafting was the best technique for high graft success with the month of July being suitable period for grafting in canopy substitution. Retaining four (4) matured leaves at the base of 60 days old rootstock was the best for achieving high graft success with reduction of infection. An investigation was done to assess the graft success on seedlings and canopy substitution using grafting techniques, retention of basal leaves on the rootstock, age of rootstock and period of grafting in a randomize complete block design with twenty plants per treatment and replicated three times. Young vigorously growing cashew seedlings were used for grafting whilst poor performing cashew trees (in yield and young trees) were stumped to produce shoots for the top working. Significantly (p < 0.05) higher grafting success was obtained for softwood grafting technique in the month of July with October recording the lowest for canopy substitution. Grafting on 60 days old seedlings with the retention of four (4) matured basal leaves on the rootstocks significantly (p < 0.05) gave high success in graft union whilst the root stocks without basal leaves recorded low graft successes. However, there was significant (p < 0.05) off-shoots development below the graft union of the rootstock. Softwood grafting was the best technique for high graft success with the month of July being suitable period for grafting in canopy substitution. Retaining four (4) matured leaves at the base of 60 days old rootstock was the best for achieving high graft success with reduction of infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".