Effect of Genotype and Periodic Pruning on Storage Root Yield and Yield Components of Some Cassava Genotypes Under Rain-Fed Conditions In Ghana
Bibliographic record
Abstract
Cassava (Manihot esculenta Crantz) is cultivated primarily for its starchy roots which provide a staple for millions of people in the tropics. The foliage contains high levels of protein which can be harvested for human and animal feed. Twenty five cassava genotypes were arranged in a randomized complete block design with three replications to investigate their tolerance to periodic pruning with respect to effect on root yield and yield components. The cassava plants were periodically pruned starting from three months after planting and at three months intervals until root harvest at 12 months after planting. Storage root yields ranged between 8.3 – 26.2 t/ha and 28.9–85.5 t/ha for the pruned plants and the control respectively. The pruned plants produced average root yield of 14.7 t/ha compared with 51.5 t/ha from the control. Though periodic pruning resulted in significant reduction in all components measured, genetic variations were observed in the level of reduction. Observed root yield reduction ranged between 40–80%. Five genotypes; 96/1642, Afisiafi, Esambankye, Agbelifia and Bankyehemaa, recorded storage root yield reduction of less than 50% of their respective controls. Starch content and mean storage root weight were also significantly reduced by periodic pruning. The significant genetic variations in the reduction of these traits indicated different levels of tolerance which can be exploited in further studies to identify ideal cassava genotypes for dual purpose utilization for foliage and root production.
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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) | 0.001 | 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".