Interaction Between Yellow Flesh Cassava Genotypes and Environmental Conditions Across Three Agro-Ecological Zones in Ghana
Bibliographic record
Abstract
New yellow-fleshed cassava genotypes are ready, highlighting the urgent need to select robust genotypes that resist diseases, thrive in diverse environments, and boost productivity for Ghanaian farmers. Nine yellow-fleshed cassava genotypes were evaluated alongside a white-fleshed reference variety in three different on-station field locations (Asuansi, Wamaso, and UCC locations) in Random Complete Block Design (RCBD) in four replications. Significant differences (p < 0.05) were found among the ten genotypes in traits like height, disease resistance, and yield. The GGE biplot analysis unveil four top-performing yellow-fleshed genotypes (12B, 1011A, 5B, 11B) consistently excelled across the Asuansi, Wamaso, and UCC locations, showing high stability and high yield potentials. It therefore recommended that these genotypes will undergo off-station field trials for validation, with the goal of introducing them as novel varieties to benefit Ghanaian 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 | 0.001 | 0.001 |
| 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".