Comparism of Yield Potential of Hybrids and Open Pollinated Varieties of Maize Seeds in Northern Guinea Savanna Alfisols, North-West Nigeria
Bibliographic record
Abstract
A two year study was conducted on maize (Zea mays L.) at the I.A.R farm, Samaru, Zaria, Nigeria, during 2013 and 2014 cropping season. The objective was to investigate the yield potentials of hybrids and OPV maize varieties under the same management condition. The experiment consisted of six maize varieties as the treatments, this includes; four hybrid seeds from some selected seed companies in North-western Region and two open pollinated varieties from I.A.R. The treatments were laid out in a randomized complete block design with four replicates. The results showed that all the six varieties of seeds were good planting materials, with highest disease incidence of 0.5 (mean across treatments) in 2014 for Mr-White from Manoma seed company and highest mean value of off-types (0.75) from the hybrid seeds. Hybrid maize from Maslaha seed company (SDM-1) out yielded all other varieties in both 2013, 2014 and combine (4490.0Kgha-1, 5210.2 Kgha-1 and 4850.1 Kgha-1) respectively, while a hybrid seed- NG-Samaru had the least yield in both 2013, 2014 and combine (2586.7Kgha-1, 3632.4 Kgha-1 and 3109.6 Kgha-1) compared to open pollinated varieties from I.A.R (Sammaz 14 and Sammaz 34).
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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) | 0.000 | 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 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".