Consistency of performance of early-maturing maize cultivars in <i>Striga-</i>infested and <i>Striga</i>-free environments
Bibliographic record
Abstract
Badu-Apraku, B., Yallou, C., Oyekunle, M., Akinwale, R., Aweke, G. and Kamara, A. 2015. Consistency of performance of early-maturing maize cultivars in Striga-infested and Striga-free environments. Can. J. Plant Sci. 95: 1073–1084. Despite the immense potential of maize (Zea mays L.) in savannas of West and Central Africa (WCA), production and productivity is constrained by Striga hermonthica parasitism. Sixteen early-maturing cultivars were evaluated at two locations in Nigeria and three locations in the Republic of Benin from 2007 to 2009 to assess the grain yield, stability and the consistency of the rankings of the cultivars under Striga-infested and Striga-free environments. The combined analysis of variance showed significant (P<0.01) cultivar and cultivar×environment interactions for grain yield and other traits under Striga-infested and Striga-free environments. The test of concordance was significant (P<0.001) for grain yield (W=0.68), number of emerged Striga plants (W=0.74) and Striga damage (W=0.56) under Striga infestation, indicating stability of resistance in the cultivars developed from diverse sources under artificial S. hermonthica infestation across environments. There was high consistency of the rankings of the cultivars for grain yield and other Striga-resistance traits under Striga-infested and Striga-free environments in Benin and Nigeria. The additive main effects and multiplicative interaction (AMMI) biplot analysis for grain yield revealed POOL15SR/ACR94TZECOMP5-W/ACR94TZECOMP5-W and 2004 TZE-Y Pop DT STR C4 as the most stable cultivars with above-average mean grain yield in Striga-infested environments and they can be combined with other crop management options to control the parasite in the Striga endemic environments. Cultivars TZE Comp 5-W C7F2 and TZE Comp5-Y C6 S6 (Set B) had less Striga damage and number of emerged Striga plants across test environments. These cultivars could therefore serve as unique sources of favorable alleles for improving Striga resistance in maize in different production environments and farming systems.
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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 | 0.001 | 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".