Genetic Response of Selected Maize Genotypes to Gray Leaf Spot (Cercospora zeina L.) Infestation
Bibliographic record
Abstract
Gray leaf spot (GLS) caused by Cercospora zea-maydis and Cercospora zeina is one of the most yield limiting diseases of maize globally. Yield losses of up to 60 percent in susceptible genotypes are not uncommon. The objectives of the study were to evaluate the response of diverse maize genotypes to Gray leafspot infestation in western Kenya; determine the genetics of GLS resistance in maize inbred lines CML312, CML389 and to evaluate the relationship between GLS assessment methods, severity and lesion length. 13 maize inbred lines, 2F1 hybrids, and F2 populations of crosses MSN21 and CML389 or CML312 were evaluated under artificial GLS infestation during the 2007/08 seasons at Maseno university. Among the inbred lines, MSN21 was the most susceptible to GLS and had the highest disease severity rating. The inbred line CML389 and their F1 hybrids showed high levels of GLS resistance. CML312 and CML384 showed tolerance to GLS. Correlation between the lesion length and severity ratings was positive and highly significant (r = 0.9; P < 0.001), suggesting that both could be used in disease damage assessment. The frequency distribution of severity data for the F2 population of a cross between MSN21 and CML312 was continuous, suggesting that GLS tolerance is influenced by quantitative genes. A similar frequency distribution data for F2 population of a cross between MSN21 and CML389, showed 2 distinct peaks, and the genotypes within the 2 classes fitted a 9 to 7 ratio. This suggests that the resistance to GLS in CML389 may be conditioned by at least 2 major genes, with complementary epistatic interactions.
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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 | 0.000 |
| 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".