Introgression of Banded Leaf and Sheath Blight (BLSB) Resistance from Teosinte to Maize Cultivar
Bibliographic record
Abstract
Maize (.) is a member of the family and is targeted as the world's most important strategic cereal food crop.This Zea mays L Poaceae study was planned to screen the maize-Teosinte RILs population for banded leaf and sheath blight and agronomic traits.A total of 338 maize-Teosinte recombinant inbred lines (RILs), derived from cross between the high popping volume (HPV) Canadian popcorn inbred line (susceptible) as the female parent and Teosinte (wild relative) as the male parent (resistant).The data were recorded for agronomic traits and disease score for banded leaf and sheath blight .The mean sum of squares due to genotypes were observed highly significant (p<0.01) for all the trait studied.The 100 seed weight, an important trait showed highly significant positive correlation with number of seed rows per cob and cobs length.Path coefficient analysis revealed direct positive effect of cob length, number of seed rows per cob and plant height on grain yield.The first two Principal component values used to construct biplot graphs explained 39.70% of the total variation.The four maize-Teosinte RIL lines viz.; RIL-210, RIL-272, RIL-314 and RIL473 were screened resistant to banded leaf and sheath blight, which is a good source of BLSB resistance and would be utilized in breeding for maize improvement program.The recombinant inbred lines viz., RIL-6, RIL-26 and RIL-419 were identified as a better-performing line for multiple agronomic traits which, would also utilized to improve agronomic performance of maize.
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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 | 0.001 |
| 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".