Identification of Resistance to Aflatoxin Accumulation and Yield Potential in Maize Hybrids in the Southeast Regional Aflatoxin Trials (SERAT)
Bibliographic record
Abstract
Aflatoxins pose a serious health hazard to humans and livestock, requiring significant economic cost in identifying and disposing of contaminated grain. Since 2003, a multi‐environmental trial of public breeding maize (Zea mays L.) hybrids across multiple programs in the southeastern United States has evaluated accumulation of aflatoxin following inoculation with the fungus Aspergillus flavus Link. The Southeast Regional Aflatoxin Trial (SERAT) was formed to identify public germplasm with the most consistent resistance to aflatoxin accumulation and to evaluate their essential agronomic traits in different environments. Yield and related agronomic traits were evaluated in 13 locations; aflatoxin levels were evaluated in four. From 2006 to 2015, the 295 experimental hybrids, composed of varying percentages of tropical and subtropical germplasm, exhibited lower levels of aflatoxin on average at 323 versus 370 ng g−1 for the commercial checks, while the check average of 10.1 Mg ha−1 exceeded the research program average yield by 20%. Repeatability for log‐transformed aflatoxin levels exceeded 0.50 in most years, while yield was mostly above 0.75. Testing for Type II stability indicated a positive response of high‐yielding lines to better environments. The SERAT program enabled the identification of 13 top‐performing experimental hybrids that have yielded on par with or exceeded check averages and had aflatoxin levels significantly lower than check averages.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".