Evaluation of Detection Methods for Genetically Modified Traits in Genotypes Resistant to European Corn Borer and Herbicides
Bibliographic record
Abstract
Detection of genetically modified (GM) traits in corn (Zea mays L.) is urgently needed for preservation of genetic identity and marketing GM products. A laboratory study was conducted to evaluate the efficiency, accuracy, and reliability of different analytical methods to detect GM traits in corn. Samples with known fractions of GM concentrations (Bacillus thuringiensis [Bt], Liberty Link [LL] and stacked [Bt/LL] genes) from commercial seed companies and those derived from yellow kernels in a white corn ear, outcrossed by pollen of neighboring Bt hybrid, were tested by lateral flow quick test kits and by enzyme-linked immunosorbent assay (ELISA)-based test strips purchased from different companies. Liberty Link hybrids are resistant to glufosinate (Liberty or Basta) herbicides, whereas Bt corn is developed for the control of European corn borer (Ostrinia nubilalis). Selected samples of GM concentrations were also tested in a commercial laboratory using DNA-based polymerase chain reaction (PCR) test. The results demonstrated that qualitative lateral flow quick tests could detect samples containing 1% or higher Bt and 2% or higher LL concentrations within the recommended time limit of the test. Faint test lines for samples containing 0.5 to 1% Bt or 1 to 2% LL concentrations appeared if samples remained in the test cup overnight. ELISA test strips detected the Bt content semiquantitatively in the range of 0.5 to 2.0%. Grain samples derived from non-Bt corn outcrossed by neighboring Bt pollen had usually lower GM concentrations than commercial GM seed samples. Both ELISA- and DNA-based PCR tests distinguished samples with GM concentrations between 0.1 to 0.5%, but the precision of quantification at this range was very low and results were highly inconsistent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 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 teacher head, 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".