Field‐Grown Bt and non‐Bt Corn: Yield, Chemical Composition, and Decomposability
Bibliographic record
Abstract
Bt (Bacillus thuringiensis) corn (Zea mays L.) accounted for 74.5% of the corn acreage in eastern Canada in 2009. Reports that Bt corn has greater yield and lignin concentrations than unmodified corn have raised questions about its effect on the soil ecosystem. Our objectives were to evaluate the biomass of field‐grown Bt and non‐Bt corn, the chemical composition of different corn components that remain as residues in the field after harvest, and the effect of the Bt modification on residue decomposition. Nine Bt corn hybrids and their near isolines were field‐grown in 2008 and 2009. Grain and stover yields were measured and leaves, stems, and roots were collected and analyzed for lignin, C, and N concentrations. Stem sections from a Bt/non‐Bt corn pair were buried in the field and sampled periodically during 1 yr. No difference in yield or lignin concentrations due to the Bt gene was noted; however, N concentration in Bt stems was significantly greater than in non‐Bt stems in 1 yr of the 2‐yr study. Leaves had less lignin and a lower C/N ratio than stems and roots in both years. In buried field litterbags, the decline in C/N ratio and mass loss suggests that Bt stems were decomposing more rapidly than non‐Bt stems. We conclude that the Bt gene does not affect the agronomic performance or the chemical composition of corn in fields without herbivory, and that Bt corn residue may be more susceptible to decomposition than non‐Bt corn residue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".