Extractable Soil Lipids and Microbial Activity as Affected by Bt and Non Bt Maize Grown on a Silty Clay Loam Soil
Bibliographic record
Abstract
Pyrolysis-gas (Py-GC) chromatography was used to characterize extractable lipids from Bt and non-Bt maize shoots and soils collected at time of harvesting. Py-GC-MS (mass spectrometry) showed that the concentrations of total alkenes identified in non-Bt shoots and soils were 47.9 and 21.3% higher than in Bt maize shoots and soils, respectively. N-alkanes identified were of similar orders of magnitude in Bt and non-Bt maize shoots, but were 28.6% higher in Bt than in non-Bt soils. Bt maize shoots contained 29.7% more n-fatty acids than non-Bt maize shoots, whereas the concentrations of n-fatty acids in Bt soils were twice as high as those in non-Bt soils. Concentrations of unsaturated fatty acids in Bt maize shoots were 22.1% higher than those in non-Bt maize shoots, while concentrations of unsaturated fatty acids were 22.5% higher in non-Bt than in Bt soils. The cumulative CO2-C evolved from soils under Bt and non-Bt crops was 30.5% lower under Bt as compared to non-Bt crops, whereas when maize shoots were added to Bt and non-Bt soils, the decrease in CO2-C evolved were 16.5 and 23.6%, respectively. Our data showed that the cultivation of Bt maize significantly increased the saturated to unsaturated lipid ratios in soils which appeared to negatively affect microbial activity.
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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) | 0.001 | 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".