Crop yield and SOC responses to biochar application were dependent on soil texture and crop type in southern Quebec, Canada
Bibliographic record
Abstract
Abstract Changes to soil nutrient availability and increases for crop yield and soil organic C (SOC) concentration on biochar‐amended soil under temperate climate conditions have only been reported in a few publications. The objective of this work was to determine if biochar application rates up to 20 Mg ha −1 affect nutrient availability in soil, SOC stocks and yield of corn ( Zea mays L.), soybean ( Glycine max L.), and switchgrass ( Panicum virgatum L.) on two coarse‐textured soils (loamy sand, sandy clay loam) in S Quebec, Canada. Data were collected from field experiments for a 3‐y period following application of pine wood biochar at rates of 0, 10, and 20 Mg ha −1 . For corn plots, at harvest 3 y after biochar application, 20 Mg biochar ha −1 resulted in 41.2% lower soil NH $ _4^+ $ on the loamy sand; the same effect was not present on the sandy clay loam soil. On the loamy sand, 20 Mg biochar ha −1 increased corn yields by 14.2% compared to the control 3 y after application; the same effect was not present on the sandy clay loam soil. Biochar did not alter yield or nutrient availability in soil on soybean or switchgrass plots on either soil type. After 3 y, SOC concentration was 83 and 258% greater after 10 and 20 Mg ha −1 biochar applications, respectively, than the control in sandy clay loam soil under switchgrass production. The same effect was not present on the sandy clay loam soil. A 67% higher SOC concentration was noted with biochar application at 20 Mg ha −1 to sandy clay loam soil under corn.
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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 | 0.000 | 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) | 0.000 | 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".