Weed competition in organic and no-till conventional soils under nonlimiting nutrient conditions
Bibliographic record
Abstract
Abstract Some well-managed organic soils are known to have higher crop yield potential than conventionally managed soils due to the greater soil quality and the ability to tolerate weed competition. However, low available soil mineral N and P in some organic systems may mask such soil quality–related benefits. We hypothesize that when plant-available N and P are not limiting, tillage-based highly diverse organic crop rotations have less yield loss (better crop tolerance) due to weed competition and higher crop yields than no-till conventional systems with low-diversity rotations. A greenhouse study was carried out in Saskatoon, Canada, using long-term (18-yr) organically managed soils (ORG) and no-till conventional soils (CONV) with three crop rotation diversities (LOW, MEDIUM, and HIGH) to compare the crop tolerance to weed competition under standard soil nutrient management conditions and under excess supply of mineral N and P. Under fertilized conditions, crop biomass increased by 50% and 69% in ORG and CONV systems, respectively. Weed biomass was similar between ORG and CONV systems under nonfertilized conditions but was 14% greater in CONV when excessive N and P were supplied. Crop biomass loss (crop tolerance) was not different among cropping systems under excess fertilizer or under standard fertilizer levels. Even with greater weed biomass under fertilized conditions, the CONV system showed crop tolerance similar to that of the ORG system. Under nonfertilized conditions, the crop biomass yield was 43% lower in ORG compared with CONV, and even after mineral N and P were applied, ORG systems showed less (17%) crop biomass than CONV. Further, differences in crop tolerance were not identified among crop rotations under both fertilizer levels. Overall, this study revealed that there were no yield benefits or better crop tolerance to weed competition in organically managed soils compared with no-till conventional soils, even under nonlimiting soil macronutrient conditions.
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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 | 0.001 |
| 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".