Crop management effect on arbuscular mycorrhizae and root growth of flax
Bibliographic record
Abstract
Monreal, M. A., Grant, C. A., Irvine, R. B., Mohr, R. M., McLaren, D. L. and Khakbazan, M. 2011. Crop management effect on arbuscular mycorrhizae and root growth of flax. Can. J. Plant Sci. 91: 315–324. The effects of two tillage systems, two preceding crops and the use of phosphorus (P) fertilizer on arbuscular mycorrhizal fungi (AMF) colonization, root biomass and root size of flax (Linum usitatissimum L.) were evaluated at two sites in Manitoba, Canada. The Brandon Research Centre Farm site had been historically managed under conventional tillage (CT), and the Manitoba Zero Tillage Research Association Farm site under reduced tillage (RT). The preceding crops were a mycorrhizal crop, wheat (Triticum aestivum L.), and a non-mycorrhizal crop, canola (Brassica napus L.), grown under RT or CT using rates of 0, 11 and 22 kg P ha−1 applied as monoammonium phosphate (MAP). Phosphorus was applied to the following flax crop as MAP at rates of 0 or 11 kg P ha−1. Flax root biomass was larger in all site-years when wheat rather than canola was the preceding crop. Also, AMF colonization and root size of flax increased in 3 and 2 site-years, respectively, when grown after wheat. Flax's root biomass decreased under CT and AMF colonization decreased when P was added either to the previous crop or to flax only in one site year. Weather conditions may have enhanced the effects of preceding crop, P fertilizer and tillage.
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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) | 0.000 | 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".