Effects of crop rotations on carrot yield and on the nematodes Pratylenchus penetrans and Meloidogyne hapla
Bibliographic record
Abstract
Carrot yield (Daucus carota) and population levels of the root-lesion nematode Pratylenchus penetrans and the northern root-knot nematode Meloidogyne hapla were measured in five rotation crops and in subsequent carrot crops at three field sites (1998-1999, 1999-2000, and 2000-2001). Total and marketable carrot yields averaged over the three sites did not differ in the crop sequences but there was a difference among sites. The total yields at sites 1, 2, and 3 were 77.86, 68.12, and 30.33 tonnes ha-1, respectively. Marketable yields were 59.04, 60.62, and 24.11 tonnes ha-1 at sites 1, 2, and 3, respectively. The lower yields were attributed primarily to less rainfall during July and August in 2001, and possibly to northern root-knot nematodes that were more prevalent at site 3. Mean levels of root-lesion nematodes in soil were highest (2690 nematodes kg-1) in carrot that followed timothy (Phleum pratense cv. Common), lowest (1100 nematodes kg-1) in carrots that followed marigold (Tagetes erecta cv. Crackerjack), and intermediate after barley (Hordeum vulgare cv. Chapais), pearl millet (Pennisetum glaucum cv. Millet 101), and annual ryegrass (Lolium multiflorum cv. Lemtal). Root-lesion nematode populations were also lower in marigold than in the other crops. Northern root-knot nematodes were not detected in rotation crops. The study indicated that carrot yields did not differ irrespective of the previous crop, but root-lesion nematode populations in soil at harvest were highest in carrots that followed timothy and lowest in carrots that followed marigolds. Population levels of root-knot nematodes in carrots did not differ among the crop sequences.
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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 | 0.001 |
| 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 | 0.000 |
| 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".