Effects of nematicides on nematode population densities and crop yield in a turnip-corn-pea cropping system
Bibliographic record
Abstract
Four management systems were evaluated in a six-year study to control nematodes in a turnip-corn-pea annual cropping System on plots of Tifton loamy sand naturally infested with Meloidogyne spp. (about 90 % M. incognita and 10% M. hapla), Pratylenchus spp. (about 65% P. scribneri, 25% P. brachyurus, and 10% P. zeae), Paratrichodorus minor and Criconemella ornata. Turnip (Brassica campestris subsp. rapifera) supported low numbers of all nematodes. 'Pioneer 3369A' corn (Zea mays) supported greater numbers of all nematodes than 'Funks G-4507'. Population densities of Meloidogyne spp. juveniles (J2) were suppressed below 80 per 150 cm3 of soil by 98 % methyl bromide + 2 % chloropicrin and 20 % methyl isothiocyanate + 80 % chlorinated C3 hydrocarbons on turnip and corn, and increased rapidly on 'Pinkeye purplehull', but not on a resistant cultivar, 'Worthmore' pea (Vigna unguiculata). Population densities of other nematodes were not affected by cultivar of pea or the nematicide, ethoprop. Fenamiphos was more effective than ethoprop in suppressing nematode population densities. Increases in crop yield in the intensive management system ranged from 4% to 52% over untreated controls.
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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) | 0.000 | 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 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".