Forage Pearl Millet and Marigold as Rotation Crops for Biological Control of Root‐Lesion Nematodes in Potato
Bibliographic record
Abstract
Risk of crop damage by root‐lesion nematode [ Pratylenchus penetrans Cobb] (RLN) can be minimized through rotation with suppressive crops or fumigation. Forage pearl millet [ Pennisetum glaucum L. ‘Canadian Forage Pearl Millet Hybrid 101’ (CFPM 101)] was ranked against a known suppressive host [marigold ( Tagetes erecta L. ‘CrackerJack’)], a known supportive host [rye ( Secale cereale L. ‘Danko’)], grain pearl millet [‘Canadian Grain Pearl Millet Hybrid 1’ (CGPMH‐1)], and forage sorghum [ Sorghum bicolor L. ‘Canadian Forage Sorghum Hybrid 17’ (CFSH‐17)] during rotation‐susceptible crop cycles with potato ( Solanum tuberosum L. ‘Russet Norkotah’). In the two experiments (A and B), fewer soil RLN were found in CFPM 101 and marigold than in rye plots in both the rotation and potato crop years. Potato roots contained fewer RLN after marigold (445 and 193 g root −1 for Exp. A and B, respectively) than after rye (4063 and 4358 g root −1 for Exp. A and B, respectively), even postfumigation after rye (1223 and 972 g root −1 for Exp. A and B, respectively). Potato root RLN counts were less after CFPM 101 (1571 g root −1 ) than after rye (nonfumigated) in Exp. A. Potato yield correlated negatively with the soil RLN population. Total (Exp. B) and marketable (Exp. A) potato yields were greater following CFPM 101 or marigold than following the rye (nonfumigated) rotation and were equal to the rye‐fumigated rotation with one exception (greater total yield after marigold than rye‐fumigated in Exp. B.) Based on these two field experiments, we conclude that CFPM 101 controls RLN in the subsequent potato crop.
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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".