Efficacy of crop succession and bionematicide application for controlling <i>Pratylenchus brachyurus</i> in soybean
Bibliographic record
Abstract
Integrated management is essential for keeping nematode populations below the economic damage thresholds. This greenhouse study evaluated the effects of applying commercially available bionematicides to a range of cover crop species on the infestation by Pratylenchus brachyurus of successively planted soybean roots. Initially, soybeans were inoculated with 500 specimens of Pratylenchus brachyurus and cultivated for 85 days. Afterward, greenhouse pots were planted with brachiaria (Urochloa ruziziensis), crotalaria (Crotalaria spectabilis), pearl millet ADR 300 (Pennisetum glaucum), or maize (Zea mays), with or without bionematicide treatments. The bionematicides used were Bacillus licheniformis + B. subtilis + Purpureocillium lilacinum (Trials 1 and 2) and P. lilacinum + Trichoderma harzianum (Trials 3 and 4). In Trial 1, crotalaria reduced nematode reproduction by 97% without bionematicide treatment, achieving 90% control when combined with bionematicides. In Trial 2, bionematicides applied to cover crops + soybean reduced nematode populations by 42%, with crotalaria achieving 94% control. Trials 3 and 4 confirmed that cover crops, particularly crotalaria, reduced nematode populations compared to maize. The combination of P. lilacinum + T. harzianum and crotalaria was the most effective, achieving up to 97% control. Overall, bionematicide agents were most effective when applied to both cover crops and soybean, reducing nematode densities by over 80%. These findings underscore the efficiency of integrating crotalaria with bionematicides as a sustainable strategy for managing P. brachyurus in soybean production systems.
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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".