Filter Pie in the Control of the Nematoid of Root Lesions in the Soybean and Corn
Bibliographic record
Abstract
The efficiency of waste from industrial processing has been increasingly studied in the control of phytonematoids, especially filter cake, coffee husks and sugar cane bagasse. The objective of this study was to evaluate the effect of organic residues through the use of filter cake to reduce the population density of Pratylenchus brachyurus (Tylenchida: Pratylenchidae). The first experiment was conducted in a greenhouse in the completely randomized design in the 2 × 4 factorial scheme (soybean genotypes vs. filter cake doses) with four replications using soybean genotypes AS 3810 IPRO and LG60163 IPRO and the second experiment was carried out under the same conditions, with maize AG 1051 with four doses of filter cake with 7 replications. In both experiments, the planting was carried out in an area located in the city of Goianésia, Goiás, Brazil. The results showed that the population density of Pratylenchus brachyurus in the maize crop to grow AG 1051 did not show statistically significant difference by applying the different doses of filter cake. In soybean genotypes AS 3810 IPRO and LG60163 IPRO were affected in ways contrary to phytonematoid infestation, in which AS 3810 IPRO showed a population increase according to the increase of the applied amounts of filter cake, whereas in the cultivar LG60163 IPRO there was a decrease for doses of 10 tonnes/ha-1 and 30 tonnes/ha-1, with an increase of only 20 tonnes/ha-1.
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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".