Antixenosis in Constitutive Resistance in Maize Genotypes to the Stink Bug Diceraeus melacanthus
Bibliographic record
Abstract
Corn is one of the most important agricultural crops in the world, however, it can be affected by numerous phytophagous insects that causing economic losses in production. Diceraeus melacanthus belongs to the complex of pests that attack maize. The objective of this work was to evaluate 17 maize genotypes regarding the effects of antixenosis resistance to the stink bug D. melacanthus. The experiments were carried out in a greenhouse with maize plants in stage V2 and adult stink bugs. Bioassays of attractiveness and food preference were carried out, in addition to evaluating physical and morphological factors of the plants, such as tissue hardness, number of punctures and colorimetric factors. Genotypes 30A37, IAC 8390, Defender, NS 77 and Supremo Tg were the ones that expressed the greatest antixenotic effects in tests free choice and no-choice, among these Defender and Supremo Tg due to possible morphological causes such as plant tissue hardness. Although the IAC 8390 genotype also presents great potential for resistance, it was not possible to attribute its causes, so more studies should be conducted to evaluate the possible chemical constituents that give them this characteristic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".