Biodiversity of Natural Enemies of Pseudococcidae in the Semiarid Region of Brazil
Bibliographic record
Abstract
Pseudococcidae species, also known as mealybugs, comprises a complex of pests in various cultivated and non-cultivated plant species, among which fruit plants are most affected by both direct and indirect damage. The incidence of these pest species has been constant in productive environments, causing significant losses due to sap suction, virus transmission, and damage to fruit quality. Thus, this study aimed to know and investigate the population dynamics of natural enemies of Pseudococcidae in different fruit plants cultivated in the semiarid region of Brazil. For this, mealybugs associated with roots, stems, leaves, and fruits of vine, pear, apple, persimmon, guava, and acerola trees were collected biweekly in 14 properties in the São Francisco Valley region, from July 2016 to June 2017. These mealybugs were properly separated for the removal of their predators and the emergence of parasitoids associated with them (Pseudococcidae). Coccophagus sp., Aenasius sp., Anagyrus kamali, Anagyrus sp. 1, Anagyrus sp. 2, Anagyrus sp. 3, Anagyrus sp. 4, Coccidoxenoides perminutus, Gyranusoidea indica, Leptomastix dactylopii, Prochiloneurus sp., Aprostocetus sp., and Signiphora sp. were identified as parasitoids and Diadiplosis multifila, Cryptolaemus montrouzieri, Tenuisvalvae notata, Cycloneda sanguinea, and Hippodamia convergens were identified as predators, in addition to unidentified species of Coccinellidae and Chrysopidae.
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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 | 0.001 | 0.001 |
| 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".