Measurement and Selection of Parasitoid Quality for Mass-Reared Trichogramma minutum Riley Used in Inundative Release
Bibliographic record
Abstract
Parasitoid quality, subject to both genetic and environmental influences, is critical to the success of any biological control program, however, its measurement and improvement is poorly understood. In this study, a classic genetic approach is taken to develop two indices, namely a character index and a fitness index, for the measurement and selection of high quality parasitoids used in inundative release. Six life-history traits and corresponding fitness components in 33 inbred strains of Trichogramma minutum were used to generate both genotypic and phenotypic variance-covariance matrices that then allowed for the construction of the indices. Most traits and their fitness components were positively correlated, both phenotypically and genotypically, with lifetime fecundity and the number of female offspring appearing to have an important influence. Selection of the top three strains showed that parasitoid quality could be improved by 36% using the character index and possibly up to 150% using the fitness index. The two indices were linearly correlated suggesting that either could be used to measure quality. The character index is recommended because it requires information on only three life-history traits (fecundity, number of female offspring, and number of male offspring) and has highly correlated responses of fitness components. Our work demonstrates that the best quality T. minutum will be obtained by using the character index to select for inbred strains which have high fecundity and number of female offspring.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".