Ecological effects of interplanted sweet alyssum and alfalfa in an organic day-neutral strawberry production system
Bibliographic record
Abstract
Production of day-neutral strawberries ( Fragaria x ananassa ) is increasing in the Upper Midwest region of the USA, resulting in an extended strawberry harvest season compared to traditional June-bearing production systems. However, the longer harvest season comes with additional insect pest pressure and the need for novel integrated pest management strategies. Spotted-wing drosophila ( Drosophila suzukii ; SWD) and tarnished plant bug ( Lygus lineolaris ; TPB) can decrease strawberry yield and fruit quality. Insecticides are the dominant management strategy for both insect pests; however, fewer effective insecticides are available in organic production systems. Interplanting is an integrated pest management strategy which can provide conservation biological control and may repel or attract species of interest through volatile organic compound (VOCs) emissions. We investigated the effect of interplanting alfalfa and sweet alyssum with day-neutral strawberry plants on fruit yield and quality, SWD infestation and TPB damage, arthropod abundance and diversity. Additionally, we measured the relative abundance of sweet alyssum VOCs, acetophenone and benzaldehyde, in the field because they may be aversive to SWD adults. The interplanting treatment inconsistently affected fruit production; in year one of the study, the control treatment had larger fruit than the other two treatments and, in year two, berries interplanted with sweet alyssum had more marketable yield than the other two treatments. Treatments did not affect SWD infestation or TPB damage. Acetophenone and benzaldehyde VOC production varied in the sweet alyssum plots by time of day and date. The control treatment had less arthropod abundance and diversity compared to the intercrop treatments. Intercropping may provide resources for arthropod communities but may not reduce key pest species such as SWD and TPB in day-neutral strawberries.
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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".