How multi-species pollination boosts strawberry yield, quality, and nutritional value
Bibliographic record
Abstract
A diverse assemblage of insect visitors can provide functional complementarity within plant pollination due to differences in characteristics such as their physical traits, visitation rate and foraging time of day or year. In a horticultural context, greater functional complementarity may play a crucial role in enhancing fruit yield and quality by improving pollination. We tested whether the identity of the crop pollinators (bumblebee Bombus terrestris and hoverfly Eupeodes corollae) independently and additively influenced commercial strawberry yield, quality, and nutritional parameters such as vitamin C and sugar concentration. Fragaria x ananassa “Malling Champion” plants received pollination treatments of either a) “control”: self-pollination where pollinators were excluded, b) “bee”: bumblebee Bombus terrestris, c) “hoverfly”: Eupeodes corollae, d) “combined”: both B. terrestris and E. corollae. Hoverflies and bumblebees exhibited distinct visitation patterns throughout the day, establishing a functional complementary relationship that enhances pollination success and crop output as well as vitamin C concentrations. Strawberries from plants receiving pollination by bumblebees, or bumblebees and hoverflies combined, had higher yields of higher marketable quality. They also had measurably higher vitamin C content than strawberries from plants pollinated by hoverflies alone, or the control (self-pollinating) plants. This study advances our understanding of niche complementarity and its impact on fruit yield and quality. By elucidating the behavioural and temporal dynamics of pollinators, we provide valuable insights for optimizing pollination strategies in agricultural contexts. Our findings highlight the significance of behavioural factors, such as handling time and number of visits, in determining fruit quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".