High dependency of chilli fruit set on wild pollinators in southern India
Bibliographic record
Abstract
Ongoing pollinator declines threaten the production of many entomophilous crops. Recent reports that yields of animal-pollinated crops in India are increasing less than pollinator-independent ones suggest the occurrence of pollen limitation. We experimentally evaluated if production of the common food crop chilli benefits from insect pollination and if crop production is constrained by lack of pollinators under field conditions. Experiments were conducted in eleven chilli fields distributed across a semi-arid agricultural landscape in Andhra Pradesh, India. The experimental treatments included open controls, open pollen-supplemented flowers, and bagged flowers for pollinator exclusion. The fruit set from the two open treatments (control and pollen supplementation) was about three times higher than that from the exclusion treatment, suggesting strong dependence on insect pollination. Control supplementation treatments did not differ, which suggests that there normally is sufficient pollination for chilli production in the area. Bees contributed 98% of flower visits. Flower visitor abundance correlated with higher fruit set, but only significantly so in the pollen supplemented treatment. While previous studies that are mostly conducted in greenhouse settings suggest that chilli reproduction does not depend much on animal pollination, our field study confirms that presence of animal pollinators increases fruit set. Future research should establish if this also applies to fruit quality and total yield. Our study highlights the importance of field-realistic experiments and warrants research on pollinator dependencies of other crops. The results have implications for crop production in an area where pollinator levels may be sufficiently high for crop pollination today but possibly not in the future due to environmental change.
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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".