Pollination deficit in open-field tomato crops (<i>Solanum lycopersicum</i> L., Solanaceae) in Rio de Janeiro state, Southeast Brazil
Bibliographic record
Abstract
More than 70% of world’s crops benefit from biotic pollination, and bees are their main pollinators. Despite the fact that some of these insects have been broadly studied, understanding the interactions between plant crops and their pollinators with a local scale approach is necessary when aiming to apply proper protective and management measures to pollinators and their respective crops. In this context, we analyzed the pollination status of open-field tomato crops (Solanum lycopersicum L.), regarding fruit-set, visitation rate and the quality of fruits. We recorded the formation of fruits through spontaneous self-pollination and open-pollination, and the occurrence of pollinators in 24 areas of open-field tomato crops. We performed experiments of apomixis, spontaneous self-pollination, manual cross pollination and supplemental cross pollination (simulating the pollinator behavior) in a greenhouse. The fruit quality was evaluated according to circumference, weight, volume and number of seeds. Higher production of fruits after open-pollination compared to spontaneous self-pollination indicates the importance of pollinators to increment productivity of S. lycopersicum in the study area. The circumference and the number of seeds from tomatoes of the greenhouse plantation did not differ between spontaneous self-pollination and the manual cross pollination. In the open-field crops the number of seeds was higher for fruits resulting from open-pollination. Our results indicate that the importance of bees is mainly related to the increase in fruit production, thus incrementing the productivity of tomato crops.production, thus incrementing the productivity of tomato crops.
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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".