Tomato (Solanum lycopersicum) specialized pollination is isolated from neighboring plants and pollinators
Bibliographic record
Abstract
Tomato is one of the crops that require buzz pollination, for which a pollinator vibrates the tubular anthers for pollen to be released. This process is efficiently carried out by wild bees, whose distribution varies according to the geographical location and the particular characteristics of the different agroecosystems. The pollination network associated with tomato fields located in an agricultural area of Cuba was determined by field observations. In addition, it was studied whether pollination influences tomato yield, through exclusion experiments and comparing the characteristics of the fruits obtained in the presence or absence of pollinators. The pollination network consisted of 241 interactions between 12 plants, including tomato, adjacent crops such as papaya and pumpkin, and ruderal species, and 11 floral visitors, fundamentally bees, with 5 species involved. Tomato flowers were almost exclusively visited by the bee species Exomalopsis pulchella, capable of buzz pollination. Species of the genus Exomalopsis are frequent pollinators of tomato in the Neotropic. This denotes a temporary specialization in the use of tomato´s floral resources by Exomalopsis pulchella. Apis mellifera was not detected visiting tomato flowers, despite being present in the pollination network associated with the studied agroecosystem. Pollination significantly increased the dimensions of tomato fruits. Exomalopsis pulchella also visited the ruderal plants Asteraceae sp., Commelinaceae sp. and Milleria quinqueflora. This should be taken into account in the management of the ruderal plant communities that surround the tomato fields, in order to promote and guarantee the presence of the main pollinator of this crop.
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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) | 0.002 | 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".