Morphological characterization of tomato (Solanum lycopersicum L.) genotypes
Bibliographic record
Abstract
Most of the tomato varieties in Bangladesh are of inbred type indicating need to characterize and assess morphological variability as the resources of selection of genotypes with desired traits toward variety development. Twenty-two promising tomato inbred lines were characterized for twenty-seven morphological traits using developmental, vegetative, and fruit traits at Bangladesh Agricultural Research Institute (BARI) Bangladesh from October 2009 to March 2010. A wide range of variation was observed among 21 qualitative and 6 quantitative physico-morphological characters in the study, while 20 traits showed substantial variation among the genotypes. Every genotype showed one or more distinct characters which could be used to identify the same. The morphological data for hypocotyl color, hypocotyl pubescence, leaf type, green shoulder trips in the fruit and fruit cross-sectional shape showed valuable diagnostic characters, which can be used to differentiate the genotypes as they were predominant in the study. However, it is difficult to distinguish all the genotypes based on a single morphological trait, but can enhance tomato diversity and quality and production.
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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 | 0.001 |
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".