Evaluation of Tomato (Solanum lycopersicum L.) Genotypes for Horticultural Characteristics on the Upland in Southern Sierra Leone
Bibliographic record
Abstract
Notwithstanding the importance of tomato in human diet, the average yield of the crop in Africa hardily exceeds 7.5 tha-1. There is continuous unavailability of high yielding cultivars that are adapted to diverse environment and suitable for different purposes. Consequently, evaluation of introduced tomato genotypes for desired horticultural characteristics to identify superior genotypes for additional improvement in yield and yield related traits is indispensible. Hence eight tomato (Solanum lycopersicum L.) genotypes including parental were field planted in a randomized complete block design with three replications at the Department of Horticulture Nursery Unit, School of Natural resources Management, Njala University, Njala Campus, Moyamba District, Southern Sierra Leone to evaluate them for good horticultural traits. Data collected include plant height at 50% and 100% flowering, stem girth at 50% and 100% flowering, days to first, 50% and 100% flowering, days to maturity, number of fruits set per plant, number of fruits harvested per plant, average fruit weights, fruit length, fruit diameter, fruit flesh thickness, locule number, marketable and nonmarketable fruits per plant. Results from the study indicated that all genotypes studied are adaptable to the Sierra Leone climatic conditions. P1 (097) recorded the highest number of fruits set per plant, number of fruits harvested per plant and tallest and largest plant height and stem girth at 100% flowering. BC2F2 had the highest locule number while R3P9 had the heaviest fruit weight. P2 (213) had the thickest fruit flesh thickness and longest duration to fruit maturity respectively while P1 (097), BC1F2 and R3P9 had the same number of shortest days to maturity. Regarding fruit length and diameter, R3P8 and R6P6 had the longest and widest. With respects to marketable and nonmarketable fruit per plant, P1 (097) recorded the highest correspondingly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".