Technical and Economic Evaluation of Three Types of Tomato Nutrient Solutions under Semi-Controlled Conditions
Bibliographic record
Abstract
This study was conducted to evaluate the effect of three types of nutrient solutions on the development, performance, quality and cost of chonto tomato (Solanum lycopersicum L.) under semi-controlled conditions. The assessment was conducted in the farm Tesorito, Manizales, Colombia. An experimental design was established in randomized complete blocks (RCB), with 3 treatments, 4 replicates per treatment and 10 effective plants per replicate. The variables were: height of the first cluster, production per plant, yield t ha-1 and qualities of the fruit. The economic variables were production costs, cost-benefit ratio (C/BR), rate of return (IRR) and net present value (NPV). In general, production per plant was greater than 4.7 kg plant-1 and the average yield was 92 t ha-1. The use of conventional fertilization (tt2) generated increased production of premium quality fruit with a value of 37.11 t ha-1, demonstrating that conventional soil fertilization implemented in this culture under semi-controlled conditions in the company of drip irrigation system in the root zone improve outcomes of productive variables, increasing profitability and competitiveness with a net profit of USD$ $ 25203.68 ha-1, with average selling price of USD$ 0.45 per kilogram and a unit production margin of USD$ 0.21 per kilogram, making this technology attractive and economically viable.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".