Assessment of a new gravity injection system for fertigation of greenhouse tomatoes grown in volcanic rock media
Bibliographic record
Abstract
Hahn, F., M.A. Pena, P. Coras and M. Vazquez. 2009. Assessment of a new gravity injection system for fertigation of greenhouse tomatoes grown in volcanic rock media. Canadian Biosystems Engineering/Le genie des biosystemes au Canada 51: 1.1 1.9. There has been continuing expansion of greenhouses in Mexico in recent years with a huge shortage of hand labor. A new fertigation system was developed using a gravity injection technique, and evaluated on tomatoes grown over volcanic rock substrate in a greenhouse. The fertigation system fills a dosing tube with the fertilizer solution, which is then mixed with the correct quantity of water and delivered to the plants in order to provide the proper electrical conductivity. This paper presents the results of a study on the effect of fertilizer dosage on biomass, fruit quantity, and flower production. Electrical conductivity (EC), which peaks during the fertigation cycle, was measured around the root zone before, during, and after fertigation. As the volcanic rock substrate stores nutrients, combined cycles of fertigation and washing (only water application) were applied to the crop. The heavier fruits were obtained with 16 combined cycles, 10 consisting of fertilizers and 6 consisting of only water. Four days of crop washing still produced tomatoes, but decreased the EC of solution around root zone by 25%. A high accuracy fertigation controller is not necessary with crops grown over volcanic rock as small yield differences are encountered under different fertigation doses owing to substrate nutrient absorption. Root microscopic images showed no damage after direct fertilizer application
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".