Portable Frost-protection Misting System: Trial on Tomato and Sweet Orange Crops
Bibliographic record
Abstract
During the North American crop-growing season, although daytime temperatures may remain well above freezing point, nighttime temperatures can easily drop below 0 °C for a few hours. The effects of frost are felt in small operations, such as residential gardens, or in specific areas of a larger operation. Various large-scale measures exist for crop frost protection but they are neither portable nor flexible. A fully automated portable frost-protection misting system that makes use of the latent heat of fusion of water was developed and tested on tomato ( Solanum lycopersicum ) and sweet orange ( Citrus sinensis ) at the Macdonald Campus of McGill University (Saint-Anne-de-Bellevue, QC, Canada). The water tank stores up to 20 gal of pressurized water and detachable auxiliary air tanks provide additional line pressure. The device is lightweight, portable and provides flexible, overhead water misting for two 25-ft rows of crops. It activates autonomously using a thermostat, battery pack, and solenoid valve, and the outlet pressure is regulated using a pressure regulator. It is easily installed and dismantled for expedient relocation and the dynamic system of tubing and nozzles can be modified as required. The system was tested in subzero ambient air temperature ranging from −7.1 to 0 °C. During misting, the flesh of the targeted tomato fruit remained, on average, 3.1 and 3.6 °C warmer than ambient temperatures. The use of the system is currently limited by the infrequent formation of ice on the misting nozzles and in the water lines due drastic drops in temperature.
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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) | 0.001 | 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".