The use of LEDs for the stomatal response, light compensation points, and storage of spinach and kale
Bibliographic record
Abstract
The spectral composition of some light-emitting diodes (LEDs) reportedly results in higher crop yield, prevents wilting, and reduces thermal damage to plants. The use of LEDs for postharvest storage and shelf-life extension has been limited, but the potential of this technology will allow for greater applications in horticulture and the food industry. In this experiment, ‘Winterbor’ kale (Brassica oleracea) and ‘Melody’ spinach (Spinacia oleracea) plants were measured for the light compensation point and stomatal response under 14 different wavelengths of light ranging from 405 to 661 nm. Data collected from these measurements were used to select two different wavelengths of LEDs and determine the proper irradiance levels for an LED irradiance storage test on spinach and kale. Treatments comprising blue, red, and amber lights were effective at increasing the stomatal opening, while the green light resulted in reduced stomatal opening. For spinach, the light response curve showed that light compensation points at 500 nm and 560 nm were 65.3 and 64.7 μmol m−2 s−1, respectively. For kale, the light compensation points at 500 nm and 560 nm were 50.8 and 44.1 μmol m−2 s−1, respectively. For the storage test experiment at room temperature, kale and spinach were stored under four different treatments: dark treatment (control), standard white fluorescent light, 500 nm, and 560 nm LED wavelengths. For spinach, the moisture content was 70.1% at 560 nm and 53.7% for dark, moisture losses of 41.5% under the 560-nm treatment and 52.0% for the dark treatment. The fresh basis moisture content was 74.6% at 560 nm and 59.3% in the dark. Moisture loss under the 560 nm treatment was 39.6% while the dark treatment had a 54.0% moisture loss. A visual assessment scale was monitored, 560 nm resulted in the top visual quality for kale compared to the other treatments with the lowest visual quality under the dark treatment at day 4. For spinach, the visual quality for 560 nm treatment was statistically the standard white fluorescent light and 500 nm, with poor-quality product occurring by day 4 and the lowest-quality product occurring at day 5. The LED treatments improved the shelf life of spinach and kale, likely as a result of stomatal aperture closure, photosynthetic rate near the light compensation point and stability of the atmospheric moisture content. This study provides valuable information on the extension of the shelf life of leafy greens during storage. Reducing fresh produce waste in grocery stores will increase revenue, thereby benefiting the Canadian economy while providing social and environmental benefits that entail increased food security and reduced food waste.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".