Response of growth, yield, and quality of pea shoots to supplemental light-emitting diode lighting during winter greenhouse production
Bibliographic record
Abstract
Low natural light levels during the winter months are a major limiting factor for greenhouse production in northern regions. To determine the effects of supplemental lighting (SL) on winter greenhouse production of pea shoots, crop growth, yield, and quality were investigated under the treatments of supplemental photosynthetic photon flux density (PPFD) of 50, 80, 110, and 140 μmol m −2 s −1 , all with a 16 h photoperiod, plus a no-SL control treatment, inside a Canadian greenhouse from December to March. Light-emitting diodes with a red to blue PPFD ratio of 4:1 and peak wavelengths at 665 and 440 nm were used for the lighting treatment. During the trial period, the average natural daily light integral (DLI) inside the greenhouse was 5.3 mol m −2 d −1 and the average daily temperature was around 13 °C. Compared with the no-SL control, SL of 50–140 μmol m −2 s −1 increased stem length and leaf number before the first harvest and promoted the cumulative yield (kg m −2 ) of pea shoots throughout the five harvest times. The total yield (kg m −2 ) of five harvests and weekly average stem extension rate were proportional to supplemental PPFD within the range of 0–140 μmol m −2 s −1 ; however, SL of 50–80 μmol m −2 s −1 , corresponding to total (natural + supplemental) DLI of 8.1–9.8 mol m −2 d −1 , resulted in the best integrated quality based on the evaluation of individual fresh mass, soluble solids content, succulence, and firmness. Therefore, a total DLI ranging between 8.1 and 9.8 mol m −2 d −1 can be suggested as a target for winter greenhouse production of pea shoots under conditions similar to this trial.
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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 | 0.001 |
| 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".