Effect of Different Combinations of Red and Blue LED Light on Growth Characteristics and Pigment Content of In Vitro Tomato Plantlets
Bibliographic record
Abstract
The aim of this study was to evaluate the growth characteristics and pigment content of tomato plantlets grown under various ratios of red (R) (661 nm) and blue (B) (449 nm) LED light. In this study, three different ratios of R and B (RB) light such as 5:01, 10:01, and 19:01 along with R (100%) were used. The photosynthetic photon flux density (PPFD), and photoperiod of the growth chamber was 120 ± 5 μmol m−2s−1 and 16/8 h (day/night), respectively. Tomato plantlets were cultured for six weeks in the growth chamber. It was shown that tomato plantlets had higher photosynthesis rate, higher pigments content, higher growth characteristics (e.g., number of leaves, leaf area, shoot number, root number, root length, dry, and fresh mass), and greater surviving rate under the R:B = 10:01 ratio among the treatments. The plantlets showed at least a threefold decrease in photosynthesis rate, as well as a significant abnormal stem elongation when grown under 100% R light. It is concluded that the RB ratio of 10:01 showed excellent performance in all growth parameters. This result has shown that the optimum lighting environment improves tomato plantlet cultures in vitro.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".