Effect of LEDs Light Spectrum on Success of Fragmentation and Growth of Leather Coral <i>Sarcophyton</i> spp.
Bibliographic record
Abstract
The increasing demand for soft corals is reflected on the high attention of the scientific community during the last decades, with several studies focus on production techniques and optimization of coral husbandry. However, coral culture success is influenced by the interaction of different factors, such as water movement, temperature, nutrients, heterotrophic feeding and light conditions. Light plays a key role in the growth, reproduction and physiology of corals that host phototrophic symbionts and it has been found that the photoresponse of corals is species-specific. Several studies have already focused on the effects of irradiance on coral and its algal symbionts. Although, only a few works have investigated the role of the spectral quality of light on coral photobiology, physiology and growth. In the present study, we hypothesize that light spectrum can influence the growth performance of Leather Coral Sarcophyton spp.when exposed at identical intensities of photosynthetically active radiation (PAR). To test our hypothesis we evaluated the effect of contrasting light spectra with an identical PAR of 70 ± 10 μmol quantam −2 .s −1 emitted by T8 fluorescent lamps (used as a control treatment) and three different colours of Light Emitting Diode (LED), white, blue and red. It was evaluated survival and growth rates of Sarcophyton spp., an important soft coral in the marine aquarium trade and for the bioprospecting of marine natural compounds. Replicated coral fragments were obtained from two mother colonies and were exposed to the four types of light spectrum for a period of 30 days. At the end of the experiment period, the results showed 100% of survival in coral fragments, and specific growth rate (SGR) of 0,055 ± 0,09%/day in control group and 0,091 ± 0,019 %/day, 0,210 ± 0,031%/day and 0,380 ± 0,245%/day in, white, blue and red light, respectively. Moreover, in all treatments at end of experiment the zooxanthellae density was ±, ± and ± for white, blue and red light spectrum, respectively showing that all light promotes conditions for zooxanthellae growth. The results also showed a positive role of use a specific light spectrum in coral growth, namely blue and red spectrum. The use of light with specific light spectrum that increasing the growth and health of corals will minimizing the production costs, increasing the feasibility of ex situ production of ornamental corals and this study identify the best LED`s light spectrum for the growth of the leather coral Sarcophyton spp.
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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 | 0.000 | 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) | 0.000 | 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".