An LED-Based Fluorescent Sensing System for on-Site Microalgal Detection
Bibliographic record
Abstract
In this work, we present a fluorescent sensing system capable of simultaneously detecting two species during microalgal co-culture, in which microalgae ( C. vulgaris ) and cyanobacteria ( Leptolyngbya sp. ) are the target species for detection. The sensing system has two different excitation light sources for stimulating chlorophyll a in microalgae and phycocyanin pigment in cyanobacteria, respectively, and a photodetector to measure corresponding fluorescent signals. This work is a significant improvement over our previous report on a fluorescent sensing system for single species [1]. Microalgae are one of the promising alternative energy sources [2]. Recent reports show that a co-culture system enhances biofuel production [3] and it is desired to monitor the population of each species. The co-inoculation of microalgae and cyanobacteria promotes the growth rate and lifespan of microalgae [4,5]. It is highly desired to simultaneously monitor the populations of microalgae and cyanobacteria in order to obtain highly efficient biofuel production. A common method is bench-top flow cytometry, which is time consuming, expensive, and difficult to deploy for on-site detection. The proposed portable fluorescent sensing system can be a viable option for on-site monitoring of co-culture solution containing microalgae and cyanobacteria. For the fluorescent sensing system, blue LEDs (448 nm peak wavelength) were selected for stimulating microalgae and amber LEDs (590 nm) for cyanobacteria. A highly sensitive silicon photomuliplier, MicroFC (SensL Inc., Cork, Ireland), was implemented to detect a low fluorescent signal from phycocyanin in cyanobacteria. Chlorophyll a and phycocyanin emit fluorescent light with the peak wavelength around 680 nm and 645 nm, respectively. Two long-pass filters, a dichroic filter with 647 nm cut-off (PIXELTEQ, Largo, FL, USA) and a color filter with 645 nm cut-off (Edmund Optics, Barrington, NJ, USA), are placed in front of the silicon photomultiplier to block the excitation light as illustrated in Figure 1. Measured results show that the photocurrent increases with the population of microalgae under the blue excitation light while its change is not significant to the amber light. Likewise, the photocurrent increases with the concentration of phycocyanin pigments under the amber excitation light while its response to the blue light is minimal. In summary, we have developed and demonstrated a portable fluorescent sensing system that is capable of differentiating microalgae and cyanobacteria. With further optimization, the developed system can be deployed in a biofuel production system for continuous monitoring of co-culture solution. Future work will also include integrated electronic circuitry for a fully standalone fluorescent detection system. References: [1] Y.-H. Shin, J. Z. Barnett, E. Song, M. T. Gutierrez-Wing, K. A. Rusch and J.-W. Choi, Microelectronic Engineering. 144 (2015) 6-11. [2] Y. Chisti, Biotechnology Advances. 25 (2007) 294-306. [3] A. Silaban, R. Bai, M. T. Gutierrez-Wing, I. I. Negulescu, and K. A. Rusch. Engineering in Life Sciences. 14 (2014) 47-56. [4] L. E. Gonzalez and Y. Bashan, Applied And Environmental Microbiology. 66 (2000) 1527-1531. [5] L. E. de-Bashan, Y. Bashan, M. Moreno, V. K. Lebsky, and J. J. Bustillos, Canadian Journal of Microbiology. 48 (2002) 514-521. Figure 1
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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".