# Multi-mode Microscopic Hyperspectral Imager for the Sensing of Biological Samples
## 3 Results
### Disaster-causing Microalgae Classification on Fluorescence Mode  
In this experiment, five different types of disaster-causing microalgae (synechocystis, chaetoceros, chlamomonas, chlorella and phaeocystis, supplied by South China Sea Fisheries Research Institute, CAFS) were detected and classified under the fluorescence mode. Here, the microalgae species were cultured in culture medium of no fluorescence to form microalgae solution. Phaeocystis and chlorella were cultured in F/2 medium, chaetoceros was cultured in F/2+si medium, synechocystis was cultured in BG-11 medium, and chlamomonas was cultured in Tris-Acetate-Phosphate (TAP) medium. All of the microalgae were cultured in a light incubator with a constant temperature of 18 \({}^{\circ}\)C, a light intensity of 2000 lux and a light-to-dark ratio of 12 h:12 h. Five cuvettes were used to hold the microalgae solution. A 405 nm blue-violet laser source (UVL4052006D20-AL, SHHO, Zhongshan, China) with 200 mW power was used as the excitation source. Note that scan imaging is not needed here, since the size of single microalgae (-2 um) is less than the spatial resolution limit of our system (5 um) and the extreme weak fluorescence of single microalgae is hard to detect. For each kind of microalgae, 35 fluorescence spectra were captured by adjusting the position of cuvette. Figure 5a provides a total of \(35\times 5\) fluorescence spectra for five kinds of microalgae in a wavelength range of 450-780 nm. To obviate the influence of solution concentration, each spectrum was normalized by the following equation and shown in Figure 5b.  
\[\mathrm{I_{norm}(\lambda)}=\frac{\mathrm{I_{origin}(\lambda)-I_{min}}}{ \mathrm{I_{max}-I_{min}}} \tag{3}\]  
As shown in Figure 5b, the normalized spectra of the five types of disaster-causing microalgae are slightly different from each other, owing to the different kinds and contents of chlorophyll. Those differences indicate the possibility to identify them through fluorescence signals.  
The fluorescence spectra were also detected by another commercial spectrometer (STS-VIS, Ocean Optics, Largo, FL, USA) to validate the measurement accuracy of our MMHI system. The measured and normalized results are shown in Figure 5c,d. The difference of fluorescence intensity between (a) and (c) is due to the different exposure and gain of the two systems, and the slight difference of normalized results between (b) and (d) is attributed to the different wavelength responses of the detectors in the two systems. We found that the results measured by the MMHI and commercial spectrometer have high consistency, which proves the feasibility and accuracy for microalgae classification of our system.  
The principal component analysis (PCA) is a common method for substantial reduction of redundant data features, which is widely used in the classification of biological samples [23]. The original data matrix of our experiments is 175 \(\times\) 923, in which 175 is the total number of microalgae samples (\(35\times 5\)) and 923 is the number of spectral sampling points for each microalgae. After dimensional reduction through the PCA procedure, a three-dimensional matrix containing the first three principal components (PCs) can be obtained, which contains 99.2% information. With a 95% interval confidence, the relationship between PC1 and PC2 is shown in Figure 6a by covariance error ellipses, while the relationship among PC1, PC2 and PC3 is shown in Figure 6b by covariance error ellipsoids. The classification results show that different types of microalgae samples are well-separated using this method. In addition, the fluorescence detection mode also shows great potential for marine microalgae discrimination as well as environmental monitoring.