Microalgae Model Training and Testing Datasets
Description
This dataset contains spectral data collected using a UV/NIR spectrometer for training and testing a predictive model. The data set focuses on Chlorella vulgaris and Monoraphidium cell concentrations (measures in cells per mL) based on spectral responses at different wavelengths. Each sample includes spectral intensity measurements at nine wavelength ranges, spanning the UV to Near-Infrared (NIR) spectrum: 405-425nm, 436-455nm, 470-490nm, 505-525nm, 545-565nm, 580-600nm, 620-640nm, 670-695nm, and 780-1000nm. The output variable (labeled "Cell Count") represents the Chlorella vulgaris and Monoraphidium cell concentration in the sample.
Files
Steps to reproduce
1. Start by preparing a highly concentrated sample of microalgae (either Chlorella vulgaris and Monoraphidium) in a beaker, labeled as sample A, and then perform spectral scanning on this sample. 2. Keep track of the results after conducting spectral scanning 20 times. 3. Dilute sample A with a factor of 10 to create two new samples, labeled as B, in two separate beakers. 4. Utilize the first sample B to clean the equipment, and use the second sample B for spectral scanning. 5. Record the results after performing spectral scanning 20 times on sample B. 6. Go through steps 2 through 5 for samples C, D, and E. 7. Gather samples D and E and position them on a haemocytometer. 8. Conduct cell counting by observing the haemocytometer under a light microscope. 9. Record the average cell count obtained for samples D and E. 10. Compute the number of cells in samples A, B, and C using the cell counts recorded for samples D and E.
Institutions
- Curtin University of Technology - Sarawak Campus Malaysia