tags:
- raman-spectroscopy
- biotechnology
- benchtop-spectroscopy
- pls-regression
- tabular-regression
license: cc-by-4.0
language: en
pretty_name: Raman Spectra of Bioprocess Analytes Mettler Toledo
task_categories:
- tabular-regression
configs:
- config_name: default
data_files:
- split: train
path: train.parquet
- split: validation
path: val.parquet
- split: test
path: test.parquet
size_categories:
- n<1K
Dataset Overview
This dataset contains Raman spectra of mixtures of glucose, sodium acetate, and magnesium sulfate. It is part of a series of 8 datasets that use eight different spectrometers that measure nearly the same samples. Some datasets have a bit more samples than others. Each spectrum is paired with ground truth concentration labels verified by enzymatic assays, reflecting the concentration ranges typically found in E. coli fermentation processes.
Target Parameters and Concentration Ranges
The dataset contains measured Raman spectra of samples with different parameters from the following substances:
- Glucose
- Acetate
- Magnesium Sulfate
Reference values for the samples were measured using an HT analyzer (Cedex BioHT, Roche Diagnostics GmbH, Mannheim, Germany).
Data Acquisition
Raman spectra were recorded using the follwing settings:
- Instrument: Mettler Toledo React Raman™ 802L
- Laser Wavelength: 785 nm
- Exposure Time: 6 s
- Laser Power: 400 mW
- Scans per Sample: 5
- Number of Samples: 55
- Container Material: Plastic
Citation
Users should cite the original publication when using this dataset (Lange et. al. https://doi.org/10.1016/j.saa.2025.125861)
or BibTex:
@article{
LANGE2025125861,
title = {Comparing machine learning methods on Raman spectra from eight different spectrometers},
journal = {Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy},
volume = {334},
pages = {125861},
year = {2025},
issn = {1386-1425},
doi = {https://doi.org/10.1016/j.saa.2025.125861},
url = {https://www.sciencedirect.com/science/article/pii/S1386142525001672},
author = {Christoph Lange and Maxim Borisyak and Martin Kögler and Stefan Born and Andreas Ziehe and Peter Neubauer and M. Nicolas Cruz Bournazou},
keywords = {Raman spectroscopy, Machine learning, Partial least squares, Convolutional neural network},
}