With the advancements in science and technology, datasets become larger and more multivariate, which warrants the need for programming tools for fast data processing and multivariate statistical analysis. Here, the MATLAB-based Toolbox for Environmental Research "TEnvR" (pronounced "ten-ver") is introduced. This novel toolbox includes 44 open-source codes for automated data analysis from a multitude of techniques, such as ultraviolet-visible, fluorescence, and nuclear magnetic resonance spectroscopies, as well as from ultrahigh resolution mass spectrometry. Provided are codes for processing data (e.g., spectral corrections, formula assignment), visualization of figures, calculation of metrics, multivariate statistics, and automated work-up of large datasets. TEnvR allows for efficient data analysis with minimal "by-hand" manual work by the user, which allows scientists to do research more efficiently. This manuscript is supplemented with a detailed tutorial, example data, and screenshots, which collectively provide instructions on how to use all codes. TEnvR is novice-friendly and experience in programming with MATLAB is not required. TEnvR fulfills the need for a concise MATLAB-based toolbox for working with environmental data and will be updated annually to keep pace with the latest advances and needs for computational work in the environmental sciences.
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Original Publication Citation
Goranov, A. I., Sleighter, R. L., Yordanov, D. A., & Hatcher, P. G. (2023). TEnvR: MATLAB-based toolbox for environmental research. Analytical Methods, 15(4), 539-554. https://doi.org/10.1039/d3ay00750b
0000-0002-5103-0838 (Goranov), 0000-0003-1833-7050 (Sleighter)
Goranov, Aleksandar I.; Sleighter, Rachel L.; Yordanov, Dobromir A.; and Hatcher, Patrick G., "TEnvR: MATLAB-Based Toolbox for Environmental Research" (2023). Chemistry & Biochemistry Faculty Publications. 282.