Hazards of using multivariate curve resolution for processing first-order spectral data. A rotational ambiguity analysis
View abstract on PubMed
Summary
This summary is machine-generated.Rotational ambiguity in multivariate curve resolution-alternating least-squares (MCR-ALS) can reduce the reliability of spectral analysis. Analyzing MCR-ALS results for rotational ambiguity is crucial for accurate concentration and spectral interpretation.
Area Of Science
- Chemometrics
- Spectroscopy
- Data Analysis
Background
- Multivariate curve resolution-alternating least-squares (MCR-ALS) is increasingly used for spectral data processing.
- However, the impact of rotational ambiguity on MCR-ALS solutions remains under-investigated.
Purpose Of The Study
- To analyze the rotational ambiguity in MCR-ALS processed spectral data.
- To assess the reliability of MCR-ALS results based on spectral overlap and the presence of uncalibrated components.
Main Methods
- Processed experimental spectral data (NIR, UV-Vis, fluorescence) using MCR-ALS.
- Analyzed rotational ambiguity using channel-wise N-BANDS method.
- Compared results with randomly initialized MCR-ALS models.
Main Results
- Low spectral overlap yielded unique analyte concentration profiles.
- High spectral overlap led to significant ambiguity in concentration profiles, reducing reliability.
- Uncalibrated components exacerbated ambiguity in MCR-ALS results.
Conclusions
- Rotational ambiguity analysis is essential for MCR-ALS in multivariate calibration.
- This analysis enhances the reliability of retrieved profiles, concentration estimations, and spectral interpretations.
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