Simultaneous determination of Total Fatty Matter, Iodine Value, and C8–C14 in soap noodles by Vis-NIRS

Importance of the Topic

Near-infrared spectroscopy (NIRS) provides a rapid, non-destructive approach to monitor critical quality parameters of soap noodles. Traditional chemical titrations and chromatographic analyses are time-consuming and labor-intensive. Implementing Vis-NIR analysis streamlines quality control, ensuring consistent product performance and consumer satisfaction.

Objectives and Study Overview

The study aimed to develop and validate quantitative NIR models for simultaneously determining Total Fatty Matter (TFM), Iodine Value (IV), and C8–C14 fatty acid content in soap noodles. By using a representative set of industrial samples, the work evaluates the potential of Vis-NIR spectroscopy for routine high-throughput quality assessment.

Methodology and Instrumentation

NIR spectra of 46 soap noodle samples were collected in reflectance mode over 400–2500 nm using a Metrohm XDS SmartProbe Analyzer. The samples were measured directly through sealed bags without any preparation. Vision Air 2.0 software managed data acquisition and chemometric modeling. Spectral pre-treatment included second derivative transformation, followed by Partial Least Squares regression applied to selected spectral regions to build calibration models.

Main Results and Discussion

• Total Fatty Matter: Concentration range 78.5–80 %. The five-factor PLS model achieved a standard error of calibration (SEC) of 0.10 % and cross-validation error (SECV) of 0.13 %.
• Iodine Value: Range 36–40. The six-factor model yielded an SEC of 0.39 and SECV of 0.45.
• C8–C14 Content: Range 1–17 %. A five-factor PLS model gave an SEC of 0.17 % and SECV of 0.21 %.

Strong correlations between NIR predictions and reference methods confirm the reliability of the models. The rapid measurement (<1 minute) without reagents highlights the efficiency gains over conventional techniques.

Benefits and Practical Applications

Implementing Vis-NIR spectroscopy for soap noodle analysis offers:

• Immediate, simultaneous determination of multiple quality parameters.
• Elimination of sample preparation and chemical reagents.
• High throughput with minimal operator training using intuitive software.
• Reduced operational costs and faster feedback for process control.

Future Trends and Potential Applications

Advancements in NIR instrumentation and chemometric algorithms will enable inline process monitoring and real-time quality assurance. Expanding the method to additional targets—such as moisture, acid value, and active detergents—can further enhance production control. Integration with machine learning may improve robustness and predictive performance.

Conclusion

The developed Vis-NIR models demonstrate a reliable, fast, and cost-effective approach for quality control of soap noodles. By replacing traditional analyses with a single spectral measurement, manufacturers can achieve significant efficiency improvements and maintain product consistency.

Reference

• Metrohm NIR Application Note NIR–51, Version 1, November 6 2017.