Analytical data transfer between a Fourier transform and a dispersive NIR instrument

Importance of the Topic

The transfer of calibration data from a Fourier transform near-infrared (FT-NIR) spectrometer to a dispersive NIR instrument addresses a key bottleneck in analytical laboratories and industrial quality control. By avoiding complete remeasurement and redevelopment of chemometric models, laboratories can upgrade or switch instruments with minimal downtime and continued compliance with standardized test protocols.

Objectives and Study Overview

This application note illustrates a practical workflow for migrating calibration models developed on an FT-NIR analyzer to a Metrohm NIRS XDS RapidLiquid dispersive NIR system. Lubricating oil quality parameters including acid number, moisture content, and kinematic viscosity at 40 °C serve as the performance benchmarks for demonstrating method transfer feasibility.

Methodology

The data transfer proceeds in four main steps:

• Conversion of spectral data from wavenumber scale (cm⁻¹) to wavelength (nm) and from transmittance to absorbance.
• Interpolation of the converted spectra to match the dispersive instrument’s spectral resolution and wavelength grid.
• Development of a transfer function using piecewise direct standardization (PDS) based on a transfer set of 30 representative samples covering the full calibration range. The spectral window used spans 1120–2100 nm to avoid saturation and low-sensitivity regions.
• Import of the transferred spectra into Vision Air Complete software, calibration model development, and final slope/bias correction using an independent validation set.

Used Instrumentation

• Source FT-NIR analyzer with spectral range 800–2500 nm, 16 cm⁻¹ resolution, 32 scans per spectrum
• Metrohm NIRS XDS RapidLiquid Analyzer (400–2500 nm transmission mode at 40 °C)
• 8 mm disposable glass vials for sample handling
• Vision Air 2.0 Complete software for data acquisition, management, and calibration development

Main Results and Discussion

Transferred spectra closely match measurements on the dispersive instrument, with minimal absorbance differences across the target range. Calibration performance on the validation set demonstrates strong correlations between NIR predictions and reference methods. Key figures of merit are:

• Acid number: SECV 0.80 mg KOH/g, SEP 0.84 mg KOH/g
• Moisture: SECV 0.012 %, SEP 0.018 %
• Viscosity at 40 °C: SECV 2.1 cSt, SEP 2.9 cSt

Benefits and Practical Applications

• Eliminates the need for full sample remeasurement and extensive chemometric redevelopment.
• Reduces instrument downtime to a few hours rather than days or weeks.
• Maintains regulatory compliance for ASTM-based oil quality testing (D664, D445, D6304).
• Provides a cost-effective path for instrument upgrades or supplier changes.

Future Trends and Potential Applications

• Extension of transfer workflows to other analytes and matrices, including pharmaceuticals and food products.
• Integration of advanced algorithms and machine learning techniques to further refine transfer functions.
• Development of automated software tools to streamline cross-platform calibration migration.
• Broader adoption of digital calibration libraries enabling remote method sharing across laboratories.

Conclusion

This study confirms that FT-NIR calibration models can be successfully ported to dispersive NIR systems with minimal loss of accuracy. The described protocol offers an efficient, reliable, and reproducible approach for laboratories seeking to modernize their instrumentation without restarting method development from scratch. Calibration transfer using PDS and targeted spectral windows ensures high fidelity of quantitative predictions within a matter of hours.