Near-Infrared Spectroscopy: Quantitative analysis according to ASTM E1655

Importance of the topic

Near-Infrared Spectroscopy (NIRS) is established as a fast, non-destructive analytical technique for both qualitative and quantitative analysis in research and industry. Its ability to verify material identity and measure multiple quality parameters in real time makes it vital for raw material inspection, process control, and final product certification.

Objectives and overview of the study

This white paper presents a structured workflow for developing quantitative NIR methods in compliance with ASTM E1655. It outlines essential steps from sample selection through validation to ensure robust, accurate multivariate calibrations.

Methodology and instrumentation

The development process comprises:

• Calibration set selection based on analyte range, sample variation and influence factors (geographical origin, particle size, moisture, temperature, process conditions).
• Spectral data acquisition in transmission mode for liquids and diffuse reflectance for solids, using scanning-type NIR instruments with stable optical setups.
• Spectral preprocessing (baseline correction, smoothing, derivatives) and wavelength region selection to enhance signal related to target analytes.
• Multivariate model building using PLS1 regression, determination of optimal latent variables by minimizing cross-validation error without overfitting, and rigorous outlier detection via leverage and residual statistics.
• Validation with an independent sample set spanning ≥95% of calibration range, evaluation of prediction error (SEP), bias testing, and precision assessment through repeat measurements.

Instrument performance monitoring follows established practices (ASTM E275, USP <1119>, Ph. Eur.) and QC samples are measured routinely to detect instrument drift or model degradation.

Main results and discussion

The ASTM E1655 workflow ensures development of NIR methods with predictable analytical figures of merit. Key findings include:

• Minimum calibration sample numbers depend on model complexity: ≥24 samples for ≤3 factors or ≥6×(factors+1) for more complex methods.
• PLS1 regression optimizes prediction for single analytes; combining individual PLS1 models enables simultaneous multicomponent analysis.
• Balanced calibration and validation designs minimize bias and ensure reproducibility across routine applications.

Benefits and practical applications

NIRS methods developed under this practice deliver:

• Rapid, solvent-free assays suitable for at-line, on-line or in-line integration.
• Multi-parameter quantification in polymers, fuels, food matrices and pharmaceuticals.
• Improved process control, reduced analysis time, and lower operational costs compared to traditional wet chemistry.

Future trends and opportunities

Advancements likely to shape NIRS include:

• Integration with automated sampling and Industry 4.0 platforms for real-time process monitoring.
• Enhanced chemometric strategies leveraging machine learning and AI for adaptive calibration update and outlier management.
• Expansion into novel applications such as biomedical diagnostics, on-site environmental analysis, and remote sensing.

Conclusion

Following the ASTM E1655 standard provides a clear, systematic route to develop robust NIR quantitation methods. By adhering to defined calibration, modelling and validation criteria, analysts can achieve reliable performance and seamless implementation in diverse industrial settings.

Reference

• Encyclopedia of Analytical Chemistry. John Wiley & Sons, 2014.
• Burns DA, Ciurczak EW. Handbook of Near-Infrared Analysis. CRC Press, 2007.
• ASTM E1655-05(2012). Standard Practices for Infrared Multivariate Quantitative Analysis. ASTM International, West Conshohocken, PA, 2012.
• Wilhelm R. Know your type of standards. ASTM, 2000.
• ASTM D6342-12(2017)e1. Standard Practice for Polyurethane Raw Materials: Determining Hydroxyl Number of Polyols by Near Infrared Spectroscopy. ASTM International, West Conshohocken, PA, 2017.
• ASTM D2699-16e1. Standard Test Method for Research Octane Number of Spark-Ignition Engine Fuel. ASTM International, West Conshohocken, PA, 2016.
• ASTM E275-08(2013). Standard Practice for Describing and Measuring Performance of Ultraviolet and Visible Spectrophotometers. ASTM International, West Conshohocken, PA, 2013.
• United States Pharmacopeia 39, 2016.
• European Pharmacopoeia 9th Edition, 2016.
• ASTM D6122-15. Standard Practice for Validation of the Performance of Multivariate Online, At-Line, and Laboratory Infrared Spectrophotometer Based Analyzer Systems. ASTM International, West Conshohocken, PA, 2015.