Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Performance optimization of spectroscopic process analyzers.

Hans F M Boelens1, Wim Th Kok, Onno E De Noord

  • 1Process Analysis and Chemometrics, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.

Analytical Chemistry
|May 1, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Analysis of microbiome high-dimensional experimental design data using generalized linear models and ANOVA simultaneous component analysis.

Frontiers in microbiomes·2026
Same author

ACMTF-R: Supervised multi-omics data integration uncovering shared and distinct outcome-associated variation.

PloS one·2026
Same author

Prioritization strategies for non-target screening in environmental samples by chromatography - High-resolution mass spectrometry: A tutorial.

Journal of chromatography. A·2025
Same author

Longitudinal Metabolomics Data Analysis Informed by Mechanistic Models.

Metabolites·2025
Same author

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations.

Metabolomics : Official journal of the Metabolomic Society·2024
Same author

A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros.

Scientific reports·2024
Same journal

Biodegradable Self-Powered Electrotherapy Patch for Integrated Smart Wound Management.

Analytical chemistry·2026
Same journal

Metabolite Fraction Libraries for Quantitative NMR Metabolomics.

Analytical chemistry·2026
Same journal

Self-Contained Lateral-Flow Microfluidic Bead-Based Assay for Rapid Quantification of Early-Stage Kidney Biomarkers.

Analytical chemistry·2026
Same journal

Overcoming the Debye Shielding Effect with Concave-Convex Structures for Sensitivity-Enhanced Thin-Film Transistors.

Analytical chemistry·2026
Same journal

Mode-Phase-Difference Photothermal Spectroscopy Assisted by a Bent Biconically Tapered Microfiber for Gas Sensing.

Analytical chemistry·2026
Same journal

Negative-Pressure-Actuated Microfluidics: A Dual-Mode Point-of-Care Sensor for Allergen-Specific IgE in Interstitial Fluid.

Analytical chemistry·2026
See all related articles

This study introduces a Net Analyte Signal (NAS) approach to enhance spectroscopic process analyzers by suppressing irrelevant spectral variations. This method improves accuracy and requires fewer measurements for effective process monitoring.

Area of Science:

  • Analytical Chemistry
  • Chemometrics
  • Process Analytical Technology (PAT)

Background:

  • Spectroscopic process analyzers require methods to mitigate spectral variations unrelated to the property of interest for improved robustness.
  • Existing methods may be sensitive to errors in reference methods or require extensive spectral data.

Purpose of the Study:

  • To present a novel approach for selecting methods to suppress non-relevant spectral variation in spectroscopic process analysis.
  • To enhance the power and robustness of spectroscopic process analyzers.

Main Methods:

  • Utilizes the Net Analyte Signal (NAS) to analyze spectral data and identify methods for suppressing irrelevant variations.
  • Employs the empirically determined signal-to-noise ratio (SNR) of the NAS as a figure of merit for method selection.

Related Experiment Videos

  • Proposes a diagnostic plot to guide users in evaluating suppression methods.

    • Main Results:

    • The Net Analyte Signal (NAS) approach effectively identifies methods to suppress unwanted spectral variation.
    • The method selection is independent of reference method errors.
    • Requires only a limited number of spectral measurements for analysis.

    Conclusions:

    • The presented NAS-based approach offers an efficient and robust strategy for selecting spectral suppression methods in process analysis.
    • This technique enhances the reliability of spectroscopic process analyzers, as demonstrated in NIR monitoring of mol-sieve separation.