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  3. Aptamer-based Sensing Array Coupled With Multiple Pattern Recognition Algorithms For Accurate Β-lactoglobulin Discrimination In Complex Matrices.
  1. Home
  3. Aptamer-based Sensing Array Coupled With Multiple Pattern Recognition Algorithms For Accurate Β-lactoglobulin Discrimination In Complex Matrices.

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Aptamer-based sensing array coupled with multiple pattern recognition algorithms for accurate β-lactoglobulin

YiChun Zhang1, Hongwei Qin2, Xibao Gao3

  • 1Department of Physical and Chemical Inspection, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, China; Institute of Quality Standard and Testing Technology for Agro-products, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.

Analytica Chimica Acta
|March 6, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

A novel aptamer-based sensing array with pattern recognition accurately detects beta-Lactoglobulin (β-LG) in complex food matrices. This method overcomes matrix effects, offering a sensitive and reliable strategy for allergen detection.

Keywords:
AptamerFood allergenMatrix effectPattern recognitionSensing arrayβ-LG

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Area of Science:

  • Analytical Chemistry
  • Biosensing
  • Food Science

Background:

  • Beta-Lactoglobulin (β-LG) is a major milk allergen causing health concerns, particularly in infants.
  • Existing detection methods struggle with complex food matrices, necessitating improved strategies.
  • Effective detection of β-LG is crucial for food safety and allergen management.

Purpose of the Study:

  • To develop a novel aptamer-based sensing array for accurate β-LG detection.
  • To overcome the challenge of matrix effects in food samples.
  • To establish a sensitive and robust method for allergen identification in diverse food matrices.

Main Methods:

  • Utilized four aptamers as recognition probes in an aptamer-based sensing array.
  • Employed gold nanoparticles (AuNPs) for colorimetric detection, observing salt-induced aggregation.
  • Applied multiple pattern recognition algorithms to analyze colorimetric responses and identify β-LG.
  • Developed a unique fingerprint pattern based on color changes for β-LG detection.

    • Main Results:

    • The aptamer-based array coupled with pattern recognition achieved over 95% classification accuracy.
    • A minimum discriminable concentration of 20 nM was established for reliable β-LG differentiation.
    • Linear Discriminant Analysis demonstrated 95.3% accuracy in blind testing of 150 samples.
    • The strategy showed robust anti-interference performance in complex food matrices.

    Conclusions:

    • The proposed aptamer-based sensing array provides a sensitive and reliable method for β-LG detection.
    • This approach effectively circumvents matrix effects, enabling accurate allergen identification in complex foods.
    • The strategy offers a promising platform for robust allergen detection, addressing limitations of conventional aptasensors.