Chemical Heterogeneity Assessment of Authentic Edible Bird’s Nests Using Multimodal FTIR Spectroscopy: A Foundation for Future Authentication Strategies

Edible Bird's Nest (EBN) is a highly prized food product, making it a frequent target for economic adulteration. Consequently, robust quality assurance is paramount to protect consumers and ensure market integrity. A significant barrier to effective quality control, however, is an incomplete understanding of the natural chemical variability within authentic EBN. This variability, influenced by factors such as geographical origin, bird species, and post-harvest processing, can confound analytical measurements and complicate the definition of a standard reference. This study provides an existence proof in a defined cohort, characterizing microscale chemical heterogeneity in authentic <i>A. fuciphagus</i> EBN. We employed a multi-modal Fourier Transform Infrared (FTIR) spectroscopy approach, integrating transmission, macro-attenuated total reflectance (ATR), and high-resolution micro-ATR chemical imaging. A diverse set of validated, authentic EBN samples was analyzed using unsupervised Principal Component Analysis (PCA) to explore the data structure. Our results reveal significant and previously unquantified spectral heterogeneity, particularly in protein and glycoprotein-related regions. In our cohort, the chemical signatures of authentic EBN do not collapse to a single, uniform profile but span a broad, multi-dimensional continuum. This inherent variability presents a critical challenge for conventional quality control methods that rely on simplistic, single-spectrum standards, which may lead to the misclassification of genuine products. By establishing a robust chemical baseline for the authentic class, this work provides the foundational data essential for developing next-generation authentication models capable of reliably distinguishing this natural variance from deliberate adulteration.

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Publication Details

Journal
Sensors
Published
2026-02-27
DOI
https://doi.org/10.3390/s26051491
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
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article

Chemical Heterogeneity Assessment of Authentic Edible Bird’s Nests Using Multimodal FTIR Spectroscopy: A Foundation for Future Authentication Strategies

Krzysztof Banaś, Utkarsh Mali, Dung Manh Ho, Agnieszka Banaś
Sensors
Identification and Quantification in Food
article

Chemical Heterogeneity Assessment of Authentic Edible Bird’s Nests Using Multimodal FTIR Spectroscopy: A Foundation for Future Authentication Strategies

Krzysztof Banaś, Utkarsh Mali, Dung Manh Ho, Agnieszka Banaś
article en

Abstract

Edible Bird's Nest (EBN) is a highly prized food product, making it a frequent target for economic adulteration. Consequently, robust quality assurance is paramount to protect consumers and ensure market integrity. A significant barrier to effective quality control, however, is an incomplete understanding of the natural chemical variability within authentic EBN. This variability, influenced by factors such as geographical origin, bird species, and post-harvest processing, can confound analytical measurements and complicate the definition of a standard reference. This study provides an existence proof in a defined cohort, characterizing microscale chemical heterogeneity in authentic <i>A. fuciphagus</i> EBN. We employed a multi-modal Fourier Transform Infrared (FTIR) spectroscopy approach, integrating transmission, macro-attenuated total reflectance (ATR), and high-resolution micro-ATR chemical imaging. A diverse set of validated, authentic EBN samples was analyzed using unsupervised Principal Component Analysis (PCA) to explore the data structure. Our results reveal significant and previously unquantified spectral heterogeneity, particularly in protein and glycoprotein-related regions. In our cohort, the chemical signatures of authentic EBN do not collapse to a single, uniform profile but span a broad, multi-dimensional continuum. This inherent variability presents a critical challenge for conventional quality control methods that rely on simplistic, single-spectrum standards, which may lead to the misclassification of genuine products. By establishing a robust chemical baseline for the authentic class, this work provides the foundational data essential for developing next-generation authentication models capable of reliably distinguishing this natural variance from deliberate adulteration.

SensorsVol. 26(5)
National University of Singapore (SG), University of Toronto (CA), Institute for Nuclear Science and Technology (VN)
International Atomic Energy Agency
Zero hunger
Openalex Percentile: Top 40%
Identification and Quantification in Food
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