Analysis of plant-based commercial milk substitutes using ATR-FTIR spectroscopy

Plant-based beverages have emerged as substitutes for cow’s milk, and their consumption has been steadily increasing in recent years, largely due to health-related reasons, such as milk protein allergies or lactose intolerance. This raises the need for development of analytical approaches for these products that can capable of accurately identifying and classifying these products. This study focused on almond, rice, oat, and soy plant-based milk substitute drinks, which are the most popular among this type of beverages. Infrared spectroscopy data have been used to develop a fast, cost-effective and easy to implement in different settings chemometrics model for these beverages, which allows their classification according to their nature and compositional variability. It was found that the use of the spectral region of the characteristic Amide I and II bands of the proteins led to an optimal description of the data by the first two principal components in the developed Principal Component Analysis (PCA) model. For oat, rice, and soy beverages, distinct characteristic spectroscopic features allowed their successful clustering using the chemometric approach, while the results obtained for the studied almond beverages evidenced their significant compositional variability, resulting in a less defined clustering. These results are consistent with the known nutritional information for the different types of beverages. • Chemometric models based on IR spectra were developed to classify vegetable drinks. • The models are fast, cost-effective and simple to implement in different settings. • Amide I and II spectral ranges were found particularly suitable for classification.

Authors

Institutions

Publication Details

Journal
Journal of Food Composition and Analysis
Published
2025-05-15
DOI
https://doi.org/10.1016/j.jfca.2025.107786
Citations
4
Primary Topic
Meat and Animal Product Quality
Type
article
Field-Weighted Citation Impact
4.77
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of plant-based commercial milk substitutes using ATR-FTIR spectroscopy

Anna Luiza B. Brito, Rui Fausto, Catarina M.M. Duarte
4 citations
Journal of Food Composition and Analysis
Meat and Animal Product Quality
4.77
article

Analysis of plant-based commercial milk substitutes using ATR-FTIR spectroscopy

Anna Luiza B. Brito, Rui Fausto, Catarina M.M. Duarte
article en
4 citations

Abstract

Plant-based beverages have emerged as substitutes for cow’s milk, and their consumption has been steadily increasing in recent years, largely due to health-related reasons, such as milk protein allergies or lactose intolerance. This raises the need for development of analytical approaches for these products that can capable of accurately identifying and classifying these products. This study focused on almond, rice, oat, and soy plant-based milk substitute drinks, which are the most popular among this type of beverages. Infrared spectroscopy data have been used to develop a fast, cost-effective and easy to implement in different settings chemometrics model for these beverages, which allows their classification according to their nature and compositional variability. It was found that the use of the spectral region of the characteristic Amide I and II bands of the proteins led to an optimal description of the data by the first two principal components in the developed Principal Component Analysis (PCA) model. For oat, rice, and soy beverages, distinct characteristic spectroscopic features allowed their successful clustering using the chemometric approach, while the results obtained for the studied almond beverages evidenced their significant compositional variability, resulting in a less defined clustering. These results are consistent with the known nutritional information for the different types of beverages. • Chemometric models based on IR spectra were developed to classify vegetable drinks. • The models are fast, cost-effective and simple to implement in different settings. • Amide I and II spectral ranges were found particularly suitable for classification.

Journal of Food Composition and AnalysisVol. 145
Istanbul Kültür University (TR), University of Coimbra (PT)
Openalex Percentile: Top 5%
Meat and Animal Product Quality
4.77
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.