Authenticating Raw from Reconstituted Milk Using Fourier Transform Infrared Spectroscopy and Chemometrics

Du, Liuying; Lu, Weiying; Gao, Boyan; Wang, Jing; Yu, Liangli

doi:10.1155/2019/5487890

Cited by 22 publications

(13 citation statements)

References 21 publications

(26 reference statements)

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“…Model overfitting is avoided because it affects the classification performance and gives bias results. An internal and external validation test using 11 latent variables confirmed the validity of the PLS-DA model with the accuracy of 98% [ 12 ].…”

Section: Chemometricsmentioning

confidence: 99%

“…The application of chemometrics or multivariate data analysis (MDA) is emerging in the authentication of milk using FTIR spectroscopy (Irnawati et al, 2021). Several studies have reported using chemometrics for classification of milk such as the authentication of raw milk from reconstituted milk with FTIR spectroscopy combined partial least square-discriminant analysis (PLS-DA) [ 12 ], the detection of formalin in cow milk using ATR-FTIR spectroscopy combined with PCA and its quantification using PLS [ 13 ], and the detection and quantification of urea in milk using FTIR spectroscopy combined with multivariate analysis (PCA and PLS) [ 14 ]. Capuano et al [ 15 ] have reported using FTIR spectra and PLS-DA for classification of milk from cow that were fed with or without fresh grass.…”

Section: Chemometricsmentioning

confidence: 99%

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The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

Windarsih

Rohman

Irnawati

et al. 2021

International Journal of Food Science

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Milk products obtained from cow, goat, buffalo, sheep, and camel as well as fermented forms such as cheese, yogurt, kefir, and butter are in a category of the most nutritious foods due to their high contents of high protein contributing to total daily energy intake. For certain reasons, high price milk products may be adulterated with low-quality ones or with foreign substances such as melamine and formalin which are added into them; therefore, a comprehensive review on analytical methods capable of detecting milk adulteration is needed. The objective of this narrative review is to highlight the use of vibrational spectroscopies (near infrared, mid infrared, and Raman) combined with multivariate analysis for authentication of milk products. Articles, conference reports, and abstracts from several databases including Scopus, PubMed, Web of Science, and Google Scholar were used in this review. By selecting the correct conditions (spectral treatment, normal versus derivative spectra at wavenumbers region, and chemometrics techniques), vibrational spectroscopy is a rapid and powerful analytical technique for detection of milk adulteration. This review can give comprehensive information for selecting vibrational spectroscopic methods combined with chemometrics techniques for screening the adulteration practice of milk products.

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Section: Chemometricsmentioning

confidence: 99%

Section: Chemometricsmentioning

confidence: 99%

The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

Windarsih

Rohman

Irnawati

et al. 2021

International Journal of Food Science

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“…PLS-DA model is used to optimize separation between different groups of samples and is completed by linking two matrices: X (the spectral data) and dependent variable (groups, class membership etc.). PLS constructs a linear regression model by projecting the predictor variables and response variables to a new set of latent variables (LVs), called factors, with maximum covariance [23] PLS-DA was performed in the fingerprint region 1800-750 cm −1 . PLS-DA models were extracted at a confidence level of 95%…”

Section: Partial Least Squares-discriminant Analysis (Pls-da)mentioning

confidence: 99%

Classification of Honey Powder Composition by FTIR Spectroscopy Coupled with Chemometric Analysis

et al. 2022

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Fourier transform infrared spectroscopy (FTIR) in connection with chemometric analysis were used as a fast and direct approach to classify spray dried honey powder compositions in terms of honey content, the type of diluent (water or skim milk), and carrier (maltodextrin or skim milk powder) used for the preparation of feed solutions before spray drying. Eleven variants of honey powders containing different amounts of honey, the type of carrier, and the diluent were investigated and compared to pure honey and carrier materials. Chemometric discrimination of samples was achieved by principal component analysis (PCA), hierarchical clustering analysis (HCA), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA) modelling procedures performed on the FTIR preprocessed spectral data for the fingerprint region (1800–750 cm−1) and the extended region (3600–750 cm−1). As a result, it was noticed that the type of carrier is a significant factor during the classification of different samples of powdered multifloral honey. PCA divided the samples based on the type of carrier, and additionally among maltodextrin-honey powders it was possible to distinguish the type of diluent. The result obtained by PCA-LDA and PLS-DA scores yielded a clear separation between four classes of samples and showed a very good discrimination between the different honey powder with a 100.0% correct overall classification rate of the samples.

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“…After olive oil, milk is the second food item that is at risk of adulteration [ 67 , 68 , 69 ]. Adulteration of milk can have economic purposes as in the case of the addition of vegetable proteins, milk of different species, addition of whey and water, not representing any serious risk to health.…”

Section: Application Of Ft-mir To Food Analysismentioning

confidence: 99%

Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine

Mendes

Duarte

2021

Foods

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Nowadays, food adulteration and authentication are topics of utmost importance for consumers, food producers, business operators and regulatory agencies. Therefore, there is an increasing search for rapid, robust and accurate analytical techniques to determine the authenticity and to detect adulteration and misrepresentation. Mid-infrared spectroscopy (MIR), often associated with chemometric techniques, offers a fast and accurate method to detect and predict food adulteration based on the fingerprint characteristics of the food matrix. In the first part of this review the basic concepts of infrared spectroscopy, sampling techniques, as well as an overview of chemometric tools are summarized. In the second part, recent applications of MIR spectroscopy to the analysis of foods such as coffee, dairy products, honey, olive oil and wine are discussed, covering a timespan from 2010 to mid-2020. The literature gathered in this article clearly reveals that the MIR spectroscopy associated with attenuated total reflection acquisition mode and different chemometric tools have been broadly applied to address quality, authenticity and adulteration issues. This technique has the advantages of being simple, fast and easy to use, non-destructive, environmentally friendly and, in the future, it can be applied in routine analyses and official food control.

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Authenticating Raw from Reconstituted Milk Using Fourier Transform Infrared Spectroscopy and Chemometrics

Cited by 22 publications

References 21 publications

The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

Classification of Honey Powder Composition by FTIR Spectroscopy Coupled with Chemometric Analysis

Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine

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