Fluorescence sensor array for identification of commercial milk samples according to their thermal treatments

Mungkarndee, Radeemada; Techakriengkrai, Ittipon; Tumcharern, Gamolwan; Sukwattanasinitt, Mongkol

doi:10.1016/j.foodchem.2015.10.083

Cited by 24 publications

(17 citation statements)

References 44 publications

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“…Until now, there have been few studies on other indicators to distinguish reconstituted milk and UHT milk besides furosine and lactulose. Mungkarndee et al 23 recognized pasteurized milk, sterilized milk, UHT fresh milk, and reconstituted milk using the fluorescence sensor array technique. However, no biomarkers were found that could be used to classify those four types of milk reliably.…”

Section: Discussionmentioning

confidence: 99%

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

Cui

Zhu

et al. 2019

J Sci Food Agric

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BACKGROUND The illegal undeclared addition of reconstituted milk powder to ultra‐heat treated (UHT) milk to lower production costs is an example of economically motivated adulteration. This activity not only defrauds consumers but also places honest traders at a disadvantage, which could damage the reputation of milk producers and reduce the integrity of the markets. In this research, a non‐targeted analytical strategy that combines proton (1H) nuclear magnetic resonance (NMR) spectroscopy with a chemometrics data mining tool was developed for the authentication of bovine UHT milk. RESULTS Unsupervised principal component analysis was used to distinguish UHT and tap‐water‐reconstituted powdered milk. Partial least squares‐discriminant analysis (PLS‐DA) with R2(Y) and Q2 equal to 0.859 and 0.748, respectively, was used to differentiate UHT and reconstituted milk samples. Three compounds were selected as biomarkers to distinguish UHT and reconstituted milk and identified according to the standard NMR‐spectra database. Finally, a PLS‐DA model was established, according to the characteristic spectral bands, to identify UHT milk and reconstituted milk. CONCLUSION This procedure demonstrated the feasibility of using non‐targeted NMR profiling combined with chemometric analysis to combat mislabeling and fraudulent practices in milk production. © 2019 Society of Chemical Industry

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Section: Discussionmentioning

confidence: 99%

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

Cui

Zhu

et al. 2019

J Sci Food Agric

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“…In a recent work by Mungkarndee et al [ 54 ] the fluorescence induced by fluorophore/protein interactions was evaluated for its ability to discriminate milk samples according to the heat treatment (pasteurized, sterilized, UHT, and recombined milk) and according to the different type of milk (fermented, soy, and corn milk). Fluorophore solutions (5 μ M) and pure protein solutions (BSA, α -casein, β -casein, α -LA, and β -LG) were prepared in sodium phosphate buffer (10 mM, pH 7.4).…”

Section: Nonreference Methods Based On Spectroscopic Techniquesmentioning

confidence: 99%

New Trends for the Evaluation of Heat Treatments of Milk

Ritota¹,

Costanzo²,

Mattera³

et al. 2017

Journal of Analytical Methods in Chemistry

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Milk is generally very rich in nutrients and this may lead it to be an ideal growth environment for many microorganisms, including pathogens, so effective measurements aiming to ensure total microbiological safety of milk and minimize the risk to human health are needed. Milk heat treatments are the most common practices carried out to inhibit the microbial growth; therefore it is necessary to have analytical procedures that are more and more up-to-date and capable of detecting the effectiveness of the heat treatments. Most of the reference and official methods to assess heat treatment in milk are based on the evaluation of the modifications of some milk components following the thermal process, such as the determination of enzyme activities (alkaline phosphatase and lactoperoxidase), whey proteins, Maillard reaction compounds (generally furosine), and lactulose. Besides the most common techniques (liquid and gas chromatography, capillary electrophoresis, or spectroscopy) used for the detection of single thermal indicators, new approaches, such as chemometric studies or more recent techniques, including size-exclusion chromatography with online electrospray mass spectrometry or stable isotope ratio mass spectrometry, are discussed in this review in order to evaluate heat treatment in milk.

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“…The overall satisfactory results clearly demonstrated the potential use of the E-tongue as a practical analytical tool for correctly classifying dairy product according to the type of milk used in the production, regardless the intrinsic samples' variability related to the brand and the presence or absence of flavor additives. This qualitative potential can be tentatively attributed to the representative potentiometric fingerprints gathered by the E-tongue device, which allowed identifying the differences of organoleptic sensations and physicochemical contents of the milks studied induced by the different technological processes used in their production (Mungkarndee et al [2]). Indeed, the capability of similar E-tongue systems, also containing lipid polymeric membranes, for differentiating pleasant and unpleasant sensory attributes of food matrices have been reported [16,21,22,[24][25][26].…”

Section: Linear Discriminant Analysismentioning

confidence: 98%

“…To increase milk shelf-stability, its microbial population must be reduced, which is usually achieved by thermal processing of milk. However, these technological processes highly affect the sensory attributes of milk as well as physicochemical changes that may condition protein functionality and the bioavailability of the nutrients [2]. Usually, food analysis is carried out using standard analytical techniques such as chromatography and spectroscopy [1,3].…”

Section: Introductionmentioning

confidence: 99%

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Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools

et al. 2018

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This study shows the potential application of a potentiometric electronic tongue coupled with a lab-made DataLogger device for the classification of dairy products according to the type of milk used in their production, i.e., natural, fermented and UHT milk. The electronic tongue device merged a commercial pH electrode and 15 lipid/polymeric membranes, which were obtained by a drop-by-drop technique. The potentiometric signal profiles gathered from the 16 sensors, during the analysis of the 11 dairy products (with ten replicate samples), together with principal component analysis showed that dairy samples could be naturally grouped according to the three types of milk evaluated. To further investigate and verify this capability, a linear discriminant analysis together with a simulated annealing variable selection algorithm was also applied to the electrochemical data, which were randomly split into two datasets, one used for model training and internal-validation using a repeated K-fold cross-validation procedure (with 64% of the data); and the other for external validation purposes (containing the remaining 36% of the data). The multivariate supervised strategy used allowed establishing a classification model, based on the potentiometric information of four sensor lipid membranes, which enabled achieving a successful discrimination rate of 100% for both internal-and external-validation processes. The demonstrated versatility of the built electronic tongue for discriminating dairy products according to the type of milk used in their production combined with its simplicity, low-cost and fast time analysis may envisage a possible future application in dairy industry.

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Fluorescence sensor array for identification of commercial milk samples according to their thermal treatments

Cited by 24 publications

References 44 publications

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

New Trends for the Evaluation of Heat Treatments of Milk

Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools

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Fluorescence sensor array for identification of commercial milk samples according to their thermal treatments

Cited by 24 publications

References 44 publications

The combined use of 1H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

The combined use of 1H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

New Trends for the Evaluation of Heat Treatments of Milk

Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools

Contact Info

Product

Resources

About

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk