Identification of cow, buffalo, goat and ewe milk species in fermented dairy products using synchronous fluorescence spectroscopy

Genis, Duygu Ozer; Bilge, Gonca; Sezer, Banu; Durna, Şahin; Boyaci, İsmail Hakkı

doi:10.1016/j.foodchem.2019.01.093

Cited by 36 publications

(18 citation statements)

References 31 publications

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“…Fluorescence in honey is ascribed to proteins, polyphenolic compounds, and Maillard reaction products [23,93,94]. The unique fluorescence patterns of food products have been successfully utilized in authentication studies of food of animal origin, including meat [95,96], fish [97,98], milk [16,17] dairy products [86,90], and honey [23,88,[99][100][101][102].…”

Section: Fluorescence Spectroscopymentioning

confidence: 99%

“…Yogurt and cheese Species identification Front-face fluorescence PLS-DA and PLSR [17] Raw milk Detection of adulterants Time Domain NMR PCA, PLS, and SIMCA [257] Milk powder Detection of adulterants 1 H NMR PCA and Conformity Index [78] Ultra-heat-treated bovine milk Detection of adulterants 1 H and 2D NMR PLS-DA [258] Goat milk Detection of adulterants FT-NIR (10000-4000 cm −1 ) PCA, Q-control, k-NN, SIMCA, and PLS-DA [255] Milk powder Detection of adulterants NIR (850-2499.5 nm) PLSR [259] Dairy Raman spectroscopy is another vibrational spectroscopic technique that has been widely investigated for adulteration purposes. For example, a portable Raman spectrometer was employed to detect melamine, dicyandiamide, urea, ammonium sulfate, and sucrose adulteration of milk.…”

Section: Milk or Dairy Products Authenticity Issue Analytical Techniqmentioning

confidence: 99%

“…The number of scientific works regarding the use of spectroscopy for food authenticity increased from 134 papers during 2010–2014 to 369 papers during 2015–2019 ( Figure 3 a), while the number of total citations ( Figure 3 b) doubled during the last five years (20,784 citations between 2015 and 2019 versus 9666 citations between 2010 and 2014). Some examples of recent applications of spectroscopic techniques for authentication of food products of animal origin include detection of adulteration in meat [ 14 , 15 ] identification of milk species [ 16 , 17 ], detection of thawed muscle foods [ 18 , 19 ] identification of muscle foods species [ 20 , 21 , 22 ], and determination of the botanical origin of honey [ 23 , 24 ], among many others.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Hassoun

Måge

Schmidt

et al. 2020

Foods

111

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Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

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Section: Fluorescence Spectroscopymentioning

confidence: 99%

Section: Milk or Dairy Products Authenticity Issue Analytical Techniqmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Hassoun

Måge

Schmidt

et al. 2020

Foods

111

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“…SFS is very useful for the analysis of mixtures of fluorescent compounds, because both excitation and emission characteristics are included into a single spectrum. SFS exhibits results of several intrinsic fluorescent compounds (tryptophan, vitamin A, riboflavin and other aromatic amino acids) that present in food and provide the fingerprint spectrum of milk (Genis et al, 2019). In the literatures, there are many applications of fluorescence spectroscopy for the quality determination (Ntakatsane et al, 2011 andVelioglu et al, 2017) or identify of the dairy products (Herbert et al, 2000 andDufour, 2008).…”

Section: Identification Of Milk Types Using Front Face and Synchronoumentioning

confidence: 99%

Identification of milk types using two different fluorescence spectroscopy techniques

Elgarhi

El-Aidie²,

Hamdy

et al. 2020

Egypt. J. Food Sci.

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F LUORESCENCE spectroscopy is a technique used to determine fluorescence spectrum that emits by fluorescent compounds. Milk has more than one fluorescent compounds such as tryptophan, vitamin A. Quick identification of milk types is needed for milk quality control and safety. The ability of two different fluorescence spectroscopy techniques (front face fluorescence spectroscopy; FFFS and synchronous scanning fluorescence spectroscopy; SFS) was determined to differentiate 40 milk samples according to their species (10 samples for each of buffalo's, cow's, goat's and sheep's milk). The statistical methods, principal component analysis (PCA) and factorial discriminant analysis (FDA) were used for better understanding the obtained results. FDA was applied separately on the first five principal components obtained from PCA which performed on the two different fluorescence techniques. Results obtained from FDA showed that 100% of correct classification was obtained for data sets from the two different fluorescence techniques. The obtained results confirmed that both the FFFS and SFS were capable of differentiating milk species.

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“…In the dairy industry, the use of low-priced milk in cheese production is a common fraudulent practice, and so, determining the milk origin is a crucial task, which may be accomplished using DNA based methods [17]. Also, the production of some traditional cheeses requires the use of raw ewe's milk, and so the possibility of detecting the use of thermized milk is of utmost relevance, which may be achieved by chromatographic techniques [18].…”

Section: Introductionmentioning

confidence: 99%

Assessing Serra da Estrela PDO cheeses’ origin-production date using fatty acids profiles

et al. 2019

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Serra da Estrela is a Portuguese traditional cheese produced with raw ewe's milk from "Churra Mondegueira" and "Bordaleira" autochthonous breeds and the wild thistle flower (Cynara cardunculus L.), which benefits from the status of Protected Designation of Origin. Cheese chemical composition, namely the fatty acids profile, depends on milk composition and on manufacturing practices. Thus, the identification of possible chemical biomarkers capable of classifying Serra da Estrela cheeses according to the dairy manufacturing plant, geographical origin or production date would be of utmost relevance for producers and consumers. A typical fatty acids profile, including 23 saturated and unsaturated fatty acids, was identified for the studied cheeses, being butyric, caproic, caprilic, capric, lauric, miristic, palmitic, stearic, oleic, linoleic and its trans-isomer and α-linolenic acids the most abundant ones (relative mean abundances ranging from 1.4% ± 0.5% to 23.9% ± 1.9%). Linear discriminant models were established based on the most discriminative fatty acids (namely, caproic, caprilic, undecanoic, lauric, pentadecanoic, palmitic, palmitoleic, heptadecanoic, oleic, linoleic trans-isomer, heneicosanoic and arachidonic acids) that included less abundant fatty acids, which were selected using the simulated annealing algorithm. The established models enabled assessing cheeses' origin (models based on 10-12 fatty acids) and/or production date (model based on 20 fatty acids) with predictive sensitivities of 71-88%. Therefore, fatty acids profiles coupled with chemometric techniques, could be foreseen as a fingerprint of cheese's genuineness, enhancing the consumers' confidence when purchasing this high-value cheese.

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Identification of cow, buffalo, goat and ewe milk species in fermented dairy products using synchronous fluorescence spectroscopy

Cited by 36 publications

References 31 publications

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Identification of milk types using two different fluorescence spectroscopy techniques

Assessing Serra da Estrela PDO cheeses’ origin-production date using fatty acids profiles

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