Cited by 8Identification and Quantification in FoodSpectroscopy and Chemometric AnalysesMeat and Animal Product Quality

High resolution melting is a useful tool to detect animal species sources of various milk types

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Bulut·2023·Journal of Food Science and Technology

Abstract

Accurate identification of animal species sources in milk have become quite important due to adulteration of high-priced milk types in the dairy industry. To date, milk identification methods have mainly depended on biochemical properties or physical properties detected by spectroscopic methods. The current study aimed to develop an easy to use and sensitive DNA-based High resolution melting (HRM) assay to identify animal species and detect cross-adulteration of water buffalo, bovine, goat, sheep, camel and donkey milks. HRM compatible designed primer set, targeted mitochondrial region, successfully amplified the specific targeted region for six animal species DNA and showed a high degree of specificity based on nucleotide variations. Capillary electrophoresis analysis validated the specific amplicons and determined the amplicon lengths as 114 bp for bovine, goat, sheep, and camel, 115 bp for water buffalo, and 121 bp for donkey. HRM analysis showed a clear discrimination for water buffalo-bovine, camel-bovine and donkey-bovine adulteration down to 0.5%, and goat-sheep adulteration down to 1% in the milk admixtures. The efficacy of the method was also confirmed by its standard curve with a very high correlation coefficient In conclusion, the designed HRM assay allows for the rapid, sensitive and cost-effective authentication of milk and dairy products. Supplementary information The online version contains supplementary material available at 10.1007/s13197-023-05705-3.

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Research works printed but not linked: 25

  1. Agrimonti C, Pirondini A, Marmiroli M, Marmiroli N (2015) A quad- ruplex PCR (qxPCR) assay for adulteration in dairy products. Food Chem 187:58-64. https:// doi. org/ 10. 1016/j. foodc hem. 2015. 04. 017 · DOI
  2. Becskei Z, Savić M, Ćirković D et al (2020) Assessment of water buf- falo milk and traditional milk products in a sustainable production system. Sustain (Switz) 12:6616. https:// doi. org/ 10. 3390/ su121 66616 · DOI
  3. Bezerra MF, Souza DFS, Correia PRT (2012) Acidification kinetics, physicochemical properties and sensory attributes of yoghurts pre- pared from mixtures of goat and buffalo milks. Int J Dairy Technol 65:437-443. https:// doi. org/ 10. 1111/j. 1471-0307. 2012. 00845.x · DOI
  4. Bottero MT, Civera T, Anastasio A et al (2002) Identification of cow's milk in "buffalo" cheese by duplex polymerase chain reaction. J Food Prot 65:362-366. https:// doi. org/ 10. 4315/ 0362-028X-65.2. 362 · DOI
  5. Boukria O, El HEM, Boudalia S et al (2020) The effect of mixing milk of different species on chemical, physicochemical, and sensory features of cheeses: a review. Foods 9:1309. https:// doi. org/ 10. 3390/ foods 90913 09 · DOI
  6. Dalmasso A, Civera T, La Neve F, Bottero MT (2011) Simultaneous detection of cow and buffalo milk in mozzarella cheese by real- time PCR assay. Food Chem 124:362-366. https:// doi. org/ 10. 1016/j. foodc hem. 2010. 06. 017 · DOI
  7. Derdak R, Sakoui S, Pop OL et al (2020) Insights on health and food applications of equus asinus (Donkey) milk bioactive proteins and peptides-An overview. Foods 9:1302. https:// doi. org/ 10. 3390/ foods 90913 02 · DOI
  8. Druml B, Cichna-Markl M (2014) High resolution melting (HRM) analysis of DNA-its role and potential in food analysis. Food Chem 158:245-254. https:// doi. org/ 10. 1016/j. foodc hem. 2014. 02. 111 · DOI
  9. Ferreira IMPLV, Caçote H (2003) Detection and quantification of bovine, ovine and caprine milk percentages in protected denomi- nation of origin cheeses by reversed-phase high-performance liquid chromatography of beta-lactoglobulins. J Chromatogr A 1015:111-118. https:// doi. org/ 10. 1016/ S0021-9673(03) 01261-5 · DOI
  10. Ganopoulos I, Sakaridis I, Argiriou A et al (2013) A novel closed- tube method based on high resolution melting (HRM) analysis for authenticity testing and quantitative detection in Greek PDO Feta cheese. Food Chem 141:835-840. https:// doi. org/ 10. 1016/j. foodc hem. 2013. 02. 130 · DOI
  11. Genis DO, Bilge G, Sezer B et al (2019) Identification of cow, buf- falo, goat and ewe milk species in fermented dairy products using synchronous fluorescence spectroscopy. Food Chem 284:60-66. https:// doi. org/ 10. 1016/j. foodc hem. 2019. 01. 093 · DOI
  12. Haygert-Velho IMP, da Conceıção GM, Cosmam LC et al (2018) Mul- tivariate analysis relating milk production, milk composition, and seasons of the year. An Acad Bras Cienc 90:3839-3852. https:// doi. org/ 10. 1590/ 0001-37652 01820 180345 · DOI
  13. Hebert PDN, Cywinska A, Ball SL, DeWaard JR (2003) Biological identifications through DNA barcodes. Proc Royal Soc B Biol Sci. https:// doi. org/ 10. 1098/ rspb. 2002. 2218 · DOI · Paper page
  14. Kara R, Demirel YN (2016) Afyon Kaymaǧi üretiminde kullanilan süt türünün real-time PCR ile belirlenmesi. Ataturk Universitesi Veteriner Bilimleri Dergisi 11:185-190. https:// doi. org/ 10. 17094/ avbd. 77186 · DOI
  15. Kearse M, Moir R, Wilson A et al (2012) Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28:1647-1649. https:// doi. org/ 10. 1093/ bioin forma tics/ bts199 · DOI
  16. López-Calleja I, Alonso IG, Fajardo V et al (2005) PCR detection of cows' milk in water buffalo milk and mozzarella cheese. Int Dairy J 15:1122-1129. https:// doi. org/ 10. 1016/j. idair yj. 2004. 12. 003 · DOI
  17. Martini M, Altomonte I, Licitra R, Salari F (2018) Nutritional and nutraceutical quality of donkey Milkfile:///C:/Users/user/Desk- top/kaan hoca makaleler/1-s2.0-S0022030289792857-main.pdf. J Equine Vet Sci 65:33-37. https:// doi. org/ 10. 1016/j. jevs. 2017. 10. 020 · DOI
  18. Paszczyk B, Polak-Śliwińska M, Zielak-Steciwko AE (2022) Chemical composition, fatty acid profile, and lipid quality ındices in com- mercial ripening of cow cheeses from different seasons. Animals. https:// doi. org/ 10. 3390/ ani12 020198 · DOI
  19. Paul AA, Kumar S, Kumar V, Sharma R (2020) Milk analog: plant based alternatives to conventional milk, production, potential and health concerns. Crit Rev Food Sci Nutr 60:3005-3023. https:// doi. org/ 10. 1080/ 10408 398. 2019. 16742 · DOI
  20. Pegels N, González I, Martín I et al (2011) Applicability assessment of a real-time PCR assay for the specific detection of bovine, ovine and caprine material in feedstuffs. Food Control. https:// doi. org/ 10. 1016/j. foodc ont. 2011. 01. 015 · DOI
  21. Pokorska J, Kułaj D, Dusza M et al (2016) New rapid method of DNA isolation from milk somatic cells. Anim Biotechnol 27:113-117. https:// doi. org/ 10. 1080/ 10495 398. 2015. 11164 · DOI
  22. Sakaridis I, Ganopoulos I, Argiriou A, Tsaftaris A (2013) High resolu- tion melting analysis for quantitative detection of bovine milk in pure water buffalo mozzarella and other buffalo dairy products. Int Dairy J 28:32-35. https:// doi. org/ 10. 1016/j. idair yj. 2012. 08. 006 · DOI
  23. Traugott M, Kamenova S, Ruess L et al (2013) Empirically Charac- terising trophic networks: what emerging DNA-Based methods, stable ısotope and fatty acid analyses can offer. In: Advances in Ecological Research van der Stoep N, van Paridon CDM, Janssens T et al (2009) Diagnos- tic guidelines for high-resolution melting curve (HRM) analysis: an interlaboratory validation of BRCA1 mutation scanning using the 96-well LightScanner TM . Hum Mutat. https:// doi. org/ 10. 1002/ humu. 21004 · DOI
  24. Wittwer CT, Reed GH, Gundry CN et al (2003) High-resolution geno- typing by amplicon melting analysis using LCGreen. Clin Chem. https:// doi. org/ 10. 1373/ 49.6. 853 · DOI
  25. Zhao DB, Bai YH, Niu YW (2015) Composition and characteristics of Chinese Bactrian camel milk. Small Rumin Res 127:58-67. https:// doi. org/ 10. 1016/j. small rumres. 2015. 04. 008 · DOI

Cited by

Authors
Bulut
Venue
Journal of Food Science and Technology
Published
2023-02-28
Volume
60
Issue
5
Pages
1612-1620
ISSN
  • 0022-1155 (ISSN-L)
  • 0975-8402
OpenAlex
W4322626551
Cited by
8
References
0
Citations by year
2026: 4 · 2024: 3 · 2023: 1
FWCI
0.71
Type
journal article
Language
en
Open access
Locations
  • Journal of Food Science and Technology (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Identification and Quantification in Food
  • Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Meat and Animal Product Quality
Keywords
high-resolution melting analysis, milk adulteration, animal species identification, milk authentication, mitochondrial DNA, buffalo milk, cow's milk, goat milk, sheep milk, camel milk, donkey milk, dairy products

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