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Süt Örneğinde FTIR ile Birleştirilmiş Kemometrik Yöntemle Tağşiş Tespiti

Year 2024, , 20 - 31, 30.06.2024
https://doi.org/10.53501/rteufemud.1389597

Abstract

Hayvansal kaynaklı gıda ürünlerinde tür tağşişi tüketici hakları ve işletme güvenilirliği açısından çok önemlidir. Bu çalışmada, çiğ manda sütüne % 0,25, % 0,5, % 1, % 1,5 % 2, % 5, % 10, % 15 ve % 20 oranlarında çiğ inek sütü karıştırılmış ve örnekler Fourier Dönüşümlü Kızılötesi - Zayıflatılmış Toplam Yansıma (FTIR-ATR) cihazında analiz edilmiştir. Elde edilen spektrumlarda biyobelirteç olarak kullanılabilecek piklerin verileri tek yönlü varyans analizi (ANOVA) ile değerlendirilmiştir. Spektrumda 1742 cm-1 karbonil piki (C=O), 1640 cm-1 amid I piki, 1160 cm-1 laktoza ait C-O piki, 2920 cm-1 CH2 piki, 2850 cm-1 CH piki ve 3300 cm-1 O-H piki olmak üzere toplam 6 pike ait veriler kemometrik analizlerde kullanılmıştır. Hiyerarşik kümeleme analizi (HCA) ile dendogramda %15’in üzerindeki konsantrasyonlar tespit edilebilmişmiş ancak %15 (v/v) konsantrasyonun altındaki değerlerin ayrımı dendogramda beklenen önemlilikte yansımamıştır. Temel bileşen analizinde (PCA) ise, su ve protein içeriklerinin oldukça benzer olduğu buna karşın yağ asitlerin, laktoz ve karbonil içeriklerinin az da olsa farklılık oluşturduğu ancak konsantrasyonlarda beklenen ayrımı gerçekleştirmediği görülmüştür. Saf, %1, %2 ve % 5 konsantrasyonların daha düşük PC1, % 15 ve 20 çoğunluğunun daha yüksek PC1 skoruna sahip olduğu görülmüştür.

References

  • Bonfatti, V., Di Martino, G., Carnier, P. (2011). Effectiveness of mid-infrared spectroscopy for the prediction of detailed protein composition and contents of protein genetic variants of individual milk of Simmental cows. Journal of Dairy Science, 94(12), 5776–5785. https://doi.org/10.3168/jds.2011-4401
  • Coates, J. (2000). Encyclopedia of Analytical Chemistry, In: Interpretation of Infrared Spectra A Practical Approach, John Wiley and Sons Limited, ISBN: 0471976709, Chichester, England.
  • Damto, T., Zewdu, A., Birhanu, T. (2023). Application of Fourier transform infrared (FT-IR) spectroscopy and multivariate analysis for detection of adulteration in honey markets in Ethiopia. Current Research in Food Science, 7, 100565. https://doi.org/10.1016/j.crfs.2023.100565
  • De Marchi, M., Penasa, M., Cecchinato, A., Mele, M., Secchiari, P., Bittante, G. (2011). Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk. Animal, 5(10), 1653–1658. https://doi.org/10.1017/S1751731111000747
  • Di Pinto, A., Terio, V., Marchetti, P., Bottaro, M., Mottola, A., Bozzo, G., Bonerba, E., Ceci, E., Tantillo, G. (2017). DNA-based approach for species identification of goat-milk products. Food Chemistry, 229, 93–97. https://doi.org/10.1016/j.foodchem.2017.02.067.
  • Dole, M. N., Patel, P. A., Sawant, S. D., Shedpure, P. S. (2011). Advance applications of fourier transform infrared spectroscopy. International Journal of Pharmaceutical Sciences Review and Research, 7(2), 159-166.
  • Fagan, C. C. and O’Donnell, C. P. (2008). Application of Mid-Infrared Spectroscopy to Food Processing Systems, In: Nondestructive Testing of Food Quality, Blackwell Publishing, ISBN: 9780813828855, Oxford, England. https://doi.org/10.1002/9780470388310.ch5
  • Gu, M., Cosenza, G., Nicolae, I., Bota, A., Guo, Y., Di Stasio, L., Pauciullo, A. (2017). Transcript analysis at DGAT1 reveals different mRNA profiles in river buffaloes with extreme phenotypes for milk fat. Journal of Dairy Science, 100(10), 8265–76. https://doi.org/10.3168/jds.2017-12771
  • Handi, J., Knowles, J., Kell, D. G. (2005). Computational cluster validation in post-genomic data analysis. Bioinformatics, 21(15), 3201–3212. https://doi.org/10.1093/bioinformatics/bti517
  • Helm, D., Labischinski, H., Schallehn, G., Naumann, D. (1991). Classification and identification of bacteria by fourier-transform infrared spectroscopy. Journal of General Microbiology, 131, 69-79. https://doi.org/10.1099/00221287-137-1-69
  • Hsu, C. P. S. (1997). Handbook of Instrumental Techniques for Analytical Chemistry, In: Separation Sciences Research and Product Development, Prentice-Hall Inc., ISBN: 0131773380, New Jersey, USA.
  • Johnson, R. A., Wichern, D. W. (2002). Applied Multivariate Statistical Analysis. Prentice Hall, ISBN: 0130925535, New Jersey, USA.
  • Kamal, M., Karoui, R. (2015). Analytical methods coupled with chemometric tools for determining the authenticity and detecting the adulteration of dairy products: A review. Trends in Food Science and Technology, 46, 27–48. https://doi.org/10.1016/j.tifs. 2015.07.007
  • Kang, O. J. (2016). Evaluation of melanoidins formed from black garlic after different thermal processing steps. Preventive Nutrition and Food Science, 21, 398–405. https://doi.org/10.3746/pnf.2016.21.4.398.
  • Kopuzlu, S., Onenc, A., Bilgin, O. C., Esenbuga, N. (2011). Determination of meat quality through principal components analysis. The Journal of Animal and Plant Science, 21(2), 151‐156.
  • Limm, W., Karunathilaka, S. R., Mossoba, M. M., (2023). Fourier transform infrared spectroscopy and chemometrics for the rapid screening of economically motivated adulteration of honey spiked with corn or rice syrup. Journal of Food Processing and Preservation, 86(4), 100054. https://doi.org/10.1016/j.jfp.2023.100054
  • Lindmark-Månsson, H., Fonde´na, R., Pettersson, H. E. (2003). Composition of Swedish dairy milk. International Dairy Journal, 13, 409–425. https://doi.org/10.1016/S0958-6946(03)00032-3
  • Lohumi, S., Mo, C., Kang, J. S., Hong, S. J., Cho, B. K. (2013). Nondestructive evaluation for the viability of watermelon (Citrullus lanatus) seeds using Fourier transform near infrared spectroscopy. Journal of Biosystems Engineering, 38(4), 312e317. https://doi.org/10.5307/JBE.2013.38.4.312
  • Manuelian, C.L., Visentin, G., Boselli, C., Giangolini, G., Cassandro, M., De Marchi, M. (2017). Short communication: Prediction of milk coagulation and acidity traits in Mediterranean buffalo milk using fourier-transform mid-infrared spectroscopy. Journal of Dairy Science, 100(9), 7083–7087. https://doi.org/10.3168/jds.2017-12707
  • Maryam, M. M., Pirouzi, M., Saberi, M. R., Chamani J. (2014). Comparison of the binding behavior of FCCP with HSA and HTF as determined by spectroscopic and molecular modeling techniques. Luminescence, 29(4), 314–331. https://doi.org/10.1002/bio.2546
  • McDermott, A., Visentin, G., De Marchi, M., Berry, D. P., Fenelon, M.A., O’Connor, P. M., Kenny, O. A., McParland, S. (2016). Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics. Journal of Dairy Science, 99(4), 3171–3182. https://doi.org/10.3168/jds.2015-9747
  • Miller, G. D, Jarvis, J. K., McBean, L. D. (2007). Handbook of Dairy Foods and Nutrition, CRC Press, ISBN: 100849328284, New York, USA.
  • Mohsin, G. H., Schmitt F. J., Kanzler C., Hoehl A., Hornemann, A. (2019). PCA-based identification and differentiation of FTIR data from model melanoidins with specific molecular compositions. Food Chemistry, 281, 106–113. https://doi.org/10.1016/j.foodchem.2018.12.054
  • Parodi, P. W. (2004). Milk fat in human nutrition. Australian Journal of Dairy Technology, 59, 3–59.
  • Pietrzak-Fiećko, R., Kamelska-Sadowska, A. M. (2020). The comparison of nutritional value of human milk with other mammals’ milk. Nutrients, 12, 1404. https://doi.org/10.3390/nu12051404
  • Pereira, E. V. S., Fernandes, D. D. S., De Araújo, M. C. U., Diniz, P. H. G. D., Maciel, M. I. S. (2020). Simultaneous determination of goat milk adulteration with cow milk and their fat and protein contents using NIR spectroscopy and PLS algorithms. Lebensmittel-Wissenschaft und Technologie, 127, 109427. https://doi.org/10.1016/j.lwt.2020.109427
  • Pesic, M., Barac, M., Vrvic, M., Ristic, N., Macej, O., Stanojevic, S. (2011). Qualitative and quantitative analysis of bovine milk adulteration in caprine and ovine milks using native-page. Food Chemistry, 125(4), 1443–1449. https://doi.org/10.1016/j. foodchem.2010.10.045
  • Ravinder, D., Gowtham, P., Khatri, K., Pawar, S. C., Botlagunta, M. (2021). Comparison of various milk samples using spectroscopy chromatography and microscopic analysis. Journal of Food Science and Nutrition Research, 4(1), 12-22. https://doi.org/10.26502/jfsnr.2642-11000059
  • Rutten, M. J. M., Bovenhuis, H., Hettinga, K. A. van Valenberg, H. J. F., van Arendonk, J. A. M. (2009). Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer, Journal of Dairy Science, 92(12), 6202–6209, https://doi.org/10.3168/jds.2009-2456
  • Sen, S., Dundar, Z., Uncu, O., Ozen, B. (2021). Potential of Fourier-transform infrared spectroscopy in adulteration detection and quality assessment in buffalo and goat milks. Microchemical Journal, 166, 106207. https://doi.org/10.1016/j.microc.2021.106207
  • Siska, S., Jumadil, M. I., Abdullah, S., Ramadon, D., Mun’im, A. (2023). ATR-FTIR and chemometric method for the detection of pig-based derivatives in food products-A review. International Food Research Journal, 30(2), 281–289. https://doi.org/10.47836/ifrj.30.2.01
  • Song, H., Xue, H., Han, Y. (2011). Detection of cow's milk in Shaanxi goat's milk with an ELISA assay. Food Control, 22(6), 883–887. https://doi.org/10.1016/j.foodcont.2010.11.019.
  • Sun, D-W. (2009). Fourier Transform Infrared (FTIR) Spectroscopy. Infrared Spectroscopy for Food Quality Analysis and Control. Academic Press, ISBN: 9780123741363, Cambridge, Massachusetts, ABD. https://doi.org/10.1016/B978-0-12-374136-3.00007-9
  • Toffanin, V., De Marchi, M., Lopez-Villalobos, N., Cassandro, M. (2015). Effectiveness of mid infrared spectroscopy for prediction of the contents of calcium and phosphorus, and titratable acidity of milk and their relationship with milk quality and coagulation properties. International Dairy Journal, 41, 68–73, https://doi.org/10.1016/j. idairyj.2014.10.002
  • Yaman, H. (2020). A rapid method for detection adulteration in goat milk by using vibrational spectroscopy in combination with chemometric methods. Journal of Food Science and Technology, 57(8), 3091–3098. https://doi.org/10.1007/s13197-020-04342-4
  • Zhou, Q., Sun, S.-Q., Yu, L., Xu, C.-H., Noda, I., Zhang, X.-R. (2006). Sequential changes of main components in different kinds of milk powders using two-dimensional in frared correlation analysis. Journal of Molecular Structure, 799(1), 77–84.
Year 2024, , 20 - 31, 30.06.2024
https://doi.org/10.53501/rteufemud.1389597

Abstract

References

  • Bonfatti, V., Di Martino, G., Carnier, P. (2011). Effectiveness of mid-infrared spectroscopy for the prediction of detailed protein composition and contents of protein genetic variants of individual milk of Simmental cows. Journal of Dairy Science, 94(12), 5776–5785. https://doi.org/10.3168/jds.2011-4401
  • Coates, J. (2000). Encyclopedia of Analytical Chemistry, In: Interpretation of Infrared Spectra A Practical Approach, John Wiley and Sons Limited, ISBN: 0471976709, Chichester, England.
  • Damto, T., Zewdu, A., Birhanu, T. (2023). Application of Fourier transform infrared (FT-IR) spectroscopy and multivariate analysis for detection of adulteration in honey markets in Ethiopia. Current Research in Food Science, 7, 100565. https://doi.org/10.1016/j.crfs.2023.100565
  • De Marchi, M., Penasa, M., Cecchinato, A., Mele, M., Secchiari, P., Bittante, G. (2011). Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk. Animal, 5(10), 1653–1658. https://doi.org/10.1017/S1751731111000747
  • Di Pinto, A., Terio, V., Marchetti, P., Bottaro, M., Mottola, A., Bozzo, G., Bonerba, E., Ceci, E., Tantillo, G. (2017). DNA-based approach for species identification of goat-milk products. Food Chemistry, 229, 93–97. https://doi.org/10.1016/j.foodchem.2017.02.067.
  • Dole, M. N., Patel, P. A., Sawant, S. D., Shedpure, P. S. (2011). Advance applications of fourier transform infrared spectroscopy. International Journal of Pharmaceutical Sciences Review and Research, 7(2), 159-166.
  • Fagan, C. C. and O’Donnell, C. P. (2008). Application of Mid-Infrared Spectroscopy to Food Processing Systems, In: Nondestructive Testing of Food Quality, Blackwell Publishing, ISBN: 9780813828855, Oxford, England. https://doi.org/10.1002/9780470388310.ch5
  • Gu, M., Cosenza, G., Nicolae, I., Bota, A., Guo, Y., Di Stasio, L., Pauciullo, A. (2017). Transcript analysis at DGAT1 reveals different mRNA profiles in river buffaloes with extreme phenotypes for milk fat. Journal of Dairy Science, 100(10), 8265–76. https://doi.org/10.3168/jds.2017-12771
  • Handi, J., Knowles, J., Kell, D. G. (2005). Computational cluster validation in post-genomic data analysis. Bioinformatics, 21(15), 3201–3212. https://doi.org/10.1093/bioinformatics/bti517
  • Helm, D., Labischinski, H., Schallehn, G., Naumann, D. (1991). Classification and identification of bacteria by fourier-transform infrared spectroscopy. Journal of General Microbiology, 131, 69-79. https://doi.org/10.1099/00221287-137-1-69
  • Hsu, C. P. S. (1997). Handbook of Instrumental Techniques for Analytical Chemistry, In: Separation Sciences Research and Product Development, Prentice-Hall Inc., ISBN: 0131773380, New Jersey, USA.
  • Johnson, R. A., Wichern, D. W. (2002). Applied Multivariate Statistical Analysis. Prentice Hall, ISBN: 0130925535, New Jersey, USA.
  • Kamal, M., Karoui, R. (2015). Analytical methods coupled with chemometric tools for determining the authenticity and detecting the adulteration of dairy products: A review. Trends in Food Science and Technology, 46, 27–48. https://doi.org/10.1016/j.tifs. 2015.07.007
  • Kang, O. J. (2016). Evaluation of melanoidins formed from black garlic after different thermal processing steps. Preventive Nutrition and Food Science, 21, 398–405. https://doi.org/10.3746/pnf.2016.21.4.398.
  • Kopuzlu, S., Onenc, A., Bilgin, O. C., Esenbuga, N. (2011). Determination of meat quality through principal components analysis. The Journal of Animal and Plant Science, 21(2), 151‐156.
  • Limm, W., Karunathilaka, S. R., Mossoba, M. M., (2023). Fourier transform infrared spectroscopy and chemometrics for the rapid screening of economically motivated adulteration of honey spiked with corn or rice syrup. Journal of Food Processing and Preservation, 86(4), 100054. https://doi.org/10.1016/j.jfp.2023.100054
  • Lindmark-Månsson, H., Fonde´na, R., Pettersson, H. E. (2003). Composition of Swedish dairy milk. International Dairy Journal, 13, 409–425. https://doi.org/10.1016/S0958-6946(03)00032-3
  • Lohumi, S., Mo, C., Kang, J. S., Hong, S. J., Cho, B. K. (2013). Nondestructive evaluation for the viability of watermelon (Citrullus lanatus) seeds using Fourier transform near infrared spectroscopy. Journal of Biosystems Engineering, 38(4), 312e317. https://doi.org/10.5307/JBE.2013.38.4.312
  • Manuelian, C.L., Visentin, G., Boselli, C., Giangolini, G., Cassandro, M., De Marchi, M. (2017). Short communication: Prediction of milk coagulation and acidity traits in Mediterranean buffalo milk using fourier-transform mid-infrared spectroscopy. Journal of Dairy Science, 100(9), 7083–7087. https://doi.org/10.3168/jds.2017-12707
  • Maryam, M. M., Pirouzi, M., Saberi, M. R., Chamani J. (2014). Comparison of the binding behavior of FCCP with HSA and HTF as determined by spectroscopic and molecular modeling techniques. Luminescence, 29(4), 314–331. https://doi.org/10.1002/bio.2546
  • McDermott, A., Visentin, G., De Marchi, M., Berry, D. P., Fenelon, M.A., O’Connor, P. M., Kenny, O. A., McParland, S. (2016). Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics. Journal of Dairy Science, 99(4), 3171–3182. https://doi.org/10.3168/jds.2015-9747
  • Miller, G. D, Jarvis, J. K., McBean, L. D. (2007). Handbook of Dairy Foods and Nutrition, CRC Press, ISBN: 100849328284, New York, USA.
  • Mohsin, G. H., Schmitt F. J., Kanzler C., Hoehl A., Hornemann, A. (2019). PCA-based identification and differentiation of FTIR data from model melanoidins with specific molecular compositions. Food Chemistry, 281, 106–113. https://doi.org/10.1016/j.foodchem.2018.12.054
  • Parodi, P. W. (2004). Milk fat in human nutrition. Australian Journal of Dairy Technology, 59, 3–59.
  • Pietrzak-Fiećko, R., Kamelska-Sadowska, A. M. (2020). The comparison of nutritional value of human milk with other mammals’ milk. Nutrients, 12, 1404. https://doi.org/10.3390/nu12051404
  • Pereira, E. V. S., Fernandes, D. D. S., De Araújo, M. C. U., Diniz, P. H. G. D., Maciel, M. I. S. (2020). Simultaneous determination of goat milk adulteration with cow milk and their fat and protein contents using NIR spectroscopy and PLS algorithms. Lebensmittel-Wissenschaft und Technologie, 127, 109427. https://doi.org/10.1016/j.lwt.2020.109427
  • Pesic, M., Barac, M., Vrvic, M., Ristic, N., Macej, O., Stanojevic, S. (2011). Qualitative and quantitative analysis of bovine milk adulteration in caprine and ovine milks using native-page. Food Chemistry, 125(4), 1443–1449. https://doi.org/10.1016/j. foodchem.2010.10.045
  • Ravinder, D., Gowtham, P., Khatri, K., Pawar, S. C., Botlagunta, M. (2021). Comparison of various milk samples using spectroscopy chromatography and microscopic analysis. Journal of Food Science and Nutrition Research, 4(1), 12-22. https://doi.org/10.26502/jfsnr.2642-11000059
  • Rutten, M. J. M., Bovenhuis, H., Hettinga, K. A. van Valenberg, H. J. F., van Arendonk, J. A. M. (2009). Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer, Journal of Dairy Science, 92(12), 6202–6209, https://doi.org/10.3168/jds.2009-2456
  • Sen, S., Dundar, Z., Uncu, O., Ozen, B. (2021). Potential of Fourier-transform infrared spectroscopy in adulteration detection and quality assessment in buffalo and goat milks. Microchemical Journal, 166, 106207. https://doi.org/10.1016/j.microc.2021.106207
  • Siska, S., Jumadil, M. I., Abdullah, S., Ramadon, D., Mun’im, A. (2023). ATR-FTIR and chemometric method for the detection of pig-based derivatives in food products-A review. International Food Research Journal, 30(2), 281–289. https://doi.org/10.47836/ifrj.30.2.01
  • Song, H., Xue, H., Han, Y. (2011). Detection of cow's milk in Shaanxi goat's milk with an ELISA assay. Food Control, 22(6), 883–887. https://doi.org/10.1016/j.foodcont.2010.11.019.
  • Sun, D-W. (2009). Fourier Transform Infrared (FTIR) Spectroscopy. Infrared Spectroscopy for Food Quality Analysis and Control. Academic Press, ISBN: 9780123741363, Cambridge, Massachusetts, ABD. https://doi.org/10.1016/B978-0-12-374136-3.00007-9
  • Toffanin, V., De Marchi, M., Lopez-Villalobos, N., Cassandro, M. (2015). Effectiveness of mid infrared spectroscopy for prediction of the contents of calcium and phosphorus, and titratable acidity of milk and their relationship with milk quality and coagulation properties. International Dairy Journal, 41, 68–73, https://doi.org/10.1016/j. idairyj.2014.10.002
  • Yaman, H. (2020). A rapid method for detection adulteration in goat milk by using vibrational spectroscopy in combination with chemometric methods. Journal of Food Science and Technology, 57(8), 3091–3098. https://doi.org/10.1007/s13197-020-04342-4
  • Zhou, Q., Sun, S.-Q., Yu, L., Xu, C.-H., Noda, I., Zhang, X.-R. (2006). Sequential changes of main components in different kinds of milk powders using two-dimensional in frared correlation analysis. Journal of Molecular Structure, 799(1), 77–84.
There are 36 citations in total.

Details

Primary Language Turkish
Subjects Instrumental Methods
Journal Section Research Articles
Authors

Sinem Çolak 0000-0001-6731-327X

Publication Date June 30, 2024
Submission Date November 13, 2023
Acceptance Date January 23, 2024
Published in Issue Year 2024

Cite

APA Çolak, S. (2024). Süt Örneğinde FTIR ile Birleştirilmiş Kemometrik Yöntemle Tağşiş Tespiti. Recep Tayyip Erdogan University Journal of Science and Engineering, 5(1), 20-31. https://doi.org/10.53501/rteufemud.1389597

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