Abstract
This study aimed to evaluate the performance of both near-infrared (NIR) diffuse reflectance and mid-infrared-attenuated total reflectance (MIR-ATR) in determining some quality parameters of a commercial white cheese made of unknown ratios of various milk species. For this purpose, 81 commercial Ezine cheese samples, a special ripened cheese produced in Turkey, containing unknown ratios of bovine, caprine, and ovine milk, were used. Reference analyses, including textural properties, protein content, nitrogen fractions, ripening index coefficients, fat, salt, dry matter-moisture, and ash contents as well as pH and titratable acidity levels, were conducted in the samples following the traditional gold standards. For NIR applications, the spectra of both intact cubes and hand-crushed cheese samples were collected, whereas the spectra of only hand-crushed cheese samples were collected for MIR-ATR. PLSR (Partial Least Squares Regression) calibration models were developed for each parameter (n = 61) and then validated using both cross-validation (leave-one-out approach) and an external validation set (n = 20). Overall, PLSR models developed for total protein, fat, salt, dry matter, moisture, and ash content, as well as pH and titratable acidity, yielded satisfactory performance statistics in the complementary use of NIR and MIR spectroscopy. However, PLSR models of the other parameters, including textural properties, nitrogen fractions, and the ripening index, could only separate high and low values and were not able to make accurate quantitative predictions. NIR spectroscopy was found to be more accurate than that of MIR-ATR spectroscopy for almost all the parameters except for pH and titratable acidity, for which MIR-ATR spectroscopy was superior.
Similar content being viewed by others
References
AOAC (2000a) Chloride (total) in cheese, Volhard method. Official methods of analysis of AOAC International 935.43. AOAC International, Gaithersburg, MD, USA
AOAC (2000b) Ash of cheese gravimetric method. Official methods of analysis of AOAC International 935.42. AOAC International, Gaithersburg, MD, USA
AOAC (2012) Official Method 948.22. Fat (crude) in nuts and nut products. Gravimetric methods, In: Official Methods of Analysis of AOAC International, 19th ed, AOAC International, Gaithersburg, MD, USA
Blazquez C, Downey G, O’Callaghan D, Howard V, Delahunty C, Sheehan E, Everard C, O’Donnell CP (2006) Modelling of sensory and instrumental texture parameters in processed cheese by near infrared reflectance spectroscopy. J Dairy Res 73(1):58–69
Botelho BG, Mendes BA, Sena MM (2013) Development and analytical validation of robust near-infrared multivariate calibration models for the quality inspection control of mozzarella cheese. Food Anal Method 6(3):881–891
Bradley RL Jr, Arnold E Jr, Barbano DM, Semerad RG, Smith DE, Vines BK (1992) Chemical and physical methods. In: Marshall RT (ed) Standard methods for the examination of dairy products, am. Public Health Assoc, Washington DC, pp 433–531
Čurda L, Kukačková O (2004) NIR spectroscopy: a useful tool for rapid monitoring of processed cheeses manufacture. Food Eng 61(4):557–560
Curro S, Manuelian CL, Penasa M, Cassandro M, Marchi MDe (2017) Technical note: feasibility of near infrared transmittance spectroscopy to predict cheese ripeness. J Dary Sci 100(11):8759–8763
Jong SD (1993) PLS fits closer than PCR. J Chemom 7(6):551–557
Downey G, Sheehan E, Delahunty C, O’Callaghan D, Guinee T, Howard V (2005) Prediction of maturity and sensory attributes of cheddar cheese using near-infrared spectroscopy. Int Dairy J 15(6–9):701–709
Fagan CC, Everard C, O’Donnell CP, Downey G, Sheehan EM, Delahunty CM, Howard V (2007) Prediction of processed cheese instrumental texture and meltability by mid-infrared spectroscopy coupled with chemometric tools. J Food Eng 80(4):1068–1077
Fagan CC, O’donnell CP, O’callaghan DJ, Downey G, Sheehan EM, Delahunty CM, Everald TP, Howard V (2007) Application of mid-infrared spectroscopy to the prediction of maturity and sensory texture attributes of cheddar cheese. J Food Sci 72(3):E130–E137
González-Martín I, González-Pérez C, Hernández-Hierro JM, González-Cabrera JM (2008) Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in cheese. Talanta 75(2):351–355
IDF (2019) IDF World dairy situation report, 2019. https://www.fil-idf.org/#1464615207164-5a2d083c-557c. Accessed 22 April 2020.
ISO (2003) International Organisation for Standardisation No. 8968. Milk–Determination of nitrogen content—Part 2: Block digestion method (Macro method), 1st edn. ISO copyright office, Geneva
ISO (2008) International Organisation for Standardization No. 5534. Cheese and processed cheese—Determination of the total solids content (Reference method), 1st edn. ISO copyright office, Geneva
ISO (2009) International Organisation for Standardisation No. 3433. Cheese-Determination of fat content—Van Gulik method, 1st edn. ISO copyright office, Geneva
Jarrett WD, Aston JW, Dulley JR (1982) A simple method for estimating free amino acids in cheddar cheese. Aust J Dairy Technol 37(2):55–58
Karoui R, Mouazen AM, Dufour É, Pillonel L, Schaller E, De Baerdemaeker J, Bosset JO (2006) Chemical characterisation of European Emmental cheeses by near infrared spectroscopy using chemometric tools. Int Dairy J 16(10):1211–1217
Karoui R, Mouazen AM, Dufour É, Pillonel L, Picque D, Bosset JO, De Baerdemaeker J (2006) Mid-infrared spectrometry: a tool for the determination of chemical parameters in Emmental cheeses produced during winter. Le Lait 86(1):83–97
Kraggerud H, Næs T, Abrahamsen RK (2014) Prediction of sensory quality of cheese during ripening from chemical and spectroscopy measurements. Int Dairy J 34(1):6–18
Kuchroo CN, Fox PF (1982) Soluble nitrogen in cheddar cheese: comparison of extraction procedures. Milchwissenschaft 37:331–335
Lee SJ, Jeon IJ, Harbers LH (1997) Near-infrared reflectance spectroscopy for rapid analysis of curds during cheddar cheese making. J Food Sci 62(1):53–56
Madalozzo ES, Sauer E, Nagata N (2015) Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration. J Food Sci Tech 52(3):1649–1655
Margolies BJ, Barbano DM (2018) Determination of fat, protein, moisture, and salt content of cheddar cheese using mid-infrared transmittance spectroscopy. J Dairy Sci 101(2):924–933
Martens H, Jensen SA, Geladi P (1983) Multivariate linearity transformation for near-infrared reflectance spectrometry. In proceedings of the nordic symposium on applied statistics, Stokkand Forlag Publishers Stavanger, Norway, pp. 205–234.
Moseholm L (1988) Analysis of air pollution plant exposure data: the soft independent modelling of class analogy (SIMCA) and partial least squares modelling with latent variable (PLS) approaches. Environ Pollut 53(1–4):313–331
Polychroniadou A, Michaelidou A, Paschaloudis N (1999) Effect of time, temperature and extraction method on the trichloroacetic acid-soluble nitrojen of cheese. Int Dairy J 9(8):559–568
Pu YY, O’Donnell C, Tobin J, O’Shea N (2019) Review of near-infrared spectroscopy as a process analytical technology for real-time product monitoring in dairy processing. Int Dairy J 103:104623
Revilla I, Gonzalez-Martin I, Hernández-Hierro JM, Vivar-Quintana A, González-Pérez C, Lurueña-Martínez MA (2009) Texture evaluation in cheeses by NIRS technology employing a fibre-optic probe. J Food Eng 92(1):24–28
Revilla I, González-Martín MI, Vivar-Quintana AM, Blanco-López MA, Lobos-Ortega IA, Hernández-Hierro JM (2016) Antioxidant capacity of different cheeses: Affecting factors and prediction by near infrared spectroscopy. J Dairy Sci 99(7):5074–5082
Rinnan Å, Nørgaard L, van den Berg F, Thygesen J, Bro R, Balling Engelsen S (2009) Data pre-processing. Chapter 2 in infrared spectroscopy for food quality analysis and control. Academic Press, London
Rodriguez-Otero JL, Hermida M, Cepeda A (1995) Determination of fat, protein, and total solids in cheese by near-infrared reflectance spectroscopy. AOAC Int 78(3):802–806
Rodriguez-Saona L, Ayvaz H, Wehling RL (2017) Infrared and raman spectroscopy. In: Nielsen S (ed) Food analysis food science text series. Springer, Cham, pp 107–127
Rodriguez-Saona LE, Koca N, Harper WJ, Alvarez VB (2006) Rapid determination of swiss cheese composition by fourier transform infrared/attenuated total reflectance spectroscopy. J Dairy Sci 89(5):1407–1412
Soto-Barajas MC, González-Martín MI, Salvador-Esteban J, Hernández-Hierro JM, Moreno-Rodilla V, Vivar-Quintana AM, Revilla I, Lobos-Ortega I, Moron-Sancho R, Curto-Diego B (2013) Prediction of the type of milk and degree of ripening in cheeses by means of artificial neural networks with data concerning fatty acids and near infrared spectroscopy. Talanta 116:50–55
Sultaneh A, Rohm H (2007) Using near infrared spectroscopy for the determination of total solids and protein content in cheese curd. Int J Dairy Technol 60(4):241–244
TPE (2006) Coğrafi İşaret Tescil Belgesi. Türk Patent Enstitüsü, Yenimahalle, Ankara. Tescil No:86, Başvuru No: C 2006/004.
Williams P (2017) Near-infrared spectroscopy. The basics. In 18th international Conference on near infrared spectroscopy (ICNIRS 2017). Copenhagen: Denmark.
Wittrup C, Nørgaard L (1998) Rapid near infrared spectroscopic screening of chemical parameters in semi-hard cheese using chemometrics. J Dairy Sci 81(7):1803–1809
Acknowledgements
This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) (Project No: 116O737).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declared that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Ayvaz, H., Mortas, M., Dogan, M.A. et al. Near- and mid-infrared determination of some quality parameters of cheese manufactured from the mixture of different milk species. J Food Sci Technol 58, 3981–3992 (2021). https://doi.org/10.1007/s13197-020-04861-0
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13197-020-04861-0