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Evaluation of maturation changes in the handcrafted waxed dry cheese from Southern Mexico using infrared spectroscopy and chemometrics: prospective tools for adding value to local products

Published online by Cambridge University Press:  08 September 2025

Valeria Martínez-Aquino ,
Edna E. Suárez-Patlán ,
Anastacio Espejel-García ,
Arturo Hernández-Montes  and
Alma L. Saucedo Open the ORCID record for Alma L. Saucedo [Opens in a new window]
Valeria Martínez-Aquino
Affiliation:
Departamento de Ingeniería Agroindustrial, Universidad Autónoma Chapingo, Texcoco, México
Edna E. Suárez-Patlán
Affiliation:
Campo Experimental San Martinito, Centro de Investigación Regional - Golfo Centro, INIFAP, Puebla, México
Anastacio Espejel-García
Affiliation:
Posgrado en Ciencia y Tecnología Agroalimentaria, Universidad Autónoma Chapingo, Texcoco, México
Arturo Hernández-Montes*
Affiliation:
Posgrado en Ciencia y Tecnología Agroalimentaria, Universidad Autónoma Chapingo, Texcoco, México
Alma L. Saucedo*
Affiliation:
Secretaría de Ciencia, Humanidades, Tecnología e Innovación, Insurgentes, Ciudad de México, México Laboratorio Nacional de Investigación y Servicio Agroalimentario y Forestal, Universidad Autónoma Chapingo, Texcoco, México
*
Corresponding author: Alma L. Saucedo; Email: allesaya@gmail.com; Arturo Hernández-Montes; Email: ahernandezmo@chapingo.mx
Corresponding author: Alma L. Saucedo; Email: allesaya@gmail.com; Arturo Hernández-Montes; Email: ahernandezmo@chapingo.mx
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Abstract

Changes in waxed dry cheese during the ripening process, over periods of 7 and 30 days, were analysed using near-infrared spectroscopy (FT-NIR) and mid-infrared spectroscopy (FT-MIR) by attenuated total reflection (ATR). FT-NIR was employed to determine the proximate composition of the cheese (protein, fat, moisture, total solids, and salt content), identifying changes directly associated with the ripening process. FT-MIR data were used to identify spectral bands associated with chemical changes occurring during the cheese maturation. Additionally, chemometric techniques were applied to demonstrate the potential of FT-MIR infrared spectroscopy for cheese differentiation and fingerprint profiling. Subsequently, partial least squares discriminant analysis (PLS-DA) of the FT-MIR spectra was performed, revealing two distinct clusters representing the cheese ripening times. Functional groups related to lipids (–CH2 – and – CH3), proteins (amide bands I and II), and carbohydrates (C–O) were identified, correlating to lipolysis, proteolysis, and lactose catabolism. Infrared spectroscopy in combination with chemometric methods proved to be a robust and reliable tool for monitoring changes during the ripening of waxed dry cheese. The results obtained highlight its usefulness as an alternative approach for the analysis and fingerprinting of traditional Mexican foods, aiming to add value to local products.

Keywords

dairy productspartial least squares discriminant analysisPCAPLS-DAprincipal component analysisproximal composition

Information

Type
Research Article
Information
Journal of Dairy Research , First View , pp. 1 - 10
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation.

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References

Andrade, J, Pereira, CG, Ranquine, T, Azarias, CA, Bell, MJV and De Carvalho Dos Anjos, V (2018) Long-term ripening evaluation of ewes’ cheeses by Fourier-transformed infrared spectroscopy under real industrial conditions. Journal of Spectroscopy 1381864(1), 1–9. doi:10.1155/2018/1381864.CrossRefGoogle Scholar
Ayvaz, H, Mortas, M, Dogan, MA, Atan, M, Yildiz Tiryaki, G and Karagul Yuceer, Y (2021) Near- and mid-infrared determination of some quality parameters of cheese manufactured from the mixture of different milk species. Journal of Food Science and Technology 58(10), 3981–3992. doi:10.1007/s13197-020-04861-0.CrossRefGoogle ScholarPubMed
Barth, A (2007) Infrared spectroscopy of proteins. Biochimica Et Biophysica Acta - Bioenergetics 1767(9), 1073–1101. doi:10.1016/j.bbabio.2007.06.004.CrossRefGoogle ScholarPubMed
Beresford, T and Williams, A (2004) The Microbiology of Cheese Ripening. Fox, PF, McSweeney, PLH, Cogan, TM and Guinee, TP (eds.), Cheese: chemistry, Physics and Microbiology. Academic Press, London, UK, Vol. 1, pp. 227–317. 10.1016/S1874-558X(04)80071-X.Google Scholar
Bittante, G, Patel, N, Cecchinato, A and Berzaghi, P (2022) Invited review: a comprehensive review of visible and near-infrared spectroscopy for predicting the chemical composition of cheese. Journal of Dairy Science 105(3), 1817–1836. doi:10.3168/jds.2021-20640.CrossRefGoogle ScholarPubMed
Califano, AN and Bevilacqua, AE (2000) Multivariate analysis of the organic acids content of gouda type cheese during ripening. Journal of Food Composition and Analysis 13(6), 949–960. doi:10.1006/jfca.2000.0930.CrossRefGoogle Scholar
Canadian Institutes for Health Research. (2024). MetaboAnalyst 6.0. Available at https://www.metaboanalyst.ca/home.xhtml (accessed 5 July 2024).Google Scholar
Cardin, M, Cardazzo, B, Mounier, J, Novelli, E, Coton, M and Coton, E (2022) Authenticity and typicity of traditional cheeses: a review on geographical origin authentication methods. Foods 11(21), 1–24. doi:10.3390/foods11213379.CrossRefGoogle ScholarPubMed
Cardin, M, Mounier, J, Coton, E, Cardazzo, B, Perini, M, Bertoldi, D, Pianezze, S, Segato, S, Di Camillo, B, Cappellato, M, Coton, M, Carraro, L, Currò, S, Lucchini, R, Mohammadpour, H and Novelli, E (2024) Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling. Food Research International 178, 11–18. doi:10.1016/j.foodres.2024.113975.CrossRefGoogle ScholarPubMed
Castro-González, NP, Calderón-Sánchez, F, Castro de Jesús, J, Moreno-Rojas, R, Tamariz-Flores, JV, Pérez-Sato, M and Soní-Guillermo, E (2018) Heavy metals in cow's milk and cheese produced in areas irrigated with waste water in Puebla, Mexico. Food Additives and Contaminants: Part B 11(1), 33–36. doi:10.1080/19393210.2017.1397060.CrossRefGoogle ScholarPubMed
Das, C, Chowdhury, BN, Chakraborty, S, Sikdar, S, Saha, R, Mukherjee, A, Karmakar, A and Chattopadhyay, S (2021) A diagrammatic approach of impedimetric phase angle-modulus sensing for identification and quantification of various polar and non-polar/ionic adulterants in milk. LWT 136, 110347. doi:10.1016/j.lwt.2020.110347.CrossRefGoogle Scholar
De Jesus, JC, Silva, GJ, Gonçalves, BH, De Souza, MR, Santos, LS and Ferrão, SPB (2020) Quick identification of the time of maturation of artisanal minas cheese by ftir-ATR spectroscopy and multivariate techniques. Journal of the Brazilian Chemical Society 31(10), 2000–2011. doi:10.21577/0103-5053.20200100.Google Scholar
Dewantier, GR, Torley, PJ and Blanch, EW (2023) Identifying chemical differences in cheddar cheese based on maturity level and manufacturer using vibrational spectroscopy and chemometrics. Molecules 28(24), 8051. doi:10.3390/molecules28248051.CrossRefGoogle Scholar
Di Donato, F, Biancolillo, A, Foschi, M and D'Archivio, AA and July (2022) Application of SPORT algorithm on ATR-FTIR data: a rapid and green tool for the characterization and discrimination of three typical Italian Pecorino cheeses. Journal of Food Composition and Analysis 114, 104784. doi:10.1016/j.jfca.2022.104784.CrossRefGoogle Scholar
Fattahi, SH, Kazemi, A, Khojastehnazhand, M, Roostaei, M and Mahmoudi, A (2024) The classification of Iranian wheat flour varieties using FT-MIR spectroscopy and chemometrics methods. Expert Systems with Applications 239, 122175. doi:10.1016/j.eswa.2023.122175.CrossRefGoogle Scholar
Foschi, M, Biancolillo, A, Reale, S, Poles, F and D'Archivio, AA and September 2024 (2025) Classification of “Ricotta” whey cheese from different milk and Designation of Origin-protected samples through infrared spectroscopy and chemometric analysis. Journal of Food Composition and Analysis 138, 107019. doi:10.1016/j.jfca.2024.107019.CrossRefGoogle Scholar
Fox, PF, Guinee, TP, Cogan, TM and McSweeney, PLH (2017) Chemistry of Milk Constituents. In Fundamentals of Cheese Science. Springer, New York, US, pp. 71–104. doi:10.1007/978-1-4899-7681-9_4CrossRefGoogle Scholar
Gan, HH, Yan, B, Linforth, RST and Fisk, ID (2016) Development and validation of an APCI-MS/GC-MS approach for the classification and prediction of Cheddar cheese maturity. Food Chemistry 190, 442–447. doi:10.1016/j.foodchem.2015.05.096.CrossRefGoogle ScholarPubMed
González-Córdova, AF, Yescas, C, Ortiz-Estrada, ÁM, De la Rosa-alcaraz, MDLÁ, Hernández-Mendoza, A and Vallejo-Cordoba, B (2016) Invited review: artisanal Mexican cheeses. Journal of Dairy Science 99(5), pp. 3250–3262. doi:10.3168/jds.2015-10103.CrossRefGoogle ScholarPubMed
Guinee, TP and Fox, PF (2017) Salt in cheese: physical, chemical and biological aspects. Cheese: chemistry, Physics and Microbiology: fourth Edition. Elsevier Inc, Vol. 1, Academic Press, London, UK. pp. 317–375. doi:10.1016/B978-0-12-417012-4.00013-2.Google Scholar
Herman-Lara, E, Bolívar-Moreno, D, Toledo-Lopez, VM, Cuevas-Glory, LF, Lope-Navarrete, MC, Barron-Zambrano, JA, Díaz-Rivera, P and Ramírez-Rivera, EDJ (2019) Minerals multi-element analysis and its relationship with geographical origin of artisanal Mexican goat cheeses. Food Science and Technology (Brazil) 39, 517–525. doi:10.1590/fst.23918.CrossRefGoogle Scholar
Jo, Y, Benoist, DM, Ameerally, A and Drake, MA (2018) Sensory and chemical properties of Gouda cheese. Journal of Dairy Science 101(3), 1967–1989. doi:10.3168/jds.2017-13637.CrossRefGoogle ScholarPubMed
Kaczyński, ŁK (2024) Analysis of water activity and gloss of stored goat cheeses according to consumer preferences and tastes. Foods 13(23), 3789. doi:10.3390/foods13233789.CrossRefGoogle ScholarPubMed
Karamoko, G and Karoui, R (2024) Physicochemical, rheology, and mid-infrared spectroscopy techniques for the characterization of artisanal and industrial maroilles cheeses. Foods 13(3086), 1–17.10.3390/foods13193086CrossRefGoogle ScholarPubMed
Khalighi, S, Ma, L, Ren, S and Varveri, A and August (2024) Evaluating the impact of data pre-processing methods on classification of ATR-FTIR spectra of bituminous binders. Fuel 376, 132701. doi:10.1016/j.fuel.2024.132701.CrossRefGoogle Scholar
Lei, T, Lin, XH and Sun, DW (2019) Rapid classification of commercial Cheddar cheeses from different brands using PLSDA, LDA and SPA–LDA models built by hyperspectral data. Journal of Food Measurement and Characterization 13, 3119–3129. doi:10.1007/s11694-019-00234-0.CrossRefGoogle Scholar
Maestrello, V, Solovyev, P, Stroppa, A, Bontempo, L and Franceschi, P and January (2024) 1H NMR profiling and chemometric analysis for ripening and production characterization of Grana Padano cheese. Food Chemistry 456, 139986. doi:10.1016/j.foodchem.2024.139986.CrossRefGoogle ScholarPubMed
Mamo, A (2017) Cheddar cheese characterization and its biochemical change during ripening.International Journal of Advanced Scientific Research and Management 2(5), 53–59Google Scholar
Margolies, BJ and Barbano, DM (2018) Determination of fat, protein, moisture, and salt content of Cheddar cheese using mid-infrared transmittance spectroscopy. Journal of Dairy Science 101(2), 924–933. doi:10.3168/jds.2017-13431.CrossRefGoogle ScholarPubMed
Martín-del-Campo, ST, Picque, D, Cosío-Ramírez, R and Corrieu, G (2007) Middle infrared spectroscopy characterization of ripening stages of Camembert-type cheeses. International Dairy Journal 17(7), 835–845. doi:10.1016/j.idairyj.2006.10.003.CrossRefGoogle Scholar
Martínez-Aquino, V, Hernández-Montes, A, Hernández-Rodríguez, BE and Santos-Moreno, A (2023) La influencia de los valores humanos en el consumo del queso Seco Encerado del Istmo de Tehuantepec, Oaxaca, y sus significados: el efecto mediador de los atributos tangibles. Acta Universitaria 33(1), 3923. https://doi.org/10.15174.au.2023.3923.CrossRefGoogle Scholar
Medina, S, Perestrelo, R, Silva, P, Pereira, JAM and Câmara, JS (2019) Current trends and recent advances on food authenticity technologies and chemometric approaches. Trends in Food Science and Technology 85, 163–176. doi:10.1016/j.tifs.2019.01.017.CrossRefGoogle Scholar
Mokari, A, Guo, S and Bocklitz, T (2023) Exploring the steps of Infrared (IR) spectral analysis: pre-processing, (classical) data modelling, and deep learning. Molecules 28(19), 1–21. doi:10.3390/molecules28196886.CrossRefGoogle ScholarPubMed
Molle, A, Cipolat-Gotet, C, Stocco, G, Ferragina, A, Berzaghi, P and Summer, A (2024) The use of milk fourier-transform infrared spectra for predicting cheesemaking traits in grana padano protected designation of origin cheese. Journal of Dairy Science 107(4), 1967–1979. doi:10.3168/jds.2023-23827.CrossRefGoogle ScholarPubMed
Özcan Yardım, D and Durak, MZ (2023) Identification of antihypertensive bioactive peptides in the herby and white cheeses produced from different milk types. European Food Research and Technology 249(9), 2265–2272. doi:10.1007/s00217-023-04293-y.CrossRefGoogle Scholar
Sakkas, L, Pappas, CS and Moatsou, G (2021) FT-MIR Analysis of Water-Soluble Extracts during the Ripening of Sheep Milk Cheese with Different Phospholipid Content. Dairy 2(4), 530–541. doi:10.3390/dairy2040042.CrossRefGoogle Scholar
Sardiñas-Valdés, M, García-Galindo, HS, Chay-Canul, AJ, Velázquez-Martínez, JR, Hernández-Becerra, JA and Ochoa-Flores, AA (2021) Ripening changes of the chemical composition, proteolysis, and lipolysis of a hair sheep milk Mexican manchego-style cheese: Effect of nano-emulsified curcumin. Foods 10(7), 1579. doi:10.3390/foods10071579.CrossRefGoogle ScholarPubMed
Silva, LKR, Jesus, JC, Onelli, RRV, Conceição, DG, Santos, LS and Ferrão, SPB (2021) Discriminating coalho cheese by origin through near and middle infrared spectroscopy and analytical measures. discrimination of coalho cheese origin. International Journal of Dairy Technology 74(2), 393–403. doi:10.1111/1471-0307.12767.CrossRefGoogle Scholar
Silva, LKR, Santos, LS and Ferrão, SPB (2022) Application of infrared spectroscopic techniques to cheese authentication: a review. International Journal of Dairy Technology 75(3), 490–512. doi:10.1111/1471-0307.12859.CrossRefGoogle Scholar
Skoog, DA, Holler, FJ and Crouch, SR (2018) Principios de Análisis Instrumental. Skoog, DA, Holler, FJ and Crouch, SR eds., 6a. Cengage Learning, Boston, MA, https://books.google.com.mx/books/about/PRINCIPIOS_DE_ANALISIS_INSTRUMENTAL_7oED.html?id=XkDqwQEACAAJ&redir_esc=y.Google Scholar
Sousa, MJ, Ard, Y and Mcsweeney, PLH (2001) Advances in the study of proteolysis during cheese ripening. International Dairy Journal 11, 327–345.10.1016/S0958-6946(01)00062-0CrossRefGoogle Scholar
Stocco, G, Cipolat-Gotet, C, Ferragina, A, Berzaghi, P and Bittante, G (2019) Accuracy and biases in predicting the chemical and physical traits of many types of cheeses using different visible and near-infrared spectroscopic techniques and spectrum intervals. Journal of Dairy Science 102(11), 9622–9638. doi:10.3168/jds.2019-16770.CrossRefGoogle ScholarPubMed
Sysi-Aho, M, Katajamaa, M, Yetukuri, L and Orešič, M (2007) Normalization method for metabolomics data using optimal selection of multiple internal standards. BMC Bioinformatics 8. doi:10.1186/1471-2105-8-93.CrossRefGoogle ScholarPubMed
Tarapoulouzi, M, Entrenas, JA, Pérez-Marín, D, Pashalidis, I and Theocharis, CR (2024) A preliminary study on determining seasonal variations in halloumi cheese using near-infrared spectroscopy and chemometrics. Processes 12(7). doi:10.3390/pr12071517.CrossRefGoogle Scholar
Thierry, A, Collins, YF, Abeijón Mukdsi, MC, McSweeney, PLH, Wilkinson, MG and Spinnler, HE (2017) Lipolysis and metabolism of fatty acids in cheese. Cheese: chemistry, Physics and Microbiology: fourth Edition. Elsevier Inc, Vol. 1, Elsevier, Amsterdam. pp. 423–444. doi:10.1016/B978-0-12-417012-4.00017-X.Google Scholar
Thodis, P, Kosma, IS, Nesseris, K, Badeka, AV and Kontominas, MG (2023) Evaluation of a New Bulk Packaging Container for the Ripening of Feta Cheese. Foods 12(11), 1–20. doi:10.3390/foods12112176.CrossRefGoogle ScholarPubMed
Torres-Salas, V, Hernández-Montes, A and Hernández-Rodríguez, BE (2023) Análisis sensorial, textural y actividad antioxidante de queso añejo de Zacazonapan durante la maduración. Biotecnia 25(2), 204–213. doi:10.18633/biotecnia.v25i2.1897.CrossRefGoogle Scholar
Torres-Salas, V, Hernández-Rodríguez, BE, Hernández-Montes, A, Castillo, E, Zuleta-Prada, H and Herbert-Pucheta, JE (2021) Solid-state NMR spectroscopy for disentangling structural and motional features of lyophilized ripened cheese water-soluble extracts related to antimicrobial activity. Food Chemistry 334, 127603. doi:10.1016/j.foodchem.2020.127603.CrossRefGoogle ScholarPubMed
Valletta, M, Ragucci, S, Landi, N, Di Maro, A, Pedone, PV, Russo, R and Chambery, A (2021) Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment. Food Chemistry 365, 130456. doi:10.1016/j.foodchem.2021.130456.CrossRefGoogle ScholarPubMed
Vásquez, N, Magán, C, Oblitas, J, Chuquizuta, T, Avila-George, H and Castro, W (2018) Comparison between artificial neural network and partial least squares regression models for hardness modeling during the ripening process of Swiss-type cheese using spectral profiles. Journal of Food Engineering 219, 8–15. doi:10.1016/j.jfoodeng.2017.09.008.CrossRefGoogle Scholar
Visconti, LG, Diniz, PHGD, de Sousa Fernandes, DD, Rodriguez, MS and Di Anibal, CV and July (2024) Authentication of grated hard cheeses and quantification of adulteration by FT-NIR spectroscopy and multivariate analysis. International Dairy Journal 158, 106035. doi:10.1016/j.idairyj.2024.106035.CrossRefGoogle Scholar
Westerhuis, JA, Hoefsloot, HCJ, Smit, S, Vis, DJ, Smilde, AK, Velzen, EJJ, Duijnhoven, JPM and Dorsten, FA (2008) Assessment of PLSDA cross validation. Metabolomics 4(1), 81–89. doi:10.1007/s11306-007-0099-6.CrossRefGoogle Scholar
Worley, B and Powers, R (2016) PCA as a Practical Indicator of OPLS-DA Model Reliability. Current Metabolomics 4(2), 97–103. doi:10.2174/2213235x04666160613122429.CrossRefGoogle ScholarPubMed
Xu, S, Bai, C, Chen, Y, Yu, L, Wu, W and Hu, K (2024) Comparing univariate filtration preceding and succeeding PLS-DA analysis on the differential variables/metabolites identified from untargeted LC-MS metabolomics data. Analytica Chimica Acta, 1287(December 2023), 342103. 10.1016/j.aca.2023.342103.10.1016/j.aca.2023.342103CrossRefGoogle ScholarPubMed
Yaman, H, Aykas, DP, Jiménez-Flores, R and Rodriguez-Saona, LE (2022) Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers. Journal of Dairy Science 105(1), 40–55. doi:10.3168/jds.2021-20313.CrossRefGoogle ScholarPubMed
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