Relationship between the dynamics of volatile aroma compounds and microbial succession during the ripening of raw ewe milk-derived Idiazabal cheese

Current Research in Food Science 6 (2023) 100425 Available online 22 December 2022 2665-9271/© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Relationship between the dynamics of volatile aroma compounds and microbial succession during the ripening of raw ewe milk-derived Idiazabal cheese Gorka Santamarina-García a , * , Gustavo Amores a , Igor Hern´ andez a , Lara Mor´ an b , Luis Javier R. Barr´ on b , Mailo Virto a , ** a Lactiker Research Group, Department of Biochemistry and Molecular Biology, Faculty of Pharmacy, University the Basque Country (UPV/EHU), Paseo de la Universidad 7, 01006, Vitoria-Gasteiz, Spain b Lactiker Research Group, Department of Pharmacy and Food Sciences, Faculty of Pharmacy, University of the Basque Country (UPV/EHU), Paseo de la Universidad 7, 01006, Vitoria-Gasteiz, Spain ARTICLE INFO Keywords: Volatile composition Odour-active compounds Microbiota Correlation analysis O2PLS CCorA ABSTRACT Cheese microbiota contributes to various biochemical processes that lead to the formation of volatile compounds and the development of flavour during ripening. Nonetheless, the role of these microorganisms in volatile aroma compounds production is little understood. This work reports for the first time the dynamics and odour impact of volatile compounds, and their relationship to microbial shifts during the ripening of a raw ewe milk-derived cheese (Idiazabal). By means of SPME-GC-MS, 81 volatile compounds were identified, among which acids predominated, followed by esters, ketones and alcohols. The ripening time influenced the abundance of most volatile compounds, thus the moments of greatest abundance were determined (such as 30–60 days for acids). Through Odour Impact Ratio (OIR) values, esters and acids were reported as the predominant odour-active chemical families, while individually, ethyl hexanoate, ethyl 3-methyl butanoate, ethyl butanoate, butanoic acid or 3-methyl butanal were notable odorants, which would provide fruity, rancid, cheesy or malt odour notes. Using a bidirectional orthogonal partial least squares (O2PLS) approach with Spearman’s correlations, 12 bacterial genera were reported as key bacteria for the volatile and aromatic composition of Idiazabal cheese, namely Psychrobacter, Enterococcus, Brevibacterium, Streptococcus, Leuconostoc, Chromohalobacter, Chryseobacterium, Carnobacterium, Lactococcus, Obesumbacterium, Stenotrophomonas and Flavobacterium. Non-starter lactic acid bacteria (NSLAB) were highly related to the formation of certain acids, esters and alcohols, such as 3-hexenoic acid, ethyl butanoate or 1-butanol. On the other hand, the starter LAB (SLAB) was related to particular ketones production, specifically 3-hydroxy-2-butanone; and environmental and/or non-desirable bacteria to certain ketones, hydrocarbons and sulphur compounds formation, such as 2-propanone, t-3-octene and dimethyl sulphone. Additionally, the SLAB Lactococcus and Psychrobacter, Brevibacterium and Chromohalobacter were described as having a negative effect on aroma development caused by NSLAB and vice versa. These results provide novel knowledge to help understand the aroma formation in a raw ewe milk-derived cheese. 1. Introduction Idiazabal cheese is a traditional semi-hard or hard cheese from the Basque Country (southwestern Europe), which is manufactured from raw milk of Latxa and/or Carranzana autochthonous breed sheep. Its production is regulated by its Protected Designation of Origin (PDO) since 1996 (Official Journal of the European Communities, 1996). The Idiazabal cheese making process is strictly regulated and establishes a minimum ripening time of 60 days (Boletín Oficial del Estado, 1993). Nonetheless, producers may employ different flock management and cheese making practices that, in turn, affect the quality of the milk and final cheese. The most notable differences are related to the flock * Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (G. Santamarina-García), [email protected] (G. Amores), [email protected] (I. Hern´ andez), [email protected] (L. Mor´ an), [email protected] (L.J.R. Barr´ on), [email protected] (M. Virto). Contents lists available at ScienceDirect Current Research in Food Science journal homepage: www.sciencedirect.com/journal/current-research-in-food-science https://doi.org/10.1016/j.crfs.2022.100425 Received 12 September 2022; Received in revised form 10 December 2022; Accepted 21 December 2022 Current Research in Food Science 6 (2023) 100425 2 management and grazing practices, such as valley or mountain grazing (Abilleira et al., 2010a; Valdivielso et al., 2016); the use of artisanal or commercial rennet (Virto et al., 2003) or the technological conditions used for cheese making and ripening (Aldalur et al., 2021). During cheese ripening, various biochemical processes take place that are responsible for the synthesis of volatile compounds and, consequently, flavour development (Fox et al., 2017; Thierry et al., 2017). Volatile compounds originate primarily from three groups of metabolic pathways: the metabolism of residual lactose, lactate and citrate; the lipolysis and subsequent metabolism of the released free fatty acids (FFAs); and the proteolysis and metabolism of the resulting peptides and free amino acids (FAAs) (Le Qu´ er´ e and Buchin, 2022). It has been reported that ripening time affects the volatile composition of Idiazabal cheese (Barron et al., 2005a, 2007). However, these studies only focused on certain time points of ripening and did not comprehensively characterize how volatile chemical families and individual compounds evolve throughout this process. This aspect is of special interest since the presence or absence, abundance and proportions of each compound characterize the type of cheese and its aroma (Le Qu´ er´ e and Buchin, 2022). In fact, the imbalance or excessive concentrations of several compounds have been related to off-flavours (Zabaleta et al., 2016). Moreover, it is generally recognized that not all volatile compounds contribute to cheese aroma (Starowicz, 2021), that is to say, not all are odour-active compounds (Fox et al., 2017; Natrella et al., 2020). Despite the large work done to elucidate the flavour and key aromatic compounds of Idiazabal cheese (Barron et al., 2005a, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016), it is unknown how the odour-impact of volatile compounds evolve during ripening. Cheese microbiota contributes to numerous biochemical reactions involved in the formation of flavour compounds (Bertuzzi et al., 2018; Le Qu´ er´ e and Buchin, 2022) and, indeed, has been described as responsible for the particular sensory properties of raw milk cheeses, such as Manchego or Erronkari/Roncal (Ballesteros et al., 2006). The microbiota of Idiazabal cheese has recently been characterized by means of high-throughput sequencing (HTS) (Santamarina-García et al., 2022a), allowing a better understanding of microbial communities than culture-based methods (Yeluri Jonnala et al., 2018). Overall, it has been observed that the ripening time modulates the bacterial composition. Specifically, the starter LAB (SLAB) (Lactococcus) predominates up to 30 or 60 days and then, non-starter LAB (NSLAB) (Lactobacillus, Leuconostoc, Enterococcus, Streptococcus and Carnobacterium) proliferate, while the relative abundance of non-desirable and/or environmental bacteria is reduced (such as Pseudomonas, Staphylococcus or Chromohalobacter). Moreover, bacterial composition differs largely among producers and several bacterial genera not reported previously in any raw ewe milk and derived cheeses have been identified (such as Buttiauxella or Obesumbacterium) (Santamarina-García et al., 2022a). In recent times, several studies that attempt to elucidate the relationship between microbial communities and volatile compounds formation in fermented products have been published (Zhong et al., 2021; Xia et al., 2022). However, few studies have focused on cheese (Zheng et al., 2018; Chen et al., 2021a) and information on raw ewe milk-derived cheeses is scarce (Cardinali et al., 2021). In addition, although the aim of these studies was to understand the association between microbial communities and the aroma formation in fermented products, only one work has analysed the correlation to odour-active volatile compounds in fermented milk (Xia et al., 2021). In order to elucidate such correlations, complex chemometric approaches are needed and the multivariate bidirectional orthogonal partial least squares (O2PLS) (Trygg and Wold, 2003) is one of the most useful approaches (Bouhaddani et al., 2016). Nonetheless, its combination with other parameters, such as correlation coefficients, is the most appropriate approach (Galindo-Prieto et al., 2014). Therefore, this study aimed to (1) characterize how volatile compounds and their odour impact evolve during the ripening of raw ewe milk-derived Idiazabal cheese, in order to (2) investigate how they relate to shifts during ripening of the unique microbiota found in this PDO cheese and (3) highlight the relevance of appropriate advanced statistical approaches to obtain insights and improve cheese quality. Moreover, the potential differences among producers producing the same type of cheese were also analysed. To the best of our knowledge, no such a comprehensive study has been conducted to date on any type of cheese. 2. Materials and methods 2.1. Cheese sampling Four artisanal Idiazabal PDO cheese producers (identified as A, B, C and D) were selected for the sampling. Idiazabal cheeses were produced from raw milk of Latxa sheep, each producer employing the milk of its own flock and following the specifications issued by Idiazabal Designation of Origin Regulatory Board (Boletín Oficial del Estado, 1993). Briefly, the milk was tempered to 25 ◦C and the mesophilic lyophilized starter culture Choozit MM 100 LYO 50 DCU (mixture of Lactococcus lactis subsp. lactis, Lactococcus lactis subsp. cremoris and Lactococcus lactis subsp. lactis biovar. diacetylactis) (DuPont NHIB Ib´ erica S.L., Barcelona, Spain) was added. Milk was coagulated using artisanal rennet or commercial rennet NATUREN® 195 Premium (Chr. Hansen Holding A/S, Hørsholm, Denmark). Cheese ripening was carried out in chambers maintained at 80–95% relative humidity and 8–14 ◦C temperature. Cheese samples for analysis were collected in duplicate at six time points during ripening (1, 7, 14, 30, 60 and 120 days) (n =48). Samples were collected and transported to the laboratory under refrigerated conditions (3 ◦C) and then stored in a freezer (−80 ◦C). Before analysis, cheese samples were defrosted for 24 h at 5 ◦C and kept at room temperature for 1 h. 2.2. Solid-phase microextraction (SPME) methodology The preparation of Idiazabal cheese samples and the SPME procedure was carried out as previously described (Valdivielso et al., 2016). Briefly, removing the rind, 15 g of cheese were ground together with 20 g of anhydrous Na 2 SO 4 (reagent grade, Scharlab, Barcelona, Spain). Afterwards, 5 μ L of cyclohexanone (0.5 μ g/L) (≥99.5%, Sigma-Aldrich, Madrid, Spain) were added as internal standard (IS) solution and it was re-homogenized. The extraction of the volatile compounds was carried out by adding 2.5 g of the aforementioned mixture to a 10 mL amber vial (Agilent Technologies). The vials were sealed with a PTFE septa and a steel magnetic cap (18 mm PTFE/SIL, Agilent Technologies) prior to placing them in the sample tray at room temperature for analysis. SPME procedure was carried out employing a PAL RSI 85 autosampler (CTC CombiPAL, Zwingen, Switzerland) equipped with a temperature-controlled air incubator. After 15 min of pre-equilibration time at 60 ◦C, volatile compounds were trapped onto a 50/30 μ m DVB/Carboxen/PDMS fibre (57298-U, Supelco, Madrid, Spain) at 60 ◦C for 30 min. 2.3. Gas chromatography–mass spectrometry (GC-MS) analysis Volatile compounds were analysed in a 7820A Gas Chromatograph system, equipped with a split/splitless injector and coupled to a 5975 series MS detector (Agilent Technologies), essentially as previously described (Barron et al., 2005b). Volatile compounds were desorbed from the fibre in the front injection port for 10 min at 240 ◦C in splitless mode (split valve was opened at 200 mL/min after 10 min of the injection). Then, volatile compounds were separated in a Supelcowax-10 fused silica capillary column (59.5 m length, 0.25 mm i.d.; 0.25 μ m film thickness) (Supelco, Madrid, Spain) and helium (99.999% purity, Air liquid, Madrid, Spain) was employed as the carrier gas at a constant pressure of 16 psi. Oven was held at 40 ◦C for 10 min, then raised at a rate of 5 ◦C/min until 110 ◦C, increased again at 10 ◦C/min until 240 ◦C, G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 3 and finally held at 240 ◦C for 15 min. Volatile compounds were then transferred to the MS detector through a transfer line at 280 ◦C and MS detector operated at 150 ◦C in full scan mode with 70 eV as total ion current. The chromatographic data obtained were analysed with MSD ChemStation Data Analysis version 5.52 (Agilent Technologies). Volatile compounds were tentatively identified by comparing their mass spectra (match factor >800) with those of the National Institute of Standards and Technology spectra library (NIST version 2.0, Gaithersburg, USA). Mean linear retention index (LRI) value of each chromatographic peak was calculated from the analysis of each Idiazabal cheese sample (4 replicates) and the saturated alkanes standard mixture (3 replicates ×2 times through the experiment) (certified reference material 49452-u, C7-C40, Sigma-Aldrich). Then, positive identification of volatile compounds was carried out by comparing the LRI and mass spectra with those of commercially available high purity standards (≥90%, supplied by Sigma-Aldrich and Honeywell Fluka, Madrid, Spain). The limit of detection (LOD) was established at twice the noise (arbitrary units) of the chromatogram. Peak area quantification was carried out by the total ion current (TIC) and the content of volatile compounds was expressed as relative abundance (peak area in arbitrary units relative to the internal standard (IS)), as expressed by the following equation: Volatile relative abundace =peak area IS area ×2,5 g sample weight (g)×100 The mean abundance of the volatile compounds of each cheese sample was obtained from the peak areas (>LOD) of each compound, as long as they were detected in at least two of the four sample replicates. The relative abundance of volatile compounds in cheese samples was expressed as mean ±standard deviation. 2.4. Statistical analysis of volatile composition Different packages and software were employed for data analysis. The IBM SPSS statistical package version 26.0 (IBM SPSS Inc., Chicago, 2019) was used for data preparation and analysis. Kruskal-Wallis analysis of variance with Bonferroni correction was performed in IBM SPSS package to determine the effect of ripening time and producer factors on volatile chemical families and individual compounds. Hierarchical Clustering Analysis (HCA) of volatile compounds was performed using log transformed, when necessary, and Unit Variance (UV) scaled data and plotted into a heat-map with RStudio version 1.3.959 and R version 3.6.3 (R Core Team, 2020) with “gplots” package (Warnes et al., 2020). The aim was to analyse volatile compounds groupings during ripening time. Then, trends along ripening were analysed through a Principal Component Analysis (PCA) using the SIMCA software version 15.0.0.4783 (Umetrics AB, Umeå, Sweden). The number of principal components (PC) was determined by eigenvalues (greater than 2.5) and cross validation. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) was also performed in SIMCA, in order to analyse whether samples differed according to the producer. Variable Influence on Projection (VIP) values and loadings weights were used to analyse the importance of each volatile compound in the model. 2.5. Calculation of Odour Impact Ratio To obtain a measure of the odour impact of each volatile compound detected in Idiazabal cheese samples, Odour Impact Ratio (OIR) was calculated as Abilleira et al. (2010b) described, with minor modifications, and as the following equation expresses: OIR =Volatile relative abundance odour threshold( μ g/L or μ g/kg) Compounds with OIR values greater than 1 indicate that the abundance of the volatile compound was higher than the odour threshold (OT) and thus, were odour-active compounds. OTs are usually calculated in water, however, values could change depending on the matrix (van Gemert, 2011). Therefore, available OT values measured in cheese were taken to avoid the matrix effect (listed in Table 2). 2.6. Correlation between bacterial communities and volatile compounds An HTS analysis was performed to characterize the bacterial communities and the shifts that occur during ripening of the collected Idiazabal cheese samples, as described by Santamarina-García et al. (2022a). Briefly, 10 g of cheese were suspended in 90 mL of 2% (w/v) sterile sodium citrate (pH 8.0), and homogenized six times (each for 20 s ON and 10 s OFF) in a stomacher (Masticator Basic 400; IUL Instruments, K¨ onigswinter, Germany). Then, 1.5 mL of the resulting suspension was centrifuged (8000×g for 10 min at 4 ◦C) and the fat-containing supernatant was discarded. The obtained pellet was resuspended in 600 μ L of sodium citrate, and centrifuged three times (8000×g for 10 min at 4 ◦C). DNA was extracted with the DNeasy Blood & Tissue Kit (Qiagen, Valencia, CA, USA) and the 16S rRNA gene library was prepared using Nextera XT DNA Library Preparation Kit (Illumina Inc., San Diego, CA, USA). The V3–V4 regions of the 16S rRNA gene were amplified by PCR (forward primer: 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′; reverse primer: 5′-GTCTCGTGGGCTCGGAGATGTGTA TAAGAGACAGGACTACHVGGGTATCTAATCC-3′), as described by Klindworth et al. (2013). Then, 16S rRNA gene sequencing was performed on the Illumina MiSeq platform using the MiSeq Reagent Kit v3 (2 ×300 bp) (Illumina Inc.). MiSeq Reporter software was used for quality filtering and trimming of raw reads and taxonomic classification was performed using the MG-RAST web data analysis tool (Meyer et al., 2008), based on the Silva SSU database (Pruesse et al., 2007). Bacterial abundance was presented as relative abundance (%) based on the identified sequences. To study the relationship between the identified bacterial genera and the dynamics of volatile aroma compounds, an O2PLS approach was applied to log transformed, when necessary, and UV scaled data in SIMCA. Main bacterial genera were selected as X-variables and volatile compounds as Y-variables. The model was validated, among others, by R2 and Q2 values, Permutation test or Inner Relation plot. The key bacterial genera for the volatile composition of Idiazabal cheese were identified based on VIP values and loading weights, together with Spearman’s Rank Correlations calculated in SPSS and interpreted in a heat map with an HCA analysis performed in R with “pheatmap” package (Kolde, 2019). The resulted correlations were verified by a Canonical Correlation Analysis (CCorA) multivariate statistical approach performed in R with “vegan” package (Oksanen et al., 2020). 3. Results and discussion 3.1. Changes in volatile composition Table 1 summarizes the average relative abundance of the individual volatile compounds identified during the ripening time of the collected Idiazabal cheese samples from the four producers (A, B, C and D). The average relative abundance percentage of the identified volatile chemical families is reported in Supplementary Table 1. A total of 81 volatile compounds were identified, which could be grouped into seven families according to their chemical structure, namely acids (9 individual acids), alcohols (21), aldehydes (7), ketones (12), esters (24), hydrocarbons (5), sulphur compounds (2) and terpenes (1). Esters and alcohols constituted the highest number of individual compounds, as previously reported for Idiazabal cheese (Barron et al., 2005a, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016), although a higher number of alcohols were identified in the present study. Overall, 18 individual compounds not reported previously in Idiazabal cheese were detected. Compared to the latest works on raw ewe milk-derived cheeses, a greater number of individual compounds have been identified (Gaglio et al., 2019a; Cardinali et al., 2021). Acids were the predominant chemical family (79.5–88.9% of the G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 4 Table 1 Average relative abundance ±standard deviation of individual volatile compounds identified throughout ripening (1, 7, 14, 30, 60 and 120 days) of Idiazabal cheese samples from 4 producers (n =48). ID LRI a Volatile compounds Ripening time (days) b P-value c 1 7 14 30 60 120 RT P Acids C1 1647 Acetic acid d 8.06 ±22.8 353 ±542 ND 24.3 ±36.4 61.6 ±101 120 ±243 NS NS C2 1698 nButanoic acid d 1681 ±1594 6884 ±5928 9289 ±7950 10674 ±6878 12053 ±7633 6624 ±8670 * ** C3 1880 nPentanoic acid d 10.5 ±14.4 55.1 ±50.4 1135 ±3050 4166 ±11566 48.1 ±57.5 428 ±942 NS * C4 1921 nHexanoic acid d 3168 ±2911 12617 ±9968 16782 ±13507 24546 ±15744 25632 ±19485 15567 ±22362 NS *** C5 2067 (E)-3-Hexenoic acid d,f ND ND ND 682 ±1692 196 ±365 2682 ±5030 NS *** C6 2105 nHeptanoic acid d ND 102 ±113 435 ±817 183 ±199 192 ±210 151 ±237 NS ** C7 2192 nOctanoic acid d 1174 ±1231 3727 ±2899 5186 ±4099 7982 ±5158 9623 ±8291 6362 ±7524 * *** C8 2395 nNonanoic acid d ND ND ND ND ND 307 ±617 C9 2396 nDecanoic acid d 490 ±502 1439 ±1119 2185 ±1695 4073 ±2525 4441 ±3872 2959 ±3862 * ** Total straight-chain acids 6532 ±6275 25177 ±20619 35012 ±31119 52331 ±43801 52247 ±40014 35200 ±49486 * *** Alcohols C10 936 Ethanol d 171 ±58.5 696 ±931 743 ±1065 1288 ±2102 443 ±505 145 ±154 NS NS C11 1040 1-Propanol d ND ND ND ND ND 287 ±723 C12 1145 1-Butanol e ND 4.76 ±8.93 10.6 ±19.8 10.6 ±19.6 20.3 ±31.4 22.4 ±24.9 * *** C13 1205 3-Methyl-1-butanol e 7.46 ±15.1 34.1 ±29.8 58.2 ±87.8 52.3 ±55.9 29.5 ±16.7 6.51 ±7.76 * *** C14 1249 1-Pentanol e 7.76 ±6.20 4.60 ±8.55 ND 19.4 ±52.6 ND ND ** NS C15 1351 1-Hexanol e ND ND 8.12 ±15.5 8.69 ±16.1 17.4 ±20.8 26.0 ±20.6 *** NS C16 1482 2-Ethyl-1-hexanol d 9.66 ±7.22 18.2 ±22.2 5.41 ±5.99 62.9 ±147 15.8 ±8.09 6.71 ±9.78 NS * C17 1552 1-Octanol e ND ND ND ND ND 3.15 ±4.24 Total primary alcohols 196 ±87.1 757 ±1001 825 ±1194 1442 ±2393 526 ±582 497 ±945 NS NS C18 1025 2-Butanol e ND ND ND 88.5 ±124 812 ±1102 424 ±334 *** NS C19 1120 2-Pentanol e ND ND ND 1.60 ±2.97 3.41 ±8.25 27.0 ±18.2 *** NS C20 1122 3-Methyl-2-butanol d,f ND ND ND ND 4.41 ±8.43 7.14 ±13.3 NS NS C21 1218 2-Hexanol e ND ND ND ND ND 1.44 ±2.75 C22 1316 2-Heptanol d ND ND ND 30.7 ±82.2 3.73 ±6.99 12.2 ±19.4 * NS C23 1509 2-Nonanol e ND ND ND ND ND 7.29 ±11.4 C24 1640 2,3-Butanediol d ND 27.1 ±76.7 ND 32.1 ±59.6 ND ND NS * C25 1646 Menthol d,f 6.65 ±6.63 13.0 ±10.4 27.5 ±41.2 11.2 ±12.6 ND ND ** ** Total secondary alcohols 6.65 ±6.63 40.1 ±87.1 27.5 ±41.2 164 ±281 823 ±1126 479 ±399 *** NS C26 1352 2-Methyl-3-pentanol d 9.41 ±17.4 ND ND ND ND ND Total tertiary alcohols 9.41 ±17.4 ND ND ND ND ND C27 1115 2-Propen-1-ol d,f ND ND 10.7 ±20.9 26.8 ±49.7 31.8 ±81.4 1.79 ±5.06 NS *** C28 1396 2-Nonen-1-ol d,f 0.497 ±0.921 ND ND ND ND ND C29 1407 (E)-4-Hexen-1-ol d,f ND ND ND ND ND 2.09 ±3.94 C30 1320 6-Heptene-2,4-diol d,f 8.00 ±10.0 8.23 ±18.7 ND ND ND ND ** * Total allyl alcohols 8.50 ±11.0 805 ±18.7 10.7 ±20.9 26.8 ±49.7 31.8 ±81.4 3.88 ±9.01 NS *** Total alcohols 221 ±122 1602 ±1107 863 ±1256 1633 ±2724 1381 ±1789 980 ±1353 * NS Aldehydes C31 1083 Hexanal e ND ND 1.55 ±2.88 ND ND ND C32 1187 Heptanal d 3.62 ±6.94 ND ND ND ND ND C33 1287 Octanal e 0.0911 ±0.258 ND ND ND ND ND C34 1399 Nonanal e 7.93 ±5.03 14.2 ±4.22 15.2 ±4.82 24.2 ±35.2 14.4 ±8.11 9.73 ±12.1 NS NS Total straight-chain aldehydes 11.6 ±12.2 14.2 ±4.22 16.7 ±7.70 24.2 ±35.2 14.4 ±8.11 9.73 ±12.1 NS NS C35 919 3-Methyl-butanal d 2.99 ±5.54 3.96 ±4.83 1.29 ±2.44 2.44 ±4.63 8.40 ±10.8 43.5 ±31.5 *** NS Total branched-chain aldehydes 2.99 ±5.54 3.96 ±4.83 1.29 ±2.44 2.44 ±4.63 8.40 ±10.8 43.5 ±31.5 *** NS C36 1541 Benzaldehyde e ND ND ND 3.90 ±11.0 12.4 ±23.0 1.80 ±2.24 * ** C37 1667 Benzeneacetaldehyde d,f ND ND 7.98 ±15.6 ND ND ND Total aromatic aldehydes ND ND 7.98 ±15.6 3.90 ±11.0 12.4 ±23.0 1.80 ±2.24 NS NS Total aldehydes 14.6 ±17.7 18.2 ±9.05 26.0 ±25.7 30.5 ±50.8 35.2 ±41.9 55.0 ±45.8 * NS Ketones C38 817 2-Propanone d 13.8 ±16.0 13.1 ±16.9 10.6 ±12.6 56.9 ±142 ND ND * *** C39 904 2-Butanone e 2.84 ±5.25 ND 25.2 ±21.3 1962 ±2305 1465 ±1572 243 ±335 *** NS C40 978 2-Pentanone e ND ND ND 107 ±129 57.2 ±77.8 98.9 ±73.9 *** NS (continued on next page) G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 5 Table 1 (continued) ID LRI a Volatile compounds Ripening time (days) b P-value c 1 7 14 30 60 120 RT P C41 1184 2-Heptanone e 17.5 ±9.45 34.6 ±12.7 39.7 ±17.2 163 ±226 82.1 ±60.3 170 ±211 ** * C42 1288 2-Octanone e 1.82 ±2.83 28.4 ±74.6 1.57 ±2.90 22.5 ±57.0 1.92 ±3.82 3.28 ±6.14 NS *** C43 1392 2-Nonanone e 12.4 ±8.40 28.7 ±13.1 34.5 ±20.8 91.0 ±69.7 64.7 ±56.1 99.2 ±111 * * C44 1447 8-Nonen-2-one d ND ND ND ND ND 8.91 ±11.2 C45 1604 2-Undecanone e ND ND 2.72 ±5.07 7.09 ±10.8 6.59 ±7.77 0.716 ±1.35 * NS Total methyl ketones 48.4 ±42.0 105 ±117 114 ±79.8 2409 ±2940 1678 ±1778 624 ±749 *** NS C46 918 (E,E)-6,10-Dimethyl-5,9dodecadien-2-one d,f ND ND ND ND 29.2 ±64.9 ND C47 981 2,3-Butanedione e 60.3 ±72.1 76.9 ±79.1 86.2 ±76.7 24.9 ±46.4 22.7 ±46.6 ND ** ** C48 1292 3-Hydroxy-2-butanone d 349 ±564 477 ±401 533 ±451 380 ±377 179 ±245 66.8 ±110 * *** C49 1367 2-Hydroxy-3-pentanone d,f ND ND 4.69 ±8.77 1.45 ±2.85 ND ND NS ** Total diketones and other ketones 409 ±636 554 ±480 624 ±536 406 ±427 230 ±357 66.8 ±110 * *** Total ketones 457 ±678 659 ±597 738 ±616 2815 ±3367 1908 ±2135 691 ±859 ** * Esters C50 1186 Methyl hexanoate e ND 3.81 ±7.83 3.33 ±6.17 ND ND ND NS ** C51 1187 Methyl 4-methyl pentanoate d,f 2.87 ±5.34 7.40 ±8.64 3.33 ±6.17 ND 3.84 ±7.20 4.53 ±8.66 NS ** Total methyl esters 2.87 ±5.34 11.2 ±16.5 6.66 ±12.3 ND 3.84 ±7.20 4.53 ±8.66 NS ** C52 1038 Ethyl butanoate d 4.32 ±3.12 27.0 ±45.3 53.8 ±97.8 78.3 ±116 62.8 ±81.3 288 ±362 ** ** C53 1055 Ethyl 2-methyl butanoate d ND ND ND ND 1.77 ±3.28 3.11 ±5.75 NS ** C54 1069 Ethyl 3-methyl butanoate d ND ND ND ND 44.2 ±112 33.9 ±65.4 NS ** C55 1134 Ethyl pentanoate e ND ND ND ND 2.12 ±4.92 2.42 ±4.54 NS ** C56 1234 Ethyl hexanoate e 18.7 ±12.0 183 ±267 343 ±554 453 ±584 480 ±647 216 ±270 * * C57 1292 Ethyl hex-4-enoate d,f ND ND ND 7.24 ±14.1 7.70 ±15.1 0.292 ±0.559 NS *** C58 1335 Ethyl heptanoate e ND ND 4.78 ±8.89 5.77 ±10.7 3.86 ±9.01 33.8 ±53.2 NS *** C59 1434 Ethyl octanoate e 5.27 ±3.72 31.7 ±45.9 71.5 ±117 120 ±139 101 ±171 58.3 ±95.9 * ** C60 1537 Ethyl nonanoate d,f ND ND ND ND ND 1.18 ±2.20 C61 1641 Ethyl decanoate d 4.47 ±3.82 20.3 ±24.1 458 ±1275 1002 ±2560 87.9 ±140 320 ±559 ** NS C62 1855 Ethyl dodecanoate d ND ND ND ND 0.640 ±1.80 1291 ±2894 NS * Total ethyl esters 32.7 ±22.7 262 ±383 930 ±2051 1667 ±3424 791 ±1185 2248 ±4312 *** ** C63 1122 Propyl butanoate e ND ND ND ND 3.35 ±8.57 6.74 ±7.88 ** *** C64 1320 Propyl hexanoate e ND ND ND ND 14.6 ±19.6 27.1 ±28.0 *** NS C65 1521 Propyl octanoate e ND ND ND ND ND 5.68 ±8.53 Total propyl esters ND ND ND ND 18.0 ±28.2 39.5 ±44.4 *** NS C66 1218 Butyl butanoate d ND ND ND ND 2.20 ±5.05 2.98 ±3.31 ** * C67 1412 Butyl hexanoate d ND ND ND ND 3.34 ±9.45 7.81 ±7.31 *** NS Total butyl esters ND ND ND ND 5.54 ±14.5 10.8 ±10.6 *** NS C68 1267 Pentyl butanoate d,f ND ND 2.11 ±3.90 3.62 ±6.81 2.45 ±5.45 127 ±237 NS *** Total pentyl esters ND ND 2.11 ±3.90 3.62 ±6.81 2.45 ±5.45 127 ±237 NS *** C69 1414 Hexyl hexanoate d ND ND ND ND ND 3.08 ±6.05 Total hexyl esters ND ND ND ND ND 3.08 ±6.05 C70 1131 1-Methylpropyl butanoate d,f ND ND ND ND ND 5.56 ±7.07 C71 1323 2-Methylpropyl hexanoate d ND ND ND ND 11.4 ±22.1 35.5 ±32.4 *** NS C72 1372 2-Propenyl hexanoate d ND ND ND ND 2.54 ±5.47 0.485 ±0.900 NS ** C73 1461 3-Methylbutyl hexanoate d,f ND ND ND ND 1.55 ±3.49 40.2 ±74.8 NS ** Total branched-alkyl esters ND ND ND ND 15.5 ±31.0 81.7 ±115 *** NS Total esters 35.6 ±28.0 273 ±400 939 ±2067 1671 ±3431 836 ±1271 2515 ±4734 *** ** Hydrocarbons C74 700 Heptane e 7.46 ±17.2 13.0 ±17.6 7.10 ±17.2 11.9 ±14.2 5.45 ±15.4 ND NS NS Total saturated hydrocarbons 7.46 ±17.2 13.0 ±17.6 7.10 ±17.2 11.9 ±14.2 5.45 ±15.4 ND NS NS C75 688 1,3-Pentadiene d ND ND ND ND ND 2.42 ±4.55 C76 837 t-3-Octene d 35.6 ±54.4 35.7 ±44.8 36.9 ±47.0 239 ±621 16.3 ±33.0 17.5 ±33.5 NS *** C77 956 1,3-Octadiene d,f 5.93 ±11.3 7.08 ±13.9 7.50 ±14.7 98.5 ±268 6.71 ±15.3 6.22 ±11.7 NS *** C78 1041 Toluene e 20.2 ±12.2 42.9 ±28.4 24.9 ±19.4 112 ±261 19.9 ±23.5 68.0 ±112 NS NS Total unsaturated hydrocarbons 61.7 ±77.9 85.7 ±87.1 69.3 ±81.2 449 ±1150 42.9 ±71.8 94.1 ±162 NS *** Total hydrocarbons 69.2 ±95.1 98.7 ±105 76.4 ±98.4 461 ±1164 48.4 ±87.2 94.1 ±162 NS *** Sulphur compounds (continued on next page) G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 6 total abundance) (Supplementary Table 1), as observed previously (Barron et al., 2005a, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016), and the highest abundances were found between 30 and 60 days of ripening (P ≤0.05) (Table 1). All the identified acids were straight-chain fatty acids, predominating hexanoic (44.2–51.1% of total acids), butanoic (18.8–27.3%) and octanoic acids (14.8–18.4%). These results agree with previous studies (Barron et al., 2005b, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016). However, 3-hexenoic acid was identified for the first time and no branched-chain acids were detected in this study. Volatile acids also predominate in other raw ewe milk-derived cheeses, such as Vastedda della valle del Belìce cheese, and similar changes during ripening have been reported (Delgado-Martínez et al., 2019; Gaglio et al., 2019a). Straight-chain fatty acids are also abundant in other raw ewe milk-derived cheeses (Gaglio et al., 2019a; Cardinali et al., 2021), although, in some cases, such as in Torta del Casar, acetic acid, branched-chain or long-chain FFAs predominate (Delgado-Martínez et al., 2019). Moreover, clear differences were observed among Idiazabal cheese producers (P ≤0.001). Samples from producer B, who used commercial rennet, showed lower abundance of acids compared to producers A, C and D that used artisanal rennet. This was expected due to the higher pregastric lipase activity of artisanal rennet compared to commercial rennet (Virto et al., 2003) and its sn-3 stereospecificity (Thierry et al., 2017; Amores et al., 2021). Lipoprotein lipase (LPL) from raw milk and microbial lipases and esterases are also important lipolytic agents in raw milk cheeses (Thierry et al., 2017; Le Qu´ er´ e and Buchin, 2022). However, LPL activity is very low in Idiazabal cheese (Ch´ avarri et al., 1998). Esters were the second family in order of importance throughout ripening (0.859–11.3%) (Supplementary Table 1), whose abundance increased until 120 days (P ≤0.001) (Table 1). Ethyl esters predominated (89.4–99.8% of total esters throughout ripening), specifically, decanoic, hexanoic, dodecanoic and butanoic ethyl esters. Moreover, several esters were identified for the first time in Idiazabal cheese, such as methyl 4-methyl pentanoate or pentyl butanoate. Among minor esters, a significant increase was also observed for propyl, butyl and branched-alkyl esters during ripening (P ≤0.01). These results partially agree with previous works in Idiazabal cheese, as far as identified compounds and their abundance are concerned (Barron et al., 2007; Abilleira et al., 2010b; Valdivielso et al., 2016). Compared to other raw ewe milk-derived cheeses, there are notable differences, although ethyl esters have also been described as predominant (Delgado-Martínez et al., 2019; Gaglio et al., 2019a; Cardinali et al., 2021). Significant differences among producers were only observed for methyl esters (P ≤ 0.01), with producers B and C showing the highest abundance; and for ethyl and pentyl esters (P ≤0.01 and P ≤0.001, respectively), for which producer A presented the highest abundance. In general, the presence of esters has been associated to LAB esterase activity (Liu et al., 2004; Bertuzzi et al., 2018) and consequently, the observed differentiation among producers could be related to the different LAB composition. Ketones abundance was remarkable (3.68–7.16%) (Supplementary Table 1), which also changed during ripening time (P ≤0.01) (Table 1). Methyl ketones abundance increased until 30 days and decreased afterwards but remaining predominant, while diketones and other ketones showed the greatest abundance at the beginning of the ripening (Table 1). These results would explain why methyl ketones have been described as predominant in Idiazabal cheese before (Barron et al., 2005a, 2007; Valdivielso et al., 2016). Individually 2-butanone predominated, as observed in previous studies (Barron et al., 2007; Abilleira et al., 2010b; Valdivielso et al., 2016), together with 3-hydroxy-2-butanone that has previously been related to mountain grazing (Valdivielso et al., 2016). Some ketones, such as 2-hydroxy-3-- pentanone or 6,10-dimethyl-5,9-dodecadien-2-one, have not been identified in Idiazabal cheese to date (Table 1). Differences among producers were only observed for diketones and other ketones (P ≤ 0.001), with producers C and D showing the highest abundance. Compared to other raw ewe milk-derived cheeses, there are great Table 1 (continued) ID LRI a Volatile compounds Ripening time (days) b P-value c 1 7 14 30 60 120 RT P C79 746 Dimethyl sulphide e 1.55 ±2.86 ND ND 17.2 ±46.3 ND ND NS ** C80 1934 Dimethyl sulphone d 25.0 ±34.0 8.05 ±15.7 7.41 ±14.0 61.4 ±163 7.76 ±14.5 6.77 ±12.5 NS *** Total sulphur compounds 26.6 ±36.8 8.05 ±15.7 7.41 ±14.0 78.6 ±209 7.76 ±14.5 6.77 ±12.5 NS *** Terpenes C81 1195 D-Limonene e 0.151 ±0.430 1.35 ±3.83 ND 1.02 ±2.89 ND ND NS NS Total terpenes 0.151 ±0.430 1.35 ±3.83 ND 1.02 ±2.89 ND ND NS NS a LRI: linear retention index. b ND: not detected. c RT: ripening time factor effect; P: producer factor effect; NS: P >0.05, *P ≤0.05, **P ≤0.01, ***P ≤0.001. d Tentatively identified volatile compounds. e Positively identified volatile compounds. f Volatile compounds not previously described in Idiazabal cheese. G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 7 differences in the identified ketones and their abundance during ripening (Delgado-Martínez et al., 2019; Gaglio et al., 2019a; Cardinali et al., 2021). Gezginc et al. (2021) have also reported 2-butanone as the most common ketone in Tulum cheese, whereas 2-heptanone, 2-nonanone and hydroxyacetone predominate in Gran Ovino cheese (Gaglio et al., 2019b). Ketones are formed by catabolism of FFAs, involving the oxidation to β-ketoacids and decarboxylation (Fox et al., 2017; Bertuzzi et al., 2018), mainly by mould and fungi (Fox et al., 2017; Le Qu´ er´ e and Buchin, 2022). Alcohols were another abundant chemical family (3.40–5.46%) (Supplementary Table 1), which showed the highest abundance at 30 days of ripening (P ≤0.05) (Table 1). Primary alcohols were remarkable during ripening, although a decrease was observed from 30 to 120 days, when the abundance of secondary alcohols notably increased (Table 1). However, the ripening time effect was only significant for secondary alcohols (P ≤0.001). These results would explain the great abundance of secondary alcohols reported before (Barron et al., 2005a, 2007; Valdivielso et al., 2016). Ethanol and 2-butanol predominated, which partially agrees with previous studies (Barron et al., 2007; Abilleira et al., 2010b) and several alcohols were identified for the first time in Idiazabal cheese, such as 3-methyl-2-butanol or 2-propen-1-ol. Differences among producers were only observed for allyl alcohols (P ≤ 0.001), with producer A presenting the highest abundance. Compared to other raw ewe milk-derived cheeses, the evolution of alcohols and the predominant compounds differ (Fern´ andez-García et al., 2004; Delgado-Martínez et al., 2019; Gaglio et al., 2019a; Cardinali et al., 2021). Gezginc et al. (2021) have also observed ethanol and 2-butanol as predominant in Tulum cheese, while Gaglio et al. (2019b) have reported 1-hexanol in Gran Ovino cheese. Alcohols biosynthesis has been related to lactose metabolism, reduction of carbonyl compounds (Le Qu´ er´ e and Buchin, 2022) or several enzymatic and non-enzymatic reactions from amino acids or methyl ketones (Yvon and Rijnen, 2001; Bertuzzi et al., 2018; Le Qu´ er´ e and Buchin, 2022). Hydrocarbons, sulphur compounds, aldehydes and terpenes were minor compounds (<4%) (Supplementary Table 1), as observed before in Idiazabal cheese (Barron et al., 2005a, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016). However, there are differences compared to other raw ewe milk-derived cheeses (Delgado-Martínez et al., 2019; Gaglio et al., 2019a; Cardinali et al., 2021), such as the high abundance of aromatic hydrocarbons reported for Vastedda della valle del Belìce cheese (Gaglio et al., 2019a). The ripening time only had a significant effect on aldehydes (P ≤0.05) (Table 1), with a predominance of straight-chain aldehydes at 30 days of ripening, aromatic aldehydes at 60 days and branched-chain aldehydes at 120 days. Nevertheless, the ripening time effect was only significant for the relative abundance of branched-chain aldehydes (P ≤0.001) (Table 1). Individually, nonanal and 3-methyl-butanal were abundant, unlike in previous studies in Idiazabal cheese (Barron et al., 2007; Abilleira et al., 2010b; Valdivielso et al., 2016), and benzeneacetaldehyde was identified for the first time. The evolution of aldehydes and the predominant compounds differ for other raw ewe milk-derived cheeses (Fern´ andez-García et al., 2004; Delgado-Martínez et al., 2019; Gaglio et al., 2019a; Cardinali et al., 2021). The presence of straight-chain aldehydes in cheese is related to the autoxidation of unsaturated fatty acids, both free and esterified (Bertuzzi et al., 2018). The presence of branched-chain and aromatic aldehydes, on the other hand, is related to the degradation of amino acids by non-enzymatic or enzymatic reactions by yeast or LAB (Yvon and Rijnen, 2001; Bertuzzi et al., 2018; Le Qu´ er´ e and Buchin, 2022). Anyway, aldehydes are transitory compounds because of their rapid reduction to alcohols or oxidation to acids (Le Qu´ er´ e and Buchin, 2022), which explains the low abundance observed. In addition, it should be noted that among minor compounds, significant differences among producers were observed only for unsaturated hydrocarbons and sulphur compounds (P ≤0.001), with producer B showing the highest abundance in both cases. Overall, the formation of sulphur compounds is related to enzymatic reactions of sulphur-containing amino acids, Fig. 1. “Analysis of volatile composition evolution during ripening (1, 7, 14, 30, 60 and 120 days) of Idiazabal cheese by means of HCA (A) and PCA (scores and loadings plots, B and C respectively) and scores plot of the OPLS-DA model based on the producer (D). Volatile compounds are labeled according to the ID (Table 1). The scale values of the HCA correspond to log transformed and UV scaled data.” G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 8 Table 2 Estimated OIR values throughout ripening time (1, 7, 14, 30, 60 and 120 days) and sensory description of each volatile compound detected in Idiazabal cheese samples (n =48). Volatile compounds OT a OIR b values during ripening (days) Described odour notes References c 1 7 14 30 60 120 Acids Acetic acid 22000 <1 Sour, vinegar, pungent, acid 1, 2, 3 nButanoic acid 50 33.6 138 186 213 241 132 Rancid, cheesy, putrid, sharp, sour, sweat 1, 2, 3 nPentanoic acid 137 <1 <1 8.28 30.4 <1 3.13 Sweat, putrid, sharp, sour, cheesy, burned 1, 3 nHexanoic acid 290 10.9 43.5 57.9 84.6 88.4 53.7 Sweat, sour, pungent, goat, rancid, cheesy, foot, faecal 1, 2, 3 (E)-3-Hexenoic acid – – Pungent, sweat, vinegar, cheesy, green 4, 5 nHeptanoic acid 3000 <1 Sweat, rancid, faecal 2, 3 nOctanoic acid 450 2.61 8.28 11.5 17.7 21.4 14.1 Sweat, goat, soapy, waxy, musty, faecal, dust, cleaner 1, 2, 3 nNonanoic acid 4000 <1 Faecal, burned, fruity 3 nDecanoic acid 10000 <1 Fatty, soapy, dust, waxy, burned 2, 3 Alcohols Ethanol 8 <1 Alcohol, winey, sweet, ethereal 1 1-Propanol 5700 <1 Alcohol, winey, sweet 1 1-Butanol 800 <1 Winey, sweet, fruity, fusel oil 1 3-Methyl-1-butanol 250 <1 Alcohol, winey, fruity, burned, herbal 1, 3 1-Pentanol 4000 <1 Alcohol, sharp, harsh 1 1-Hexanol 50 <1 Winey, oily, flower, fruity, 1, 2 2-Ethyl-1-hexanol 830 <1 Green, citrus, floral, oily, sweet 5, 6 1-Octanol 42 <1 Fatty, waxy, citrus, oily, walnut, moss, chemical, metal, burned 7, 8 2-Butanol 59 <1 <1 <1 1.50 13.8 7.19 Winey, alcohol, sweet, fruity, fusel oil 1, 2 2-Pentanol 41 <1 Alcohol, slightly green, winey, fruity 1, 2 3-Methyl-2-butanol 420 <1 Fruity 5 2-Hexanol 82 <1 Herbal, green, chemical, winey, fruity, fatty, terpenic, cauliflower 5, 9 2-Heptanol 70 <1 Earthy, sweet, fruity, oily, green, herbal 1, 2, 3 2-Nonanol 75 <1 Fatty, mild, green, melon, coconut 7, 9, 10 2,3-Butanediol 11000 <1 Fruity 3 Menthol 920 <1 Minty, cooling 11 2-Methyl-3-pentanol 420 <1 Grilled, bread 3 2-Propen-1-ol 5000 <1 Pungent, mustard 5 2-Nonen-1-ol 130 <1 Green, fatty, melon 5 (E)-4-Hexen-1-ol 100 <1 Green, herbal, musty, tomato 5 6-Heptene-2,4-diol – – – Aldehydes Hexanal 5 <1 Green, herbal, sharp 1, 3 Heptanal 3 1.21 <1 <1 <1 <1 <1 Fatty, fruity, soapy, green, waxy, herbal 10, 12, 13, 14, 15 Octanal 1.5 <1 Fruity, green, citrus, fatty, fatty-fruity, lemon 10, 12, 13, 14, 15, 16 Nonanal 10 <1 1.42 1.52 2.42 1.44 <1 Sweet, fatty-floral, floral-waxy, rosy, citrus, peas, plastic 1, 2, 3 3-Methyl-butanal 0.200 15.0 19.8 6.46 12.2 42.0 217 Malt, chocolate, toffee, green 1 Benzaldehyde 325 <1 Almond, cherry stone, burned sugar 7, 14, 17 Benzeneacetaldehyde 5.50 <1 <1 1.45 <1 <1 <1 Floral, honey, daisy, green, violet-like, hyacinth, styrene, rosy, dry fruit, sweet 6, 10, 14, 16, 18, 19 Ketones 2-Propanone 840 <1 Sweet, fruity, ethereal, nauseating 1 2-Butanone 30 <1 <1 <1 65.4 48.8 8.09 Sweet, ethereal, slightly nauseating 1 2-Pentanone 70000 <1 Sweet, fruity, ethereal 1, 2 2-Heptanone 5 3.51 6.92 7.93 32.5 16.4 34.0 Musty, blue cheese, pungent, soapy, flower 1, 2, 3 2-Octanone 41 <1 Fruity, musty, floral, green, herbal, mouldy, humidity, soapy, musty, blue-cheese 6, 8, 9, 10, 18 2-Nonanone 5 2.48 5.75 6.91 18.2 12.9 19.8 Musty, floral, fruity, soapy 1, 2 8-Nonen-2-one – – Blue cheese, fruity baked 6, 8, 10 2-Undecanone 6.2 <1 <1 <1 1.14 1.06 <1 Fruity, herbal 2 (E,E)-6,10-Dimethyl-5,9dodecadien-2-one – – – 2,3-Butanedione 3 20.1 25.6 28.7 8.29 7.56 <1 Buttery, sweet, cream, caramel 7, 10, 12, 13, 14, 15, 16, 20 3-Hydroxy-2-butanone 850 <1 Buttery, flower 1, 3 2-Hydroxy-3-pentanone 2500 <1 Fatty, truffle, earthy, nutty 5, 6, 10 Esters Methyl hexanoate 390 <1 Citrus, pineapple, ethereal 9, 16 Methyl 4-methyl pentanoate – – Strawberry, roasted cocoa 21, 22 Ethyl butanoate 1 4.32 27.0 53.8 78.3 62.8 288 Fruity, apple, pineapple, banana, sweet, flower 1, 2, 3 Ethyl 2-methyl butanoate – – Sweet, fruity 10, 13 Ethyl 3-methyl butanoate 0.1 <1 <1 <1 <1 442 339 Fruity, olive, sweet 2, 3 Ethyl pentanoate 8.7 <1 Fruity, sweet, acid, apple, pineapple, green, berry, tropical 5, 15, 18 Ethyl hexanoate 1 18.7 183 343 453 480 216 Fruity, apple, pineapple, banana, mouldy, flower 1, 2, 3 Ethyl hex-4-enoate – – – Ethyl heptanoate 2.2 <1 <1 2.17 2.62 1.75 15.4 Fruity, pineapple, sweet, banana, berry, cognac and slightly green with a seedy nuance 5, 9, 18 (continued on next page) G. Santamarina-García et al. Current Research in Food Science 6 (2023) 100425 9 mainly methionine, by microorganisms (Fox et al., 2017; Le Qu´ er´ e and Buchin, 2022), while hydrocarbons mainly originate from degradation of carotene (Povolo et al., 2007). Subsequently, the dynamics of volatile compounds during ripening were analysed by multivariate analysis. Through an HCA, the volatile composition was divided into three stages: initial stage (1–14 days), middle stage (30–60 days) and advanced stage (120 days) (Fig. 1A). Acetic and heptanoic acids, methyl esters, most diketones, most straightchain aldehydes and benzeneacetaldehyde, some alcohols (such as 2methyl-3-pentanol or menthol), saturated hydrocarbons and terpenes characterized the initial stage. Most abundant acids, few ethyl esters, most methyl ketones and the rest of diketones, some primary and secondary alcohols, nonanal and benzaldehyde, unsaturated hydrocarbons and sulphur compounds characterized the middle stage. Finally, 3-hexenoic and nonanoic acids, most esters, the rest of primary and secondary alcohols, 3-methyl butanal and 8-nonen-2-one characterized the advanced stage. The characteristic presence of some volatile compounds at the initial and middle stage of ripening would explain why they have either not been identified or have been detected in smaller abundance in previous studies (Barron et al., 2005a, 2007; Abilleira et al., 2010b; Valdivielso et al., 2016). PCA approach confirmed the HCA results (Fig. 1B–C). To study differences in the volatile composition among producers of the Idiazabal cheeses analysed, an OPLS-DA approach was applied. Despite its limitations, the model reported a clear distinction between producers, specifically, between A, B and C-D (Fig. 1D). Octanoic acid, ethyl octanoate or 2-octanone were some of the most important volatile compounds for such differentiation. The observed differentiation could be due to several reasons, such as the type of rennet used (Virto et al., 2003), as mentioned above; or the level of rennet lipase employed, since the higher the level, the greater FFAs release and sensory scores in Idiazabal cheese (Amores et al., 2021). Moreover, the sheep grazing system could also have affected the volatile composition of Idiazabal cheese, since clear differences have been reported in cheeses made from milk from extensive mountain grazing, compared to indoor feeding and part-time grazing sheep (Valdivielso et al., 2016). Finally, cheese making and ripening conditions (De Filippis et al., 2016) or microbial composition (Fox et al., 2017), have also been reported to affect the volatile composition of cheese, although it has not been studied in Idiazabal cheese. 3.2. OIR values It is well known that not all volatile compounds contribute to cheese aroma, mainly due to their OTs (Starowicz, 2021). Therefore, OIR values were calculated to elucidate the key aromatic compounds of Idiazabal cheese (Table 2). Overall, esters and acids showed the highest OIR values during ripening and, consequently, were the most odour-active compounds. Esters OIR values increased as ripening progressed and all the identified odour-active esters were ethyl esters, predominating ethyl 3-methyl butanoate, ethyl butanoate and ethyl hexanoate (Table 2). Therefore, odour-active esters corresponded to predominant esters Table 2 (continued) Volatile compounds OT a OIR b values during ripening (days) Described odour notes References c 1 7 14 30 60 120 Ethyl octanoate 65 <1 <1 1.10 1.85 1.55 <1 Fruity, winey, pineapple, apricot, burned, earthy, flower 1, 2, 3 Ethyl nonanoate 377 <1 Cheesy, fruity 3 Ethyl decanoate 23 <1 <1 19.9 43.6 3.82 13.9 Fruity, winey, fatty, flower, humidity 2, 3 Ethyl dodecanoate 400 <1 <1 <1 <1 <1 3.23 Flower, vanilla 3 Propyl butanoate 124 <1 Fruity, sweet, pineapple, banana 1, 2 Propyl hexanoate – – Fruity, pineapple, blackberry, fatty 1, 2 Propyl octanoate – – Coconut 5 Butyl butanoate 100 <1 Fruity, pineapple, banana, sweet, fatty 1, 2 Butyl hexanoate 700 <1 Flower, fruity, pineapple, mouldy 2, 3 Pentyl butanoate 210 <1 Sweet, fruity, banana, pineapple, cherry, tropical 5 Hexyl hexanoate 6400 <1 Green, sweet, waxy, fruity with tropical and berry notes 5 1-Methylpropyl butanoate – – Sweet, fruity, pineapple, rum, cherry, apple, overripe fruit 5 2-Methylpropyl hexanoate – – Apple 1 2-Propenyl hexanoate 200 <1 Pineapple, fatty-fruity 1 3-Methylbutyl hexanoate 320 <1 Fruity, sweet, pineapple with a slightly pungent sour cheesy note 5 Hydrocarbons Heptane 950 <1 Solvent, sweet-ethereal, diffusive 1 1,3-Pentadiene 2500 <1 Plastic, paint, kerosene 23 t-3-Octene – – Sharp, herbal, leather-like 2 1,3-Octadiene 5600 <1 Woody-moss 13 Toluene 1 20.2 42.9 24.9 112 19.9 68.0 Fruity, sweet-gassy, hydrocarbon 1 Sulphur compounds Dimethyl sulphide 1.2 1.29 <1 <1 14.3 <1 <1 Unpleasant wild radish, cabbage, sulphurous, pomegranate, corn, earthy, rancid 10, 12, 15, 20 Dimethyl sulphone 2.5 10.0 3.22 2.96 24.5 3.10 2.71 Sweet, flower, sulphurous, hot milk, burned 9, 10, 14 Terpenes D-Limonene 70 <1 Grass 3 a OT expressed as μ g/L or μ g/kg. Data are taken from the following: Abilleira et al. (2010b); Wang et al. (2021); Natrella et al. (2020); Sarhir et al. (2021); Majcher and Jele´ n (2011); Kubíckov´ a and Grosch (1998); Attaie (2009); van Gemert (2011). b OIR values calculated as mean relative abundance from 4 producers (A, B, C and D) at each ripening time (1, 7, 14, 30, 60, 120 days)/odour threshold. OIR with values higher than 1 are bold coloured. c Described odour notes taken from: (1) Barron et al. (2005a); (2) Abilleira et al. (2010b); (3) Zabaleta et al. (2016); (4) Cˆ amara et al. (2020); (5) The Good Scents Company Information System (2021); (6) Poveda et al. (2008); (7) Juric et al. (2003); (8) Jung et al. (2013); (9) Moio et al. (2000); (10) Curioni and Bosset (2002); (11) Zhang et al. (2022); (12) Natrella et al. (2020); (13) Sympoura et al. (2009); (14) Wang et al. (2020); (15) Karagul Yuceer et al. (2009); (16) Whetstine et al. (2005); (17) Chen et al. (2021b); (18) Qian and Reineccius (2002); (19) Fox et al. (2017); (20) Boscaini et al. (2003); (21) Campo et al. (2006); (22) Takeoka et al. (1995); (23) Horwood et al. (1981). G. Santamarina-García et al.