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Sensory properties and metabolomic profiles of dry-cured ham during the ripening process
Food Research International 129 (2020) 108850
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Sensory properties and metabolomic profiles of dry-cured ham during the ripening process
T
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Masahiro Sugimotoa,b, , Tetsuya Sugawarac, Shinichi Obiyad, Ayame Enomotoa, Miku Kanekoa, Sana Otaa, Tomoyoshi Sogaa, Masaru Tomitaa a
Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan Research and Development Center for Minimally Invasive Therapies Health Promotion and Preemptive Medicine, Tokyo Medical University, Shinjuku, Tokyo 160-8402, Japan c Yamagata Research Institute of Technology, Shonai Testing Facility, Mikawa, Tagawa, Tsuruoka, Yamagata 997-0321, Japan d Tohoku Ham, Tsuruoka, Yamagata 997-0011, Japan b
A R T I C LE I N FO
A B S T R A C T
Keywords: Dry-cured ham Metabolomics Ripening Sensory evaluation Taste sensor
Dry-cured ham with a long ripening period is a valuable product worldwide. Ripening time is a key determinant of the endogenous metabolites that characterize the flavor and taste of ham products. While various studies have analyzed the relationship between ripening duration and sensory characteristics, no studies have evaluated ham products produced in Japan. Here, we conducted time-course metabolomic profiling, taste sensor-based analyses, and sensory evaluations by non-trained consumers during ripening. Capillary electrophoresis-mass spectrometry was used to quantify non-volatile metabolites, such as amino acids, organic acids, and nucleotides. In an analysis of eight time-points during 680 days of ripening, the highest score for the after-taste of umami was observed on day 540, despite subtle changes in the scores for other properties. The concentrations of aspartic acid and glutamic acid relative to those of total amino acids were the highest at this point. This approach can contribute to the understanding of the relationship between the metabolite profile and ripening duration.
1. Introduction Dry-cured hams treated by long-term ripening are popular worldwide, including in Japan. Dry-cured hams typically have high production costs because of the long length of the ripening-drying stage, which gives the product a profound taste and flavor (Flores, Grimm, Toldrá, & Spanier, 1997). Therefore, chemical changes during ripening have been investigated extensively to understand this process (Jurado, García, Timón, & Carrapiso, 2007; Martin, Antequera, Ventanas, BenitezDonoso, & Cordoba, 2001; Ruiz, Ventanas, Cava, Andres, & Garcia, 1999; Sforza et al., 2006; Zhang et al., 2018). Previous studies have examined the chemical changes in dry-cured ham during the ripening process. Metabolites are key chemical components for characterizing the taste and flavor of ham, and they have been approximately classified into volatile molecules, lipids, and other molecules. As examples of volatile metabolites, methylbutanal increased during the ripening of Iberian dry-cured hams, and the amount of this compound showed a positive correlation with their flavor
intensities (Ruiz et al., 1999). Changes in the volatile hydrocarbon content during ripening of Iberian dry-cured hams and Dahe black pig hams were also analyzed (Narváez-Rivas, Gallardo, & León-Camacho, 2015; Shi, Li, & Huang, 2019). Changes in lipids during the ripening were also reported. The oxidative changes in lipids during each processing step of Iberian ham, e.g., during salting, with various conditions, were analyzed (Andrés, Cava, Ventanas, Muriel, & Ruiz, 2004; Narváez-Rivas et al., 2015). As examples of the relationship between ripening and lipid profiles, changes in the content of phospholipids and free fatty acids, as well as the proportion of polyunsaturated fatty acids in French dry-cured ham were investigated (Buscailhon, Gandemer, & Monin, 1994). The relationship between lipid peroxidation and the texture of Serrano ham under various ripening conditions has been determined (del Olmo, Calzada, & Nuñez, 2016). In addition to these metabolites, the amino acid, peptides, and nucleotide contents in lean ham were shown to contribute to the taste (Gallego, Mora, & Toldrá, 2018; Liu et al., 2019; Perez-Santaescolastica
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Corresponding author at: Institute for Advanced Biosciences, Keio University, 246-2 Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. E-mail addresses: [email protected] (M. Sugimoto), [email protected] (T. Sugawara), [email protected] (S. Obiya), [email protected] (A. Enomoto), [email protected] (M. Kaneko), [email protected] (S. Ota), [email protected] (T. Soga), [email protected] (M. Tomita). https://doi.org/10.1016/j.foodres.2019.108850 Received 4 September 2019; Received in revised form 16 November 2019; Accepted 20 November 2019 Available online 30 November 2019 0963-9969/ © 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. Experimental design. (A) Example of a ham sample at ripening. (B) Part of ham sampled, including the inside round (A), outside round (B), round tip (C), and rump (D). (C) Sampling schedule. Triangles indicate collection points. Samples were analyzed by metabolomics, taste sensor, and chemical analyses. Only metabolomic analysis was conducted at the point indicated by a filled triangle.
The aim of this study was to understand the relationship of the metabolomic profile and ripening duration of dry-cured ham produced in Japan. The demand for dry-cured ham produced by long-duration ripening has increased, increasing the need for commercial production. However, available ingredients and environments differ between regions, such as the Mediterranean region, and thus the production protocol and consumer acceptability should be investigated. We analyzed changes in taste-active metabolites during the ripening process. The sensory characteristics of these samples were analyzed by a taste sensor. We also conducted sensory evaluation tests and metabolite profiling of ham samples produced in Japan, Spain, and Italy to understand their relationships. CE-MS was performed to simultaneously quantify various hydrophilic molecules, such as amino acids, organic acids, peptides, nucleotides, and their intermediate metabolites. The relationships among ripening duration, metabolite profile, and sensory features were analyzed.
et al., 2019). Protein degradation by protease yields taste-active molecules (Degnes, Kvitvang, Haslene-Hox, & Aasen, 2017; LópezPedrouso et al., 2019; Mora, Fraser, & Toldrá, 2013). Dipeptides are generated by the enzymatic action of dipeptidyl peptidases by releasing two amino acids from longer peptides and protein fragments (Sentandreu & Toldrá, 2001). Peptidyl dipeptidases and cathepsin B can also release dipeptides (Toldra, Rico, & Flores, 1993); thus, increases in amino acids confer various flavor and taste properties. The proteolysis showed no effect on total amino acid content while changed the balance of amino acids (Perez-Santaescolastica et al., 2018). During ripening, glycogen and glucose are catabolized, which decreases sweetness, while the concentration of lactate, an end-product of glycolysis, gradually increases (Buscailhon, Touraille, Girard, & Monin, 1995). Decreases in the pH and moisture content change the texture of ham (Garcıa-Rey, Garcıa-Garrido, Quiles-Zafra, Tapiador, & De Castro, 2004). Ripening also changes nucleic acid metabolites; ATP is reduced to ADP and subsequently AMP, while IMP is increased, conferring an umami taste because of the presence of glutamic acids. During long ripening periods, IMP changes to hypoxanthine and inosine, thereby increasing the intensity of bitterness (Hernández-Cázares, Aristoy, & Toldrá, 2011). The harmony of this wide variety of metabolites contributes to the taste and flavor of ham products. Metabolomics, a comprehensive metabolite profiling technology, is a new tool for the quality assessment of foods. For example, nuclear magnetic resonance has been used to analyze various crossbreeds of pigs (Straadt, Aaslyng, & Bertram, 2014) and metabolic patterns in Jinhua ham and Xuanwei ham (Zhang et al., 2018). Volatile compounds and lipids in Jinhua ham at each processing step, e.g., salting and ripening, have also been identified (Zhou & Zhao, 2007). Previously, we utilized capillary electrophoresis-mass spectrometry (CE-MS) to analyze the effect of processing conditions, such as smoking and lactic acid bacteria, on the quality of ham (Sugimoto et al., 2016, 2017). During the ripening process, protein degradation and increased dipeptides and amino acids are frequently observed in various fermented foods (Zhao, Schieber, & Gänzle, 2016), including in dry-cured ham (Degnes et al., 2017; Zhang et al., 2019); however, these previous studies have mostly focused on dry-cured hams produced from the Mediterranean region and China. The demand for commercial production of dry-cured ham in Japan has increased, but no studies using Japanese ingredients and environments have been published.
2. Material and methods 2.1. Ingredients and processing Ham samples were prepared using ingredients available in Japan by following the procedure for preparing Prosciutto ham with some modifications. The rump part is conventionally eliminated from the carcass for Prosciutto, while the rump part of the carcass is not eliminated in Japan. Specific pathogen-free Landrace, Large White, and Duroc (LWD) crossbred pigs were used. These pigs were fed corn, soybean cake, and rice, which contribute to ileal digestibility (Cervantes-Pahm, Liu, & Stein, 2014), and reared in the Shonal region (Yamagata, Japan). Slaughter was conducted when the pigs reached a mass of 110 kg (approximately 6 months). Hog, lard (Mogamigawa farm, Yamagata, Japan), rice flour (JA Tsuruoka, Yamagata, Japan), sea salt (Nihonkaikikaku, Niigata, Japan), and black pepper (Yasuma, Kanagawa, Japan) were used. The ham was prepared as follows: (1) Salting procedure: salt (3% of meat, w/w) was rubbed on the surface of the hog on days 1 and 7, and the samples were then kept in stainless-steel containers at ≤4 °C for 15 days. (2) Drying: the samples were suspended from the ceiling in a ripening room at ≤4 °C for 75 days. (3) Desalting: the samples were desalted in 35 °C water and 2
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ripened for 60 days at ≤4 °C. (4) Lard layering: the sample surfaces were covered with a coating of lard, black pepper, and rice flour. Rice flour, a staple food in Japan, is not typically used to produce Prosciutto ham but was used to give the ham unique characteristics. (5) Ripening: the samples were hung for various durations (Fig. 1A). All processes were conducted in the ham-producing company industry Tohoku Ham (Yamagata, Japan).
sensor (Japan Intelligent Sensor Technology [Insent], Inc., Kanagawa, Japan). Data from the rump were used as a reference, and data from the other parts were normalized against the reference (Exp. 1). Similarly, the data from the samples with 0 days of ripening were used as a reference, and the results for the other samples were normalized against this reference (Exp. 2). The remaining samples (175 g) were used for chemical analyses of moisture, lipids, and NaCl (Japan Food Research Laboratories, 2004). Chemical analyses were conducted in Exp. 2 and Exp. 3 with three samples of each ham.
2.2. Experimental design The following three experiments were conducted.
2.4. Chemical analysis
2.2.1. Effect of part-specific variation on metabolic profiles (Exp. 1) As a preliminary test, four parts, including the rump, outside round, inside round, and round tip, were subjected to metabolomics and taste sensor analyses (Fig. 1B). The samples were collected at 540 days. Three samples were collected from each part, and average concentrations were used.
Moisture was analyzed based on loss during drying, i.e., ham samples were homogenized and mixed with diatomaceous earth, dried at 135 °C for 2 h, and the reduction in dry weight was determined. Lipids were quantified by the Soxhlet extraction method, i.e., ham samples were extracted for 10 h by diethyl ether using a Soxhlet extractor, and the weight of the extracted lipids was determined. NaCl was extracted from the homogenized ham samples with 1% (w/v) hydrochloric acid and quantified using an atomic absorption spectrophotometer (AA7000; Shimadzu, Kyoto, Japan). All measurements were conducted in triplicate. This analysis was conducted as described in Exp. 2.
2.2.2. Effect of ripening duration on metabolic profiles and taste sensor analysis (Exp. 2) Metabolomics analyses of the ham samples were performed in triplicate after 0, 30, 90, 150, 366, 400, 540, and 680 days of ripening. Chemical analysis and taste sensor-based analysis were conducted after 0, 150, 400, 540, and 680 days of ripening (Fig. 1C). Based on the results of Exp. 1, only the outside round part was used in this experiment. For each sample, three samples were collected from each part, and average concentrations were used.
2.5. Metabolomics analyses The sample processing protocol, parameter settings for CE-MS, and processing from raw data to a concentration matrix were performed as described previously, with slight modifications (Sugimoto et al., 2017). Six small pieces (approximately 50 mg × 3 and 200 g × 3) were cut from adjacent parts from each ham sample and immediately frozen at −80 °C for metabolomic and taste sensor analyses, respectively. Briefly, metabolites of each ham sample were extracted by plunging the samples into methanol (500 μL) containing (20 μM each) methionine sulfone, D-camphor-10-sulfonic acid, and 2-(N-morpholino)ethanesulfonic acid as internal standards. The samples were homogenized at 1,500 rpm for 5 min using a cell disruption device (Shake Master Neo, BMS, Tokyo, Japan). Subsequently, 500 μL of chloroform and 200 μL of Milli-Q water (Millipore, Billerica, MA, USA) were added, and the solution was centrifuged at 4,600g for 15 min at 4 °C. The upper aqueous layer (300 μL) was centrifugally filtered (5-kDa cutoff filter, Millipore) at 9,100g for 4 h at 20 °C to remove large molecules. The filtrate (300 μL) was lyophilized and dissolved in 50 μL of Milli-Q water containing reference compounds (200 μmol/L 3-aminopyrrolidine and trimesate). The final solutions were measured by CE-MS in cation and anion modes. CE-MS raw data were analyzed using our proprietary software, MasterHands (Sugimoto, Wong, Hirayama, Soga, & Tomita, 2010), which follows typical data processing flows, including the detection of all possible peaks, elimination of noise and redundant features, and generation of an aligned data matrix with annotated metabolite identities and relative areas (peak areas normalized to those of internal standards) (Sugimoto, Kawakami, Robert, Soga, & Tomita, 2012). Concentrations were calculated using external standards based on the relative area, i.e., the area divided by that of internal standards. The concentration of each metabolite was normalized by the sample weight.
2.2.3. Relationship between metabolic profile and sensory features in various types of hams (Exp. 3) Iberian dry-cured ham traditionally requires at least 18–24 months for ripening (Rodriguez, Nunez, Cordoba, Bermudez, & Asensio, 1996). Here, we compared our produced samples to those produced in 18 and 24 months. Additionally, various commercially available dry-cured hams and our hams produced under different conditions were compared. To compare the produced dry-cured ham in Italy to our ham samples, prosciutto (Galloni, Parma, Italy) was used. As another European ham sample, Jamón serrano (Espuña, Olot, Spain) was also collected. Both of them were ranked higher than various ham samples from Japan in our previous study (Sugimoto et al., 2016). Only one commercial company in Japan follows the procedure for preparing Jamón serrano for the production of ham (Shirakawa., Akita Pref., Japan). This sample was also collected for comparison. To assess the effects of different salt treatments, ham samples were also prepared by 12 months of ripening with pink salt collected from the Himalaya mountains (Japan Salt, Tochigi, Japan) and sea salt. Samples ripened for 18 and 24 months with sea salt were also prepared (Table S1). Samples were labeled based on region, with the labels J and S indicating that the samples were collected from Japan and Spain, respectively. For the samples collected in Japan, the duration of ripening was labeled as 18M for samples aged 18 months, and so on. Two J-12M samples produced with rock salt and sea salt were labeled as J12-M-A and J12-M-B. Jamón serrano-like samples collected in Japan and Prosciutto samples were labeled as JJS and PP, respectively.
2.6. Sensory evaluation by non-trained consumers
2.3. Taste sensor and chemical analyses
Sensory evaluation tests were conducted as described in our previous study (Sugimoto et al., 2016), with slight modifications. The features to be evaluated and scoring method were different. Briefly, a reference sample was provided, and scores of the other samples were evaluated relative to this sample in the previous study, while a hedonic scoring system was used for evaluation of Italian and French ham by non-trained consumers (Cannata et al., 2010) without the use of reference samples. The following 13 features were evaluated.
Approximately 200 g of each sample collected from each ham was crushed using a mixer in two tubes. Next, 100 g of ion-exchanged water was added to 25 g of homogenized samples, and the samples were homogenized again and centrifuged at 9,500g for 20 min. The supernatant was filtered through 2-ply cotton gauze (Model No. 002-2146; Iwatsuki, Tokyo, Japan). The filtrate was analyzed using a SA402B taste 3
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Fig. 2. Time-course results for chemical analysis and taste sensor test (Exp. 2). (A) NaCl, (B) moisture, (C) lipid, and (D) taste sensor results. Panels A, B, and C show averages and standard deviations (n = 3). The scores on day 0 were set as 0 as a reference, and those of the other samples were normalized against this reference. ANOVA and post hoc Dunnett’s multiple comparison tests were used for comparisons between each value (> 0 days) and the value at day 0. All chemical analysis results were significant at P < 0.0001 (ANOVA). ****P < 0.0001, ***P < 0.001, and *P < 0.05.
participants. This analysis was conducted in Exp 3.
(1) Appearance (redness of lean, color gradation of lean, and whiteness of fat) (2) Flavor (3) Taste (sweetness, saltiness, acidity, bitterness, astringency, and umami) (4) Texture (hardness and pleasance on the tongue) (5) Overall evaluation
2.7. Statistical and data analyses One-way analysis of variance (ANOVA) and Bonferroni’s multiple comparison tests were used to evaluate the data obtained in the sensory evaluation tests. The time-course data were assessed by one-way ANOVA and Dunnett’s tests to compare the data from day 1 (as a control) and subsequent days of ripening, where data from days 0 and 150 were used as controls for metabolomic and taste sensor analyses, respectively. Pearson’s correlation coefficients were used to compare the metabolomic profiles between the two ham samples. Clustering was conducted to evaluate the similarity in metabolomic profiles, and the results were visualized as a heatmap. Correlation analyses were conducted using the data obtained in Exp. 3. Two independent analyses using (1) only metabolite concentrations and (2) metabolite concentrations and scores given by the sensory evaluation tests were conducted. P < 0.05 was considered to indicate statistically significant differences. Statistical analyses and data visualization were conducted using XLSTAT (ver. 2014.1.04; Addinsoft, Paris, France), MeV TM4 (Aiello et al., 2011), and GraphPad Prism (ver. 7.03, GraphPad Software, Inc., San Diego, CA, USA). The data are available upon request from the corresponding author.
Scores were determined based on the consumers’ preference using a 5-point scale (1, 2, … and 5), where 3 was optimal, 1 indicated the weakest evaluation, and 5 indicated the strongest evaluation. The items for taste evaluation, e.g., astringency, were selected among the items used for evaluation of meat and pork (Buscailhon et al., 1994). All samples were stored at 4 °C and prepared within 2.5 h prior to evaluation. The samples were served in a blinded manner (Fig. S1), and the order of assessment was not specified considering the bias introduced by the carryover effect. The purpose of the sensory evaluation test in this study was to analyze consumers’ acceptability. Consistency in the overall evaluation score between trained panelists and consumers was reported (Resano, Sanjuan, Cilla, Roncales, & Albisu, 2010). No professional panelists were included; only consumers of various ages and genders participated. The sensory evaluation was conducted in a large classroom. All samples were provided in a blinded manner. Bread without salt (Cracotte) and a bottle of water were provided to dilute the aftertaste between samplings. All participants were non-trained Japanese consumers. The characteristics of the participants are summarized at Table S3. The participants gathered in a large classroom between 16:00 and 18:00, and sensory evaluation was conducted at one time. Scoring sheets were also provided and collected just after the evaluation. The instructions for the evaluation were displayed in front of the
3. Results 3.1. Part-specific variation in metabolomic profiles among meat parts (Exp. 1) Variations in amino acids and organic acids among the samples collected from various parts are depicted in Fig. S2A and Fig. S2B. The 4
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desalting and low-temperature drying (i.e., after 150 days), the concentrations of these metabolites decreased, while those of other amino acids and peptides increased gradually. Among the amino acids, asparagine (Asn), followed by leucine (Leu), isoleucine (Ile), and other amino acids showed increasing trends during the ripening process.
rump showed unique profiles for both amino acids and organic acids. Overall, the concentrations of most amino acids in the rump were lower than those in other parts. Other parts showed similar metabolic profiles. Taste sensor analysis indicated substantial variation in the aftertaste of umami among parts, and the score for the rump was particularly low compared to those for the other parts (Fig. S2C). The other features showed no clear variation. Based on these data, the rump was not used, and the outside round was used for subsequent analyses (Exp. 2 and Exp. 3).
3.3. Sensory evaluation and metabolomic profile of various samples (Exp. 3) 3.3.1. Sensory evaluation scores and sensory scores obtained by the taste sensor for various products A total of 194 non-trained consumers (108 males and 85 females) were enrolled in the evaluation test (Table S3). Tables S4 and S5 summarize the results of sensory evaluation tests. Jamón Serrano from Spain (SJS) and Prosciutto from Italy (PP) showed relatively higher scores than the other samples. For example, the overall score for SJS was significantly higher than those for J-24M and Jamón Serrano-type sample from Japan (JJS) (ANOVA with Bonferroni’s multiple comparison test). Fig. S3 and Table S6 summarize the results of taste sensor analysis. All scores showed significant variation (P < 0.05, ANOVA). The aftertaste of umami showed the largest variation and JJS showed the highest score. Among samples with different ripening durations, samples collected at 540 days (J-18M) showed higher scores than the other samples, including J-12 M-A, J-12-B, and J24-M.
3.2. Effect of ripening duration (Exp. 2) 3.2.1. Time-course of chemical and taste sensor results Time-course data for moisture (Fig. 2A), NaCl (Fig. 2B), and lipids (Fig. 2C) were obtained. Moisture decreased dramatically over 90 days of salting (P < 0.0001, one-way ANOVA with Dunnett’s test) and decreased gradually thereafter. NaCl showed the opposite pattern. Lipids showed a moderate increase and eventually a significant elevation at 400 days (P = 0.0011, one-way ANOVA with Dunnett’s test). Fig. 2D shows a radar chart of the taste sensor results, and Table S2 summarizes the results of statistical analyses. All scores showed significant variation over time (P < 0.0001, one-way ANOVA), except for astringency (P = 0.0463, one-way ANOVA). Differences in a score of ≥ 1 were recognized as sensory differences. Saltiness and, particularly, the aftertaste of umami showed large variations. The saltiness decreased 150 days after desalting and then increased again. The umami aftertaste increased, showing the highest value at 540 days, followed by a decrease.
3.3.2. Comparison of metabolomic profiles among various products Fig. 4 and Table S7 summarize the results of the metabolomic and chemical analyses. SJS and PP, which showed higher overall sensory scores (Fig. 5A), showed higher lipid concentrations than the other samples (Table S7). Metabolomic analyses revealed higher amino acid concentrations, except for Gln, in the samples with the longest ripening time compared to those with shorter ripening times (J-18M and J-12MA). The difference in salt also affected the metabolomic profiles, e.g., J12M-A showed higher concentrations of inosine and Ala-Ala than J-
3.2.2. Time-course of metabolomic profiles during ripening Fig. 3 shows the heatmap of the time-courses of metabolomic profiles. At 0 and 30 days, the concentrations of most metabolites were lower and the concentrations of IMP, GMP, malate, and fumarate were higher than those on subsequent days. Among the amino acids, glutamine (Gln) and cysteine (Cys) showed high concentrations. After
Fig. 3. Time-course analysis of metabolomic profiles (Exp. 2). Each concentration was divided by the average concentration for each metabolite and is shown using a blue-white-red scheme, where red and blue indicate relatively higher and lower values and white indicates the average. Metabolites were grouped according to Pearson correlation-based clustering analysis. Amino acids, organic acids, nucleotides, and peptides are shown in different colors. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 5
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Fig. 4. Heatmap showing metabolomic profiles (Exp. 3). Data were visualized using the method used to generate Fig. 3.
showed no such metabolites. The correlation network among metabolite concentrations is depicted in Fig. 6. The 13 amino acids, fumarate, carnitine, and creatinine showed a large network. Asn, Arg, and serine (Ser) also showed correlations. Other metabolites, such as guanine and ornithine, also showed correlations.
12M-B. SJS and PP showed similar overall profiles, while guanine and ornithine concentrations were higher in the PP samples (Fig. 4).
3.3.3. Correlation analysis (Exp. 3) The correlations among sensory evaluation scores and quantified metabolite concentrations obtained from Exp. 3 are summarized at Table S8. Only correlations showing P < 0.05 are listed. For example, appearance showed various correlated metabolites, while flavor
Fig. 5. Relationship between the scores in the sensory evaluation test and metabolite quantities. (A) Correlations of all quantified metabolites of SJS showing the highest score in overall sensory evaluation. ***P < 0.001. (B) Relative concentrations of Asp and Glu compared to the concentrations of all amino acids (%). C) Relationships between absolute concentrations of guanine, Asp, and Glu. Lines were fit by leastsquares regression. Point size indicates the overall score obtained in the sensory evaluation.
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Fig. 6. Correlation network among quantified metabolites (Exp. 3). The metabolite showing high correlation (R2 > 0.81) was connected. Metabolites with known taste for sweetness, bitterness, umami, and sourness were colored in pink, green, orange, and yellow, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
4. Discussion
longest duration, while J-18M was ranked higher than the other samples with shorter ripening durations, indicating that the balance of amino acids relative to the total amino acid concentration is related to the sensory features. The effects of salt were evaluated for two types of dry-cured ham ripened for 12 months with rock salt (J-12M-A) and sea salt (J-12M-B). The metabolic profile showed that only inosine and AlaAla were higher in J-12M-A, while other metabolites showed similar concentration patterns (Fig. 4). The overall score in the sensory evaluation test was higher for J-12M-A (Table S4), but did not significantly differ from those of the other samples (Table S5). These results indicate that the type of salt used has no significant effects on ham ripening. With respect to the balance of amino acids during ripening, Asp and Glu showed unique patterns and increased up to 540 days, followed by a decrease at 680 days (Fig. 5B). The individual amino acid concentrations increased at 90 days (P < 0.05; ANOVA with Dunnett’s tests) and subsequently increased in a gradual manner (Fig. S4). Briefly, the total concentration of amino acids increased more rapidly between days 540 and 680 compared to the levels of Asp and Gly. Interestingly, these amino acid concentrations showed clear linearity with respect to the guanine concentration (Fig. 5C). The overall sensory evaluation scores for the samples close to the regression lines were relatively high, while those of the samples far from this line, e.g., J-24M, were relatively low (Fig. 5C). The guanine concentration also increased at 90 days (P < 0.05; ANOVA with Dunnett’s tests) and reached a maximum at 540 days (Fig. S4). Inosine (IMP) and Glu are known to enhance the umami characteristic. Sensory analysis revealed the highest value for the aftertaste of umami in J-18M among samples with different ripening durations (J12M-A, J-18M, and J-24M), while umami showed a significant difference among samples. Thus, our data showed a positive correlation between these nucleotides and only the aftertaste of umami. Our method did not measure volatile compounds, although several relationships among free amino acids and flavor have been demonstrated. For example, increased amino acid contents affect bitter flavor (Sforza et al., 2001; Virgili, Schivazappa, Parolari, Bordini, & Degni, 1998). Peptide levels are correlated with flavor formation (HansenMøller, Hinrichsen, & Jacobsen, 1997; Ruiz, 1999). Volatile compounds were generated by the Maillard reaction of Jinhua ham and histidine and lysine among amino acids contributed to the flavor characterization (Zhu et al., 2018). Correlation analyses (Fig. 6) revealed that most amino acids functioned as sources of sweetness, bitterness, sourness, and umami. Asn, Arg, and Ser also showed correlations. Among the dipeptides, only β-Ala-Lys showed a correlation with 3-hydrobutyrate, while their contribution to taste and flavor remain unknown. No metabolites showed a significant correlation with flavor (Table S8). Based
In this study, the relationships among changes in the metabolomic profiles of ham samples and taste were evaluated by taste sensor, consumer acceptability, and metabolomic analyses. Variations in the metabolomic profiles among parts from a ham sample were analyzed (Exp. 1). The inside and outside rounds and round tip showed similar patterns, while the rump showed unique patterns in both metabolite concentrations and sensory test scores (Fig. S2). During the salting process, the top of the rump was treated with salt, and the rump was wider surface of lean (Fig. 1A). The salt concentration is initially higher in drier external zones compared to in the humid inner zone, which subsequently reverses (Arnau, Guerrero, Casademont, & Gou, 1995). One possible reason for this rump-specific bias is the faster chemical process in permeation and faster oxidation compared to in the other zone. Therefore, the outside round zone was analyzed as a representative sample in Exp. 2 and Exp. 3. During the ripening process (Exp. 2), moisture decreased, while lipids and NaCl increased (Fig. 2) in the outside round part. Metabolites during ripening showed moderate increases for each amino acid, except for Gln and Cys. Asn showed the most rapid increase, followed by Leu and Ile. Peptides also showed similar increasing trends during the ripening period (Fig. 3). These monotonic increases can be explained by the degradation of proteins during ripening. SJS, PP, and 7 types of ham produced in Japan were compared by metabolomic analysis and sensory evaluation (Exp. 3). SJS and PP showed lower NaCl and moisture contents and higher lipid concentrations than Japanese ham samples (Table S7). All quantified metabolites in SJS exhibited the highest positive correlation with those of PP (R = 0.9937, P < 0.05, Pearson correlation) and second highest positive correlation with those of J-18 M (R = 0.9936, P < 0.05, Pearson correlation) (Fig. 5A). Interestingly, the three sensory evaluation scores, overall evaluation, umami, and flavor, ranked SJS, PP, and J-18 M within the top three samples (Table S4). Among the metabolites, SJS showed higher concentrations of malate and isocitrate than the other samples (Fig. 4). PP showed higher concentrations of amino acids, such as tryptophan (Trp), aspartic acid (Asp), glycine (Gly), histidine (His), methionine (Met), phenylalanine (Phe), and ornithine. JJS showed similar profiles (Fig. 4). A comparison of six types of Iberian hams revealed that Serrano ham had lower tyrosine (Tyr) and higher Asp contents (Virgili et al., 1999); not only the total concentration of amino acids but also the balance among amino acids contributes to flavor (Zhao et al., 2016). Our data also revealed the highest concentration of amino acids in the ham ripened for the 7
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on our data, estimating flavor characteristics from a single metabolite is difficult. Relative Gln and Asp contents compared to the total concentration of amino acids showed a unique time-course, increasing up to 540 days and decreasing thereafter (Fig. 5B). Such non-monotonic changes in various metabolites have been reported. For example, Ser, Trp, and valine concentrations in dry-cured ham increased up to 15 months and then decreased, although the total amino acids increased monotonically (Degnes et al., 2017). In the comparison of Parma ham samples processed for 450, 570, and 690 days, monosodium glutamate-like and bitter taste monotonically increased, while sour flavors peaked at 570 days (Sforza et al., 2006). The ratio of hypoxanthine to inosine increased up to 5 months, the ratio of creatine to creatinine increased up to 9 months, and both ratios remained constant thereafter during ham ripening (Escudero, Mora, Aristoy, & Toldra, 2011). Creatine and creatinine showed consistent trends, despite variations in the balance of NaCl and KCl over their long ripening periods (Mora, HernandezCazares, Sentandreu, & Toldra, 2010). In our study, the taste sensor results showed the best scores for full-bodied umami at 540 days; the ratio of the amino acids and nucleotide balance may have contributed to this result. This study had several limitations. CE-MS enables the profiling of only hydrophilic metabolites. Other analytical methodologies enables lipids and volatile compound profiling (Domínguez et al., 2019; PérezPalacios & Estévez, 2020; Wang et al., 2018). Integration of the data analyzed by multiple approaches would contribute to comprehensive understanding of the chemical properties of dry-cured hams. Samples of only 50 mg were necessary for the metabolomic analyses; therefore, we collected lean pieces from ham samples. The taste sensor analysis required large pieces (approximately 200 g), which included fat, presumably explaining the discrepancy between the metabolomic profile results and other observations. Here, we utilized a 5-point scale, but a 9-point scale is an alternative method commonly used for consumer acceptance tests (Laureati et al., 2014; Yeu, Lee, & Lee, 2008). Only Japanese consumers were involved in the evaluation test, and differences in sensory assessments by people of different nationalities were reported (Garcia-Gonzalez et al., 2006). Furthermore, ham samples were served in a blinded manner under normal lighting. Various factors affecting consumer acceptability, such as visible characteristics (Morales, Guerrero, Aguiar, Guardia, & Gou, 2013), were not completely eliminated. In addition, randomizing the order of the samples would have reduced bias from the carryover effect.
We utilized Japanese samples as a case study, but a similar approach can be used to analyze the ripening process of any type of ham. CRediT authorship contribution statement Masahiro Sugimoto: Writing - review & editing, Methodology, Formal analysis. Tetsuya Sugawara: Formal analysis, Methodology, Investigation. Shinichi Obiya: Resources. Ayame Enomoto: Visualization. Miku Kaneko: Investigation, Data curation. Sana Ota: Investigation, Data curation. Tomoyoshi Soga: Supervision. Masaru Tomita: Project administration. Acknowledgements This work was supported by a collaborative grant (exploring research seeds) and a grant from Yamagata prefecture and Tsuruoka city. We thank all sensory evaluation contributors. We would like to thank Editage (www.editage.jp) for English language editing. Declarations of Competing Interest None. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.foodres.2019.108850. References Aiello, D., De Luca, D., Gionfriddo, E., Naccarato, A., Napoli, A., Romano, E., ... Tagarelli, A. (2011). Review: Multistage mass spectrometry in quality, safety and origin of foods. European Journal of Mass Spectrometry (Chichester, Eng), 17(1), 1–31. Andrés, A. I., Cava, R., Ventanas, J., Muriel, E., & Ruiz, J. (2004). Lipid oxidative changes throughout the ripening of dry-cured Iberian hams with different salt contents and processing conditions. Food Chemistry, 84(3), 375–381. Arnau, J., Guerrero, L., Casademont, G., & Gou, P. (1995). Physical and chemical changes in different zones of normal and PSE dry cured ham during processing. Food Chemistry, 52(1), 63–69. Buscailhon, S., Berdague, J. L., Bousset, J., Cornet, M., Gandemer, G., Touraille, C., & Monin, G. (1994). Relations between compositional traits and sensory qualities of French dry-cured ham. Meat Science, 37(2), 229–243. Buscailhon, S., Gandemer, G., & Monin, G. (1994). Time-related changes in intramuscular lipids of French dry-cured ham. Meat Science, 37(2), 245–255. Buscailhon, S., Touraille, C., Girard, J., & Monin, G. (1995). Relationships between muscle tissue characteristics and sensory qualities of dry-cured ham. Journal of Muscle Foods, 6(1), 9–22. Cannata, S., Ratti, S., Meteau, K., Mourot, J., Baldini, P., & Corino, C. (2010). Evaluation of different types of dry-cured ham by Italian and French consumers. Meat Science, 84(4), 601–606. Cervantes-Pahm, S. K., Liu, Y., & Stein, H. H. (2014). Comparative digestibility of energy and nutrients and fermentability of dietary fiber in eight cereal grains fed to pigs. Journal of the Science of Food and Agriculture, 94(5), 841–849. Degnes, K. F., Kvitvang, H. F. N., Haslene-Hox, H., & Aasen, I. M. (2017). Changes in the profiles of metabolites originating from protein degradation during ripening of dry cured ham. Food Bioprocess Technology, 10(6), 1122–1130. del Olmo, A., Calzada, J., & Nuñez, M. (2016). Lipolysis, lipid peroxidation and texture of Serrano ham processed under different ripening temperature conditions. International Journal of Food Science and Technology, 51(8), 1793–1800. Domínguez, R., Purriños, L., Pérez-Santaescolástica, C., Pateiro, M., Barba, F. J., Tomasevic, I., ... Lorenzo, J. M. (2019). Characterization of volatile compounds of dry-cured meat products using HS-SPME-GC/MS Technique. Food Analytical Methods, 12(6), 1263–1284. Escudero, E., Mora, L., Aristoy, M. C., & Toldra, F. (2011). Possible biological markers of the time of processing of dry-cured ham. Meat Science, 89(4), 536–539. Flores, M., Grimm, C. C., Toldrá, F., & Spanier, A. M. (1997). Correlations of sensory and volatile compounds of Spanish “Serrano” dry-cured ham as a function of two processing times. Journal of Agriculture and Food Chemistry, 45(6), 2178–2186. Gallego, M., Mora, L., & Toldrá, F. (2018). Differences in peptide oxidation between muscles in 12 months Spanish dry-cured ham. Food Research International, 109, 343–349. Garcia-Gonzalez, D. L., Roncales, P., Cilla, I., Del Rio, S., Poma, J. P., & Aparicio, R. (2006). Interlaboratory evaluation of dry-cured hams (from France and Spain) by assessors from two different nationalities. Meat Science, 73(3), 521–528. Garcıa-Rey, R., Garcıa-Garrido, J., Quiles-Zafra, R., Tapiador, J., & De Castro, M. L. (2004). Relationship between pH before salting and dry-cured ham quality. Meat
5. Conclusion In this study, the effects of ripening duration on the metabolite profile and sensory features of ham were analyzed. The primary purpose of this study was to understand the effect of ripening duration on dry-cured ham produced in Japan. The ham samples were analyzed by CE-MS-based metabolomics, chemical analyses, taste sensor analyses, and sensory evaluations. Part-specific variations revealed unique features of the rump, and thus the outside round part was used for subsequent analyses. The ripening process resulted in a gradual increase in amino acids for up to 680 days. However, samples ripened for 540 days were considered as optimal, as they showed the highest overall evaluation score in sensory evaluation and highest aftertaste of umami in the sensory test. The total concentration of amino acids increased gradually during ripening, while the relative concentrations of Gln and Asn compared to the total amino acid concentration were highest at 540 days, and guanine concentration, nucleotide concentration, and their combination, which enhanced the umami-related characteristics, were also the highest at 540 days. These metabolite changes along with other gradual increases in various amino acids and organic acids contributed to this sensory change. The correlation analysis revealed that various amino acids were correlated with each other and that it is difficult to estimate sensory attributes using only a single metabolite. 8
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dry-cured Iberian ham as affected by the length of the curing process. Meat Science, 52(1), 19–27. Sentandreu, M., & Toldrá, F. (2001). Dipeptidyl peptidase activities along the processing of Serrano dry-cured ham. European Food Research and Technology, 213(2), 83–87. Sforza, S., Galaverna, G., Schivazappa, C., Marchelli, R., Dossena, A., & Virgili, R. (2006). Effect of extended aging of parma dry-cured ham on the content of oligopeptides and free amino acids. Journal of Agriculture and Food Chemistry, 54(25), 9422–9429. Sforza, S., Pigazzani, A., Motti, M., Porta, C., Virgili, R., Galaverna, G., ... Marchelli, R. (2001). Oligopeptides and free amino acids in Parma hams of known cathepsin B activity. Food Chemistry, 75(3), 267–273. Shi, Y., Li, X., & Huang, A. (2019). A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham. Meat Science, 158, 107904. Straadt, I. K., Aaslyng, M. D., & Bertram, H. C. (2014). An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception. Meat Science, 96(2), 719–728. Sugimoto, M., Kawakami, M., Robert, M., Soga, T., & Tomita, M. (2012). Bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis. Current Bioinformatics, 7(1), 96–108. Sugimoto, M., Obiya, S., Kaneko, M., Enomoto, A., Honma, M., Wakayama, M., ... Tomita, M. (2017). Metabolomic profiling as a possible reverse engineering tool for estimating processing conditions of dry-cured hams. Journal of Agriculture and Food Chemistry, 65(2), 402–410. Sugimoto, M., Obiya, S., Kaneko, M., Enomoto, A., Honma, M., Wakayama, M., & Tomita, M. (2016). Simultaneous analysis of consumer variables, acceptability and sensory characteristics of dry-cured ham. Meat Science, 121, 210–215. Sugimoto, M., Wong, D. T., Hirayama, A., Soga, T., & Tomita, M. (2010). Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics, 6(1), 78–95. Toldra, F., Rico, E., & Flores, J. (1993). Cathepsin B, D, H and L activities in the processing of dry-cured ham. Journal of the Science of Food and Agriculture, 62(2), 157–161. Virgili, R., Parolari, G., Bordini, C. S., Schivazappa, C., Cornet, M., & Monin, G. (1999). Free amoni acids and dipeptides in dry-cured ham. Journal of Muscle Foods, 10(2), 119–130. Virgili, R., Schivazappa, C., Parolari, G., Bordini, C. S., & Degni, M. (1998). Proteases in fresh pork muscle and their influence on bitter taste formation in dry-cured ham. Journal of Food Biochemistry, 22(1), 53–63. Wang, W., Feng, X., Zhang, D., Li, B., Sun, B., Tian, H., & Liu, Y. (2018). Analysis of volatile compounds in Chinese dry-cured hams by comprehensive two-dimensional gas chromatography with high-resolution time-of-flight mass spectrometry. Meat Science, 140, 14–25. Yeu, K., Lee, Y., & Lee, S. Y. (2008). Consumer acceptance of an extruded soy-based highprotein breakfast cereal. Journal of Food Science, 73(1), S20–S25. Zhang, J., Ye, Y., Sun, Y., Pan, D., Ou, C., Dang, Y., ... Wang, D. (2018). 1H NMR and multivariate data analysis of the differences of metabolites in five types of dry-cured hams. Food Research International, 113, 140–148. Zhang, J., Yi, Y., Pan, D., Zhou, G., Wang, Y., Dang, Y., ... Cao, J. (2019). (1)H NMR-based metabolomics profiling and taste of boneless dry-cured hams during processing. Food Research International, 122, 114–122. Zhao, C. J., Schieber, A., & Gänzle, M. G. (2016). Formation of taste-active amino acids, amino acid derivatives and peptides in food fermentations–A review. Food Research International, 89, 39–47. Zhou, G. H., & Zhao, G. M. (2007). Biochemical changes during processing of traditional Jinhua ham. Meat Science, 77(1), 114–120. Zhu, C. Z., Zhao, J. L., Tian, W., Liu, Y. X., Li, M. Y., & Zhao, G. M. (2018). Contribution of Histidine and Lysine to the Generation of Volatile Compounds in Jinhua Ham Exposed to Ripening Conditions Via Maillard Reaction. Journal of Food Science, 83(1), 46–52.
Science, 67(4), 625–632. Hansen-Møller, J., Hinrichsen, L., & Jacobsen, T. (1997). Evaluation of peptides generated in Italian-style dry-cured ham during processing. Journal of Agriculture and Food Chemistry, 45(8), 3123–3128. Hernández-Cázares, A. S., Aristoy, M. C., & Toldrá, F. (2011). Nucleotides and their degradation products during processing of dry-cured ham, measured by HPLC and an enzyme sensor. Meat Science, 87(2), 125–129. Japan Food Research Laboratories (2004). Analytical Manual for Standard Tables of Food Composition in Japan (5th ed.). Tokyo: Chuouhoki Publishing in Japanese. Jurado, Á., García, C., Timón, M. L., & Carrapiso, A. I. (2007). Effect of ripening time and rearing system on amino acid-related flavour compounds of Iberian ham. Meat Science, 75(4), 585–594. Laureati, M., Buratti, S., Giovanelli, G., Corazzin, M., Lo Fiego, D. P., & Pagliarini, E. (2014). Characterization and differentiation of Italian Parma, San Daniele and Toscano dry-cured hams: A multi-disciplinary approach. Meat Science, 96(1), 288–294. Liu, S., Wang, G., Xiao, Z., Pu, Y., Ge, C., & Liao, G. (2019). 1H-NMR-based water-soluble low molecular weight compound characterization and free fatty acid composition of five kinds of Yunnan dry-cured hams. LWT, 108, 174–182. López-Pedrouso, M., Pérez-Santaescolástica, C., Franco, D., Carballo, J., Zapata, C., & Lorenzo, J. (2019). Molecular insight into taste and aroma of sliced dry-cured ham induced by protein degradation undergone high-pressure conditions. Food Research International, 122, 635–642. Martin, L., Antequera, T., Ventanas, J., Benitez-Donoso, R., & Cordoba, J. J. (2001). Free amino acids and other non-volatile compounds formed during processing of Iberian ham. Meat Science, 59(4), 363–368. Mora, L., Fraser, P. D., & Toldrá, F. (2013). Proteolysis follow-up in dry-cured meat products through proteomic approaches. Food Research International, 54(1), 1292–1297. Mora, L., Hernandez-Cazares, A. S., Sentandreu, M. A., & Toldra, F. (2010). Creatine and creatinine evolution during the processing of dry-cured ham. Meat Science, 84(3), 384–389. Morales, R., Guerrero, L., Aguiar, A. P., Guardia, M. D., & Gou, P. (2013). Factors affecting dry-cured ham consumer acceptability. Meat Science, 95(3), 652–657. Narváez-Rivas, M., Gallardo, E., & León-Camacho, M. (2015). Evolution of volatile hydrocarbons from subcutaneous fat during ripening of Iberian dry-cured ham. A tool to differentiate between ripening periods of the process. Food Research International, 67, 299–307. Pérez-Palacios, T., & Estévez, M. (2020). Analysis of lipids and lipid oxidation products. In Meat Quality Analysis (pp. 217-239): Elsevier. Perez-Santaescolastica, C., Carballo, J., Fulladosa, E., Garcia-Perez, J. V., Benedito, J., & Lorenzo, J. M. (2018). Effect of proteolysis index level on instrumental adhesiveness, free amino acids content and volatile compounds profile of dry-cured ham. Food Research International, 107, 559–566. Perez-Santaescolastica, C., Carballo, J., Fulladosa, E., Munekata, P. E. S., Bastianello Campagnol, P. C., Gomez, B., & Lorenzo, J. M. (2019). Influence of high-pressure processing at different temperatures on free amino acid and volatile compound profiles of dry-cured ham. Food Research International, 116, 49–56. Resano, H., Sanjuan, A. I., Cilla, I., Roncales, P., & Albisu, L. M. (2010). Sensory attributes that drive consumer acceptability of dry-cured ham and convergence with trained sensory data. Meat Science, 84(3), 344–351. Rodriguez, M., Nunez, F., Cordoba, J. J., Bermudez, E., & Asensio, M. A. (1996). Grampositive, catalase-positive cocci from dry cured Iberian ham and their enterotoxigenic potential. Applied Environmental Microbiology, 62(6), 1897–1902. Ruiz, J., Garcı́a, C., del Carmen Dı́az, M. a., Cava, R., Tejeda, J. F., & Ventanas, J. (1999). Dry cured Iberian ham non-volatile components as affected by the length of the curing process. Food Research International, 32 (9), (pp. 643–651). Ruiz, J., Ventanas, J., Cava, R., Andres, A., & Garcia, C. (1999). Volatile compounds of
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Sensory properties and metabolomic profiles of dry-cured ham during the ripening process
T
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Masahiro Sugimotoa,b, , Tetsuya Sugawarac, Shinichi Obiyad, Ayame Enomotoa, Miku Kanekoa, Sana Otaa, Tomoyoshi Sogaa, Masaru Tomitaa a
Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan Research and Development Center for Minimally Invasive Therapies Health Promotion and Preemptive Medicine, Tokyo Medical University, Shinjuku, Tokyo 160-8402, Japan c Yamagata Research Institute of Technology, Shonai Testing Facility, Mikawa, Tagawa, Tsuruoka, Yamagata 997-0321, Japan d Tohoku Ham, Tsuruoka, Yamagata 997-0011, Japan b
A R T I C LE I N FO
A B S T R A C T
Keywords: Dry-cured ham Metabolomics Ripening Sensory evaluation Taste sensor
Dry-cured ham with a long ripening period is a valuable product worldwide. Ripening time is a key determinant of the endogenous metabolites that characterize the flavor and taste of ham products. While various studies have analyzed the relationship between ripening duration and sensory characteristics, no studies have evaluated ham products produced in Japan. Here, we conducted time-course metabolomic profiling, taste sensor-based analyses, and sensory evaluations by non-trained consumers during ripening. Capillary electrophoresis-mass spectrometry was used to quantify non-volatile metabolites, such as amino acids, organic acids, and nucleotides. In an analysis of eight time-points during 680 days of ripening, the highest score for the after-taste of umami was observed on day 540, despite subtle changes in the scores for other properties. The concentrations of aspartic acid and glutamic acid relative to those of total amino acids were the highest at this point. This approach can contribute to the understanding of the relationship between the metabolite profile and ripening duration.
1. Introduction Dry-cured hams treated by long-term ripening are popular worldwide, including in Japan. Dry-cured hams typically have high production costs because of the long length of the ripening-drying stage, which gives the product a profound taste and flavor (Flores, Grimm, Toldrá, & Spanier, 1997). Therefore, chemical changes during ripening have been investigated extensively to understand this process (Jurado, García, Timón, & Carrapiso, 2007; Martin, Antequera, Ventanas, BenitezDonoso, & Cordoba, 2001; Ruiz, Ventanas, Cava, Andres, & Garcia, 1999; Sforza et al., 2006; Zhang et al., 2018). Previous studies have examined the chemical changes in dry-cured ham during the ripening process. Metabolites are key chemical components for characterizing the taste and flavor of ham, and they have been approximately classified into volatile molecules, lipids, and other molecules. As examples of volatile metabolites, methylbutanal increased during the ripening of Iberian dry-cured hams, and the amount of this compound showed a positive correlation with their flavor
intensities (Ruiz et al., 1999). Changes in the volatile hydrocarbon content during ripening of Iberian dry-cured hams and Dahe black pig hams were also analyzed (Narváez-Rivas, Gallardo, & León-Camacho, 2015; Shi, Li, & Huang, 2019). Changes in lipids during the ripening were also reported. The oxidative changes in lipids during each processing step of Iberian ham, e.g., during salting, with various conditions, were analyzed (Andrés, Cava, Ventanas, Muriel, & Ruiz, 2004; Narváez-Rivas et al., 2015). As examples of the relationship between ripening and lipid profiles, changes in the content of phospholipids and free fatty acids, as well as the proportion of polyunsaturated fatty acids in French dry-cured ham were investigated (Buscailhon, Gandemer, & Monin, 1994). The relationship between lipid peroxidation and the texture of Serrano ham under various ripening conditions has been determined (del Olmo, Calzada, & Nuñez, 2016). In addition to these metabolites, the amino acid, peptides, and nucleotide contents in lean ham were shown to contribute to the taste (Gallego, Mora, & Toldrá, 2018; Liu et al., 2019; Perez-Santaescolastica
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Corresponding author at: Institute for Advanced Biosciences, Keio University, 246-2 Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. E-mail addresses: [email protected] (M. Sugimoto), [email protected] (T. Sugawara), [email protected] (S. Obiya), [email protected] (A. Enomoto), [email protected] (M. Kaneko), [email protected] (S. Ota), [email protected] (T. Soga), [email protected] (M. Tomita). https://doi.org/10.1016/j.foodres.2019.108850 Received 4 September 2019; Received in revised form 16 November 2019; Accepted 20 November 2019 Available online 30 November 2019 0963-9969/ © 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. Experimental design. (A) Example of a ham sample at ripening. (B) Part of ham sampled, including the inside round (A), outside round (B), round tip (C), and rump (D). (C) Sampling schedule. Triangles indicate collection points. Samples were analyzed by metabolomics, taste sensor, and chemical analyses. Only metabolomic analysis was conducted at the point indicated by a filled triangle.
The aim of this study was to understand the relationship of the metabolomic profile and ripening duration of dry-cured ham produced in Japan. The demand for dry-cured ham produced by long-duration ripening has increased, increasing the need for commercial production. However, available ingredients and environments differ between regions, such as the Mediterranean region, and thus the production protocol and consumer acceptability should be investigated. We analyzed changes in taste-active metabolites during the ripening process. The sensory characteristics of these samples were analyzed by a taste sensor. We also conducted sensory evaluation tests and metabolite profiling of ham samples produced in Japan, Spain, and Italy to understand their relationships. CE-MS was performed to simultaneously quantify various hydrophilic molecules, such as amino acids, organic acids, peptides, nucleotides, and their intermediate metabolites. The relationships among ripening duration, metabolite profile, and sensory features were analyzed.
et al., 2019). Protein degradation by protease yields taste-active molecules (Degnes, Kvitvang, Haslene-Hox, & Aasen, 2017; LópezPedrouso et al., 2019; Mora, Fraser, & Toldrá, 2013). Dipeptides are generated by the enzymatic action of dipeptidyl peptidases by releasing two amino acids from longer peptides and protein fragments (Sentandreu & Toldrá, 2001). Peptidyl dipeptidases and cathepsin B can also release dipeptides (Toldra, Rico, & Flores, 1993); thus, increases in amino acids confer various flavor and taste properties. The proteolysis showed no effect on total amino acid content while changed the balance of amino acids (Perez-Santaescolastica et al., 2018). During ripening, glycogen and glucose are catabolized, which decreases sweetness, while the concentration of lactate, an end-product of glycolysis, gradually increases (Buscailhon, Touraille, Girard, & Monin, 1995). Decreases in the pH and moisture content change the texture of ham (Garcıa-Rey, Garcıa-Garrido, Quiles-Zafra, Tapiador, & De Castro, 2004). Ripening also changes nucleic acid metabolites; ATP is reduced to ADP and subsequently AMP, while IMP is increased, conferring an umami taste because of the presence of glutamic acids. During long ripening periods, IMP changes to hypoxanthine and inosine, thereby increasing the intensity of bitterness (Hernández-Cázares, Aristoy, & Toldrá, 2011). The harmony of this wide variety of metabolites contributes to the taste and flavor of ham products. Metabolomics, a comprehensive metabolite profiling technology, is a new tool for the quality assessment of foods. For example, nuclear magnetic resonance has been used to analyze various crossbreeds of pigs (Straadt, Aaslyng, & Bertram, 2014) and metabolic patterns in Jinhua ham and Xuanwei ham (Zhang et al., 2018). Volatile compounds and lipids in Jinhua ham at each processing step, e.g., salting and ripening, have also been identified (Zhou & Zhao, 2007). Previously, we utilized capillary electrophoresis-mass spectrometry (CE-MS) to analyze the effect of processing conditions, such as smoking and lactic acid bacteria, on the quality of ham (Sugimoto et al., 2016, 2017). During the ripening process, protein degradation and increased dipeptides and amino acids are frequently observed in various fermented foods (Zhao, Schieber, & Gänzle, 2016), including in dry-cured ham (Degnes et al., 2017; Zhang et al., 2019); however, these previous studies have mostly focused on dry-cured hams produced from the Mediterranean region and China. The demand for commercial production of dry-cured ham in Japan has increased, but no studies using Japanese ingredients and environments have been published.
2. Material and methods 2.1. Ingredients and processing Ham samples were prepared using ingredients available in Japan by following the procedure for preparing Prosciutto ham with some modifications. The rump part is conventionally eliminated from the carcass for Prosciutto, while the rump part of the carcass is not eliminated in Japan. Specific pathogen-free Landrace, Large White, and Duroc (LWD) crossbred pigs were used. These pigs were fed corn, soybean cake, and rice, which contribute to ileal digestibility (Cervantes-Pahm, Liu, & Stein, 2014), and reared in the Shonal region (Yamagata, Japan). Slaughter was conducted when the pigs reached a mass of 110 kg (approximately 6 months). Hog, lard (Mogamigawa farm, Yamagata, Japan), rice flour (JA Tsuruoka, Yamagata, Japan), sea salt (Nihonkaikikaku, Niigata, Japan), and black pepper (Yasuma, Kanagawa, Japan) were used. The ham was prepared as follows: (1) Salting procedure: salt (3% of meat, w/w) was rubbed on the surface of the hog on days 1 and 7, and the samples were then kept in stainless-steel containers at ≤4 °C for 15 days. (2) Drying: the samples were suspended from the ceiling in a ripening room at ≤4 °C for 75 days. (3) Desalting: the samples were desalted in 35 °C water and 2
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ripened for 60 days at ≤4 °C. (4) Lard layering: the sample surfaces were covered with a coating of lard, black pepper, and rice flour. Rice flour, a staple food in Japan, is not typically used to produce Prosciutto ham but was used to give the ham unique characteristics. (5) Ripening: the samples were hung for various durations (Fig. 1A). All processes were conducted in the ham-producing company industry Tohoku Ham (Yamagata, Japan).
sensor (Japan Intelligent Sensor Technology [Insent], Inc., Kanagawa, Japan). Data from the rump were used as a reference, and data from the other parts were normalized against the reference (Exp. 1). Similarly, the data from the samples with 0 days of ripening were used as a reference, and the results for the other samples were normalized against this reference (Exp. 2). The remaining samples (175 g) were used for chemical analyses of moisture, lipids, and NaCl (Japan Food Research Laboratories, 2004). Chemical analyses were conducted in Exp. 2 and Exp. 3 with three samples of each ham.
2.2. Experimental design The following three experiments were conducted.
2.4. Chemical analysis
2.2.1. Effect of part-specific variation on metabolic profiles (Exp. 1) As a preliminary test, four parts, including the rump, outside round, inside round, and round tip, were subjected to metabolomics and taste sensor analyses (Fig. 1B). The samples were collected at 540 days. Three samples were collected from each part, and average concentrations were used.
Moisture was analyzed based on loss during drying, i.e., ham samples were homogenized and mixed with diatomaceous earth, dried at 135 °C for 2 h, and the reduction in dry weight was determined. Lipids were quantified by the Soxhlet extraction method, i.e., ham samples were extracted for 10 h by diethyl ether using a Soxhlet extractor, and the weight of the extracted lipids was determined. NaCl was extracted from the homogenized ham samples with 1% (w/v) hydrochloric acid and quantified using an atomic absorption spectrophotometer (AA7000; Shimadzu, Kyoto, Japan). All measurements were conducted in triplicate. This analysis was conducted as described in Exp. 2.
2.2.2. Effect of ripening duration on metabolic profiles and taste sensor analysis (Exp. 2) Metabolomics analyses of the ham samples were performed in triplicate after 0, 30, 90, 150, 366, 400, 540, and 680 days of ripening. Chemical analysis and taste sensor-based analysis were conducted after 0, 150, 400, 540, and 680 days of ripening (Fig. 1C). Based on the results of Exp. 1, only the outside round part was used in this experiment. For each sample, three samples were collected from each part, and average concentrations were used.
2.5. Metabolomics analyses The sample processing protocol, parameter settings for CE-MS, and processing from raw data to a concentration matrix were performed as described previously, with slight modifications (Sugimoto et al., 2017). Six small pieces (approximately 50 mg × 3 and 200 g × 3) were cut from adjacent parts from each ham sample and immediately frozen at −80 °C for metabolomic and taste sensor analyses, respectively. Briefly, metabolites of each ham sample were extracted by plunging the samples into methanol (500 μL) containing (20 μM each) methionine sulfone, D-camphor-10-sulfonic acid, and 2-(N-morpholino)ethanesulfonic acid as internal standards. The samples were homogenized at 1,500 rpm for 5 min using a cell disruption device (Shake Master Neo, BMS, Tokyo, Japan). Subsequently, 500 μL of chloroform and 200 μL of Milli-Q water (Millipore, Billerica, MA, USA) were added, and the solution was centrifuged at 4,600g for 15 min at 4 °C. The upper aqueous layer (300 μL) was centrifugally filtered (5-kDa cutoff filter, Millipore) at 9,100g for 4 h at 20 °C to remove large molecules. The filtrate (300 μL) was lyophilized and dissolved in 50 μL of Milli-Q water containing reference compounds (200 μmol/L 3-aminopyrrolidine and trimesate). The final solutions were measured by CE-MS in cation and anion modes. CE-MS raw data were analyzed using our proprietary software, MasterHands (Sugimoto, Wong, Hirayama, Soga, & Tomita, 2010), which follows typical data processing flows, including the detection of all possible peaks, elimination of noise and redundant features, and generation of an aligned data matrix with annotated metabolite identities and relative areas (peak areas normalized to those of internal standards) (Sugimoto, Kawakami, Robert, Soga, & Tomita, 2012). Concentrations were calculated using external standards based on the relative area, i.e., the area divided by that of internal standards. The concentration of each metabolite was normalized by the sample weight.
2.2.3. Relationship between metabolic profile and sensory features in various types of hams (Exp. 3) Iberian dry-cured ham traditionally requires at least 18–24 months for ripening (Rodriguez, Nunez, Cordoba, Bermudez, & Asensio, 1996). Here, we compared our produced samples to those produced in 18 and 24 months. Additionally, various commercially available dry-cured hams and our hams produced under different conditions were compared. To compare the produced dry-cured ham in Italy to our ham samples, prosciutto (Galloni, Parma, Italy) was used. As another European ham sample, Jamón serrano (Espuña, Olot, Spain) was also collected. Both of them were ranked higher than various ham samples from Japan in our previous study (Sugimoto et al., 2016). Only one commercial company in Japan follows the procedure for preparing Jamón serrano for the production of ham (Shirakawa., Akita Pref., Japan). This sample was also collected for comparison. To assess the effects of different salt treatments, ham samples were also prepared by 12 months of ripening with pink salt collected from the Himalaya mountains (Japan Salt, Tochigi, Japan) and sea salt. Samples ripened for 18 and 24 months with sea salt were also prepared (Table S1). Samples were labeled based on region, with the labels J and S indicating that the samples were collected from Japan and Spain, respectively. For the samples collected in Japan, the duration of ripening was labeled as 18M for samples aged 18 months, and so on. Two J-12M samples produced with rock salt and sea salt were labeled as J12-M-A and J12-M-B. Jamón serrano-like samples collected in Japan and Prosciutto samples were labeled as JJS and PP, respectively.
2.6. Sensory evaluation by non-trained consumers
2.3. Taste sensor and chemical analyses
Sensory evaluation tests were conducted as described in our previous study (Sugimoto et al., 2016), with slight modifications. The features to be evaluated and scoring method were different. Briefly, a reference sample was provided, and scores of the other samples were evaluated relative to this sample in the previous study, while a hedonic scoring system was used for evaluation of Italian and French ham by non-trained consumers (Cannata et al., 2010) without the use of reference samples. The following 13 features were evaluated.
Approximately 200 g of each sample collected from each ham was crushed using a mixer in two tubes. Next, 100 g of ion-exchanged water was added to 25 g of homogenized samples, and the samples were homogenized again and centrifuged at 9,500g for 20 min. The supernatant was filtered through 2-ply cotton gauze (Model No. 002-2146; Iwatsuki, Tokyo, Japan). The filtrate was analyzed using a SA402B taste 3
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Fig. 2. Time-course results for chemical analysis and taste sensor test (Exp. 2). (A) NaCl, (B) moisture, (C) lipid, and (D) taste sensor results. Panels A, B, and C show averages and standard deviations (n = 3). The scores on day 0 were set as 0 as a reference, and those of the other samples were normalized against this reference. ANOVA and post hoc Dunnett’s multiple comparison tests were used for comparisons between each value (> 0 days) and the value at day 0. All chemical analysis results were significant at P < 0.0001 (ANOVA). ****P < 0.0001, ***P < 0.001, and *P < 0.05.
participants. This analysis was conducted in Exp 3.
(1) Appearance (redness of lean, color gradation of lean, and whiteness of fat) (2) Flavor (3) Taste (sweetness, saltiness, acidity, bitterness, astringency, and umami) (4) Texture (hardness and pleasance on the tongue) (5) Overall evaluation
2.7. Statistical and data analyses One-way analysis of variance (ANOVA) and Bonferroni’s multiple comparison tests were used to evaluate the data obtained in the sensory evaluation tests. The time-course data were assessed by one-way ANOVA and Dunnett’s tests to compare the data from day 1 (as a control) and subsequent days of ripening, where data from days 0 and 150 were used as controls for metabolomic and taste sensor analyses, respectively. Pearson’s correlation coefficients were used to compare the metabolomic profiles between the two ham samples. Clustering was conducted to evaluate the similarity in metabolomic profiles, and the results were visualized as a heatmap. Correlation analyses were conducted using the data obtained in Exp. 3. Two independent analyses using (1) only metabolite concentrations and (2) metabolite concentrations and scores given by the sensory evaluation tests were conducted. P < 0.05 was considered to indicate statistically significant differences. Statistical analyses and data visualization were conducted using XLSTAT (ver. 2014.1.04; Addinsoft, Paris, France), MeV TM4 (Aiello et al., 2011), and GraphPad Prism (ver. 7.03, GraphPad Software, Inc., San Diego, CA, USA). The data are available upon request from the corresponding author.
Scores were determined based on the consumers’ preference using a 5-point scale (1, 2, … and 5), where 3 was optimal, 1 indicated the weakest evaluation, and 5 indicated the strongest evaluation. The items for taste evaluation, e.g., astringency, were selected among the items used for evaluation of meat and pork (Buscailhon et al., 1994). All samples were stored at 4 °C and prepared within 2.5 h prior to evaluation. The samples were served in a blinded manner (Fig. S1), and the order of assessment was not specified considering the bias introduced by the carryover effect. The purpose of the sensory evaluation test in this study was to analyze consumers’ acceptability. Consistency in the overall evaluation score between trained panelists and consumers was reported (Resano, Sanjuan, Cilla, Roncales, & Albisu, 2010). No professional panelists were included; only consumers of various ages and genders participated. The sensory evaluation was conducted in a large classroom. All samples were provided in a blinded manner. Bread without salt (Cracotte) and a bottle of water were provided to dilute the aftertaste between samplings. All participants were non-trained Japanese consumers. The characteristics of the participants are summarized at Table S3. The participants gathered in a large classroom between 16:00 and 18:00, and sensory evaluation was conducted at one time. Scoring sheets were also provided and collected just after the evaluation. The instructions for the evaluation were displayed in front of the
3. Results 3.1. Part-specific variation in metabolomic profiles among meat parts (Exp. 1) Variations in amino acids and organic acids among the samples collected from various parts are depicted in Fig. S2A and Fig. S2B. The 4
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desalting and low-temperature drying (i.e., after 150 days), the concentrations of these metabolites decreased, while those of other amino acids and peptides increased gradually. Among the amino acids, asparagine (Asn), followed by leucine (Leu), isoleucine (Ile), and other amino acids showed increasing trends during the ripening process.
rump showed unique profiles for both amino acids and organic acids. Overall, the concentrations of most amino acids in the rump were lower than those in other parts. Other parts showed similar metabolic profiles. Taste sensor analysis indicated substantial variation in the aftertaste of umami among parts, and the score for the rump was particularly low compared to those for the other parts (Fig. S2C). The other features showed no clear variation. Based on these data, the rump was not used, and the outside round was used for subsequent analyses (Exp. 2 and Exp. 3).
3.3. Sensory evaluation and metabolomic profile of various samples (Exp. 3) 3.3.1. Sensory evaluation scores and sensory scores obtained by the taste sensor for various products A total of 194 non-trained consumers (108 males and 85 females) were enrolled in the evaluation test (Table S3). Tables S4 and S5 summarize the results of sensory evaluation tests. Jamón Serrano from Spain (SJS) and Prosciutto from Italy (PP) showed relatively higher scores than the other samples. For example, the overall score for SJS was significantly higher than those for J-24M and Jamón Serrano-type sample from Japan (JJS) (ANOVA with Bonferroni’s multiple comparison test). Fig. S3 and Table S6 summarize the results of taste sensor analysis. All scores showed significant variation (P < 0.05, ANOVA). The aftertaste of umami showed the largest variation and JJS showed the highest score. Among samples with different ripening durations, samples collected at 540 days (J-18M) showed higher scores than the other samples, including J-12 M-A, J-12-B, and J24-M.
3.2. Effect of ripening duration (Exp. 2) 3.2.1. Time-course of chemical and taste sensor results Time-course data for moisture (Fig. 2A), NaCl (Fig. 2B), and lipids (Fig. 2C) were obtained. Moisture decreased dramatically over 90 days of salting (P < 0.0001, one-way ANOVA with Dunnett’s test) and decreased gradually thereafter. NaCl showed the opposite pattern. Lipids showed a moderate increase and eventually a significant elevation at 400 days (P = 0.0011, one-way ANOVA with Dunnett’s test). Fig. 2D shows a radar chart of the taste sensor results, and Table S2 summarizes the results of statistical analyses. All scores showed significant variation over time (P < 0.0001, one-way ANOVA), except for astringency (P = 0.0463, one-way ANOVA). Differences in a score of ≥ 1 were recognized as sensory differences. Saltiness and, particularly, the aftertaste of umami showed large variations. The saltiness decreased 150 days after desalting and then increased again. The umami aftertaste increased, showing the highest value at 540 days, followed by a decrease.
3.3.2. Comparison of metabolomic profiles among various products Fig. 4 and Table S7 summarize the results of the metabolomic and chemical analyses. SJS and PP, which showed higher overall sensory scores (Fig. 5A), showed higher lipid concentrations than the other samples (Table S7). Metabolomic analyses revealed higher amino acid concentrations, except for Gln, in the samples with the longest ripening time compared to those with shorter ripening times (J-18M and J-12MA). The difference in salt also affected the metabolomic profiles, e.g., J12M-A showed higher concentrations of inosine and Ala-Ala than J-
3.2.2. Time-course of metabolomic profiles during ripening Fig. 3 shows the heatmap of the time-courses of metabolomic profiles. At 0 and 30 days, the concentrations of most metabolites were lower and the concentrations of IMP, GMP, malate, and fumarate were higher than those on subsequent days. Among the amino acids, glutamine (Gln) and cysteine (Cys) showed high concentrations. After
Fig. 3. Time-course analysis of metabolomic profiles (Exp. 2). Each concentration was divided by the average concentration for each metabolite and is shown using a blue-white-red scheme, where red and blue indicate relatively higher and lower values and white indicates the average. Metabolites were grouped according to Pearson correlation-based clustering analysis. Amino acids, organic acids, nucleotides, and peptides are shown in different colors. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 5
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Fig. 4. Heatmap showing metabolomic profiles (Exp. 3). Data were visualized using the method used to generate Fig. 3.
showed no such metabolites. The correlation network among metabolite concentrations is depicted in Fig. 6. The 13 amino acids, fumarate, carnitine, and creatinine showed a large network. Asn, Arg, and serine (Ser) also showed correlations. Other metabolites, such as guanine and ornithine, also showed correlations.
12M-B. SJS and PP showed similar overall profiles, while guanine and ornithine concentrations were higher in the PP samples (Fig. 4).
3.3.3. Correlation analysis (Exp. 3) The correlations among sensory evaluation scores and quantified metabolite concentrations obtained from Exp. 3 are summarized at Table S8. Only correlations showing P < 0.05 are listed. For example, appearance showed various correlated metabolites, while flavor
Fig. 5. Relationship between the scores in the sensory evaluation test and metabolite quantities. (A) Correlations of all quantified metabolites of SJS showing the highest score in overall sensory evaluation. ***P < 0.001. (B) Relative concentrations of Asp and Glu compared to the concentrations of all amino acids (%). C) Relationships between absolute concentrations of guanine, Asp, and Glu. Lines were fit by leastsquares regression. Point size indicates the overall score obtained in the sensory evaluation.
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Fig. 6. Correlation network among quantified metabolites (Exp. 3). The metabolite showing high correlation (R2 > 0.81) was connected. Metabolites with known taste for sweetness, bitterness, umami, and sourness were colored in pink, green, orange, and yellow, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
4. Discussion
longest duration, while J-18M was ranked higher than the other samples with shorter ripening durations, indicating that the balance of amino acids relative to the total amino acid concentration is related to the sensory features. The effects of salt were evaluated for two types of dry-cured ham ripened for 12 months with rock salt (J-12M-A) and sea salt (J-12M-B). The metabolic profile showed that only inosine and AlaAla were higher in J-12M-A, while other metabolites showed similar concentration patterns (Fig. 4). The overall score in the sensory evaluation test was higher for J-12M-A (Table S4), but did not significantly differ from those of the other samples (Table S5). These results indicate that the type of salt used has no significant effects on ham ripening. With respect to the balance of amino acids during ripening, Asp and Glu showed unique patterns and increased up to 540 days, followed by a decrease at 680 days (Fig. 5B). The individual amino acid concentrations increased at 90 days (P < 0.05; ANOVA with Dunnett’s tests) and subsequently increased in a gradual manner (Fig. S4). Briefly, the total concentration of amino acids increased more rapidly between days 540 and 680 compared to the levels of Asp and Gly. Interestingly, these amino acid concentrations showed clear linearity with respect to the guanine concentration (Fig. 5C). The overall sensory evaluation scores for the samples close to the regression lines were relatively high, while those of the samples far from this line, e.g., J-24M, were relatively low (Fig. 5C). The guanine concentration also increased at 90 days (P < 0.05; ANOVA with Dunnett’s tests) and reached a maximum at 540 days (Fig. S4). Inosine (IMP) and Glu are known to enhance the umami characteristic. Sensory analysis revealed the highest value for the aftertaste of umami in J-18M among samples with different ripening durations (J12M-A, J-18M, and J-24M), while umami showed a significant difference among samples. Thus, our data showed a positive correlation between these nucleotides and only the aftertaste of umami. Our method did not measure volatile compounds, although several relationships among free amino acids and flavor have been demonstrated. For example, increased amino acid contents affect bitter flavor (Sforza et al., 2001; Virgili, Schivazappa, Parolari, Bordini, & Degni, 1998). Peptide levels are correlated with flavor formation (HansenMøller, Hinrichsen, & Jacobsen, 1997; Ruiz, 1999). Volatile compounds were generated by the Maillard reaction of Jinhua ham and histidine and lysine among amino acids contributed to the flavor characterization (Zhu et al., 2018). Correlation analyses (Fig. 6) revealed that most amino acids functioned as sources of sweetness, bitterness, sourness, and umami. Asn, Arg, and Ser also showed correlations. Among the dipeptides, only β-Ala-Lys showed a correlation with 3-hydrobutyrate, while their contribution to taste and flavor remain unknown. No metabolites showed a significant correlation with flavor (Table S8). Based
In this study, the relationships among changes in the metabolomic profiles of ham samples and taste were evaluated by taste sensor, consumer acceptability, and metabolomic analyses. Variations in the metabolomic profiles among parts from a ham sample were analyzed (Exp. 1). The inside and outside rounds and round tip showed similar patterns, while the rump showed unique patterns in both metabolite concentrations and sensory test scores (Fig. S2). During the salting process, the top of the rump was treated with salt, and the rump was wider surface of lean (Fig. 1A). The salt concentration is initially higher in drier external zones compared to in the humid inner zone, which subsequently reverses (Arnau, Guerrero, Casademont, & Gou, 1995). One possible reason for this rump-specific bias is the faster chemical process in permeation and faster oxidation compared to in the other zone. Therefore, the outside round zone was analyzed as a representative sample in Exp. 2 and Exp. 3. During the ripening process (Exp. 2), moisture decreased, while lipids and NaCl increased (Fig. 2) in the outside round part. Metabolites during ripening showed moderate increases for each amino acid, except for Gln and Cys. Asn showed the most rapid increase, followed by Leu and Ile. Peptides also showed similar increasing trends during the ripening period (Fig. 3). These monotonic increases can be explained by the degradation of proteins during ripening. SJS, PP, and 7 types of ham produced in Japan were compared by metabolomic analysis and sensory evaluation (Exp. 3). SJS and PP showed lower NaCl and moisture contents and higher lipid concentrations than Japanese ham samples (Table S7). All quantified metabolites in SJS exhibited the highest positive correlation with those of PP (R = 0.9937, P < 0.05, Pearson correlation) and second highest positive correlation with those of J-18 M (R = 0.9936, P < 0.05, Pearson correlation) (Fig. 5A). Interestingly, the three sensory evaluation scores, overall evaluation, umami, and flavor, ranked SJS, PP, and J-18 M within the top three samples (Table S4). Among the metabolites, SJS showed higher concentrations of malate and isocitrate than the other samples (Fig. 4). PP showed higher concentrations of amino acids, such as tryptophan (Trp), aspartic acid (Asp), glycine (Gly), histidine (His), methionine (Met), phenylalanine (Phe), and ornithine. JJS showed similar profiles (Fig. 4). A comparison of six types of Iberian hams revealed that Serrano ham had lower tyrosine (Tyr) and higher Asp contents (Virgili et al., 1999); not only the total concentration of amino acids but also the balance among amino acids contributes to flavor (Zhao et al., 2016). Our data also revealed the highest concentration of amino acids in the ham ripened for the 7
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on our data, estimating flavor characteristics from a single metabolite is difficult. Relative Gln and Asp contents compared to the total concentration of amino acids showed a unique time-course, increasing up to 540 days and decreasing thereafter (Fig. 5B). Such non-monotonic changes in various metabolites have been reported. For example, Ser, Trp, and valine concentrations in dry-cured ham increased up to 15 months and then decreased, although the total amino acids increased monotonically (Degnes et al., 2017). In the comparison of Parma ham samples processed for 450, 570, and 690 days, monosodium glutamate-like and bitter taste monotonically increased, while sour flavors peaked at 570 days (Sforza et al., 2006). The ratio of hypoxanthine to inosine increased up to 5 months, the ratio of creatine to creatinine increased up to 9 months, and both ratios remained constant thereafter during ham ripening (Escudero, Mora, Aristoy, & Toldra, 2011). Creatine and creatinine showed consistent trends, despite variations in the balance of NaCl and KCl over their long ripening periods (Mora, HernandezCazares, Sentandreu, & Toldra, 2010). In our study, the taste sensor results showed the best scores for full-bodied umami at 540 days; the ratio of the amino acids and nucleotide balance may have contributed to this result. This study had several limitations. CE-MS enables the profiling of only hydrophilic metabolites. Other analytical methodologies enables lipids and volatile compound profiling (Domínguez et al., 2019; PérezPalacios & Estévez, 2020; Wang et al., 2018). Integration of the data analyzed by multiple approaches would contribute to comprehensive understanding of the chemical properties of dry-cured hams. Samples of only 50 mg were necessary for the metabolomic analyses; therefore, we collected lean pieces from ham samples. The taste sensor analysis required large pieces (approximately 200 g), which included fat, presumably explaining the discrepancy between the metabolomic profile results and other observations. Here, we utilized a 5-point scale, but a 9-point scale is an alternative method commonly used for consumer acceptance tests (Laureati et al., 2014; Yeu, Lee, & Lee, 2008). Only Japanese consumers were involved in the evaluation test, and differences in sensory assessments by people of different nationalities were reported (Garcia-Gonzalez et al., 2006). Furthermore, ham samples were served in a blinded manner under normal lighting. Various factors affecting consumer acceptability, such as visible characteristics (Morales, Guerrero, Aguiar, Guardia, & Gou, 2013), were not completely eliminated. In addition, randomizing the order of the samples would have reduced bias from the carryover effect.
We utilized Japanese samples as a case study, but a similar approach can be used to analyze the ripening process of any type of ham. CRediT authorship contribution statement Masahiro Sugimoto: Writing - review & editing, Methodology, Formal analysis. Tetsuya Sugawara: Formal analysis, Methodology, Investigation. Shinichi Obiya: Resources. Ayame Enomoto: Visualization. Miku Kaneko: Investigation, Data curation. Sana Ota: Investigation, Data curation. Tomoyoshi Soga: Supervision. Masaru Tomita: Project administration. Acknowledgements This work was supported by a collaborative grant (exploring research seeds) and a grant from Yamagata prefecture and Tsuruoka city. We thank all sensory evaluation contributors. We would like to thank Editage (www.editage.jp) for English language editing. Declarations of Competing Interest None. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.foodres.2019.108850. References Aiello, D., De Luca, D., Gionfriddo, E., Naccarato, A., Napoli, A., Romano, E., ... Tagarelli, A. (2011). Review: Multistage mass spectrometry in quality, safety and origin of foods. European Journal of Mass Spectrometry (Chichester, Eng), 17(1), 1–31. Andrés, A. I., Cava, R., Ventanas, J., Muriel, E., & Ruiz, J. (2004). Lipid oxidative changes throughout the ripening of dry-cured Iberian hams with different salt contents and processing conditions. Food Chemistry, 84(3), 375–381. Arnau, J., Guerrero, L., Casademont, G., & Gou, P. (1995). Physical and chemical changes in different zones of normal and PSE dry cured ham during processing. Food Chemistry, 52(1), 63–69. Buscailhon, S., Berdague, J. L., Bousset, J., Cornet, M., Gandemer, G., Touraille, C., & Monin, G. (1994). Relations between compositional traits and sensory qualities of French dry-cured ham. Meat Science, 37(2), 229–243. Buscailhon, S., Gandemer, G., & Monin, G. (1994). Time-related changes in intramuscular lipids of French dry-cured ham. Meat Science, 37(2), 245–255. Buscailhon, S., Touraille, C., Girard, J., & Monin, G. (1995). Relationships between muscle tissue characteristics and sensory qualities of dry-cured ham. Journal of Muscle Foods, 6(1), 9–22. Cannata, S., Ratti, S., Meteau, K., Mourot, J., Baldini, P., & Corino, C. (2010). Evaluation of different types of dry-cured ham by Italian and French consumers. Meat Science, 84(4), 601–606. Cervantes-Pahm, S. K., Liu, Y., & Stein, H. H. (2014). Comparative digestibility of energy and nutrients and fermentability of dietary fiber in eight cereal grains fed to pigs. Journal of the Science of Food and Agriculture, 94(5), 841–849. Degnes, K. F., Kvitvang, H. F. N., Haslene-Hox, H., & Aasen, I. M. (2017). Changes in the profiles of metabolites originating from protein degradation during ripening of dry cured ham. Food Bioprocess Technology, 10(6), 1122–1130. del Olmo, A., Calzada, J., & Nuñez, M. (2016). Lipolysis, lipid peroxidation and texture of Serrano ham processed under different ripening temperature conditions. International Journal of Food Science and Technology, 51(8), 1793–1800. Domínguez, R., Purriños, L., Pérez-Santaescolástica, C., Pateiro, M., Barba, F. J., Tomasevic, I., ... Lorenzo, J. M. (2019). Characterization of volatile compounds of dry-cured meat products using HS-SPME-GC/MS Technique. Food Analytical Methods, 12(6), 1263–1284. Escudero, E., Mora, L., Aristoy, M. C., & Toldra, F. (2011). Possible biological markers of the time of processing of dry-cured ham. Meat Science, 89(4), 536–539. Flores, M., Grimm, C. C., Toldrá, F., & Spanier, A. M. (1997). Correlations of sensory and volatile compounds of Spanish “Serrano” dry-cured ham as a function of two processing times. Journal of Agriculture and Food Chemistry, 45(6), 2178–2186. Gallego, M., Mora, L., & Toldrá, F. (2018). Differences in peptide oxidation between muscles in 12 months Spanish dry-cured ham. Food Research International, 109, 343–349. Garcia-Gonzalez, D. L., Roncales, P., Cilla, I., Del Rio, S., Poma, J. P., & Aparicio, R. (2006). Interlaboratory evaluation of dry-cured hams (from France and Spain) by assessors from two different nationalities. Meat Science, 73(3), 521–528. Garcıa-Rey, R., Garcıa-Garrido, J., Quiles-Zafra, R., Tapiador, J., & De Castro, M. L. (2004). Relationship between pH before salting and dry-cured ham quality. Meat
5. Conclusion In this study, the effects of ripening duration on the metabolite profile and sensory features of ham were analyzed. The primary purpose of this study was to understand the effect of ripening duration on dry-cured ham produced in Japan. The ham samples were analyzed by CE-MS-based metabolomics, chemical analyses, taste sensor analyses, and sensory evaluations. Part-specific variations revealed unique features of the rump, and thus the outside round part was used for subsequent analyses. The ripening process resulted in a gradual increase in amino acids for up to 680 days. However, samples ripened for 540 days were considered as optimal, as they showed the highest overall evaluation score in sensory evaluation and highest aftertaste of umami in the sensory test. The total concentration of amino acids increased gradually during ripening, while the relative concentrations of Gln and Asn compared to the total amino acid concentration were highest at 540 days, and guanine concentration, nucleotide concentration, and their combination, which enhanced the umami-related characteristics, were also the highest at 540 days. These metabolite changes along with other gradual increases in various amino acids and organic acids contributed to this sensory change. The correlation analysis revealed that various amino acids were correlated with each other and that it is difficult to estimate sensory attributes using only a single metabolite. 8
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dry-cured Iberian ham as affected by the length of the curing process. Meat Science, 52(1), 19–27. Sentandreu, M., & Toldrá, F. (2001). Dipeptidyl peptidase activities along the processing of Serrano dry-cured ham. European Food Research and Technology, 213(2), 83–87. Sforza, S., Galaverna, G., Schivazappa, C., Marchelli, R., Dossena, A., & Virgili, R. (2006). Effect of extended aging of parma dry-cured ham on the content of oligopeptides and free amino acids. Journal of Agriculture and Food Chemistry, 54(25), 9422–9429. Sforza, S., Pigazzani, A., Motti, M., Porta, C., Virgili, R., Galaverna, G., ... Marchelli, R. (2001). Oligopeptides and free amino acids in Parma hams of known cathepsin B activity. Food Chemistry, 75(3), 267–273. Shi, Y., Li, X., & Huang, A. (2019). A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham. Meat Science, 158, 107904. Straadt, I. K., Aaslyng, M. D., & Bertram, H. C. (2014). An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception. Meat Science, 96(2), 719–728. Sugimoto, M., Kawakami, M., Robert, M., Soga, T., & Tomita, M. (2012). Bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis. Current Bioinformatics, 7(1), 96–108. Sugimoto, M., Obiya, S., Kaneko, M., Enomoto, A., Honma, M., Wakayama, M., ... Tomita, M. (2017). Metabolomic profiling as a possible reverse engineering tool for estimating processing conditions of dry-cured hams. Journal of Agriculture and Food Chemistry, 65(2), 402–410. Sugimoto, M., Obiya, S., Kaneko, M., Enomoto, A., Honma, M., Wakayama, M., & Tomita, M. (2016). Simultaneous analysis of consumer variables, acceptability and sensory characteristics of dry-cured ham. Meat Science, 121, 210–215. Sugimoto, M., Wong, D. T., Hirayama, A., Soga, T., & Tomita, M. (2010). Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics, 6(1), 78–95. Toldra, F., Rico, E., & Flores, J. (1993). Cathepsin B, D, H and L activities in the processing of dry-cured ham. Journal of the Science of Food and Agriculture, 62(2), 157–161. Virgili, R., Parolari, G., Bordini, C. S., Schivazappa, C., Cornet, M., & Monin, G. (1999). Free amoni acids and dipeptides in dry-cured ham. Journal of Muscle Foods, 10(2), 119–130. Virgili, R., Schivazappa, C., Parolari, G., Bordini, C. S., & Degni, M. (1998). Proteases in fresh pork muscle and their influence on bitter taste formation in dry-cured ham. Journal of Food Biochemistry, 22(1), 53–63. Wang, W., Feng, X., Zhang, D., Li, B., Sun, B., Tian, H., & Liu, Y. (2018). Analysis of volatile compounds in Chinese dry-cured hams by comprehensive two-dimensional gas chromatography with high-resolution time-of-flight mass spectrometry. Meat Science, 140, 14–25. Yeu, K., Lee, Y., & Lee, S. Y. (2008). Consumer acceptance of an extruded soy-based highprotein breakfast cereal. Journal of Food Science, 73(1), S20–S25. Zhang, J., Ye, Y., Sun, Y., Pan, D., Ou, C., Dang, Y., ... Wang, D. (2018). 1H NMR and multivariate data analysis of the differences of metabolites in five types of dry-cured hams. Food Research International, 113, 140–148. Zhang, J., Yi, Y., Pan, D., Zhou, G., Wang, Y., Dang, Y., ... Cao, J. (2019). (1)H NMR-based metabolomics profiling and taste of boneless dry-cured hams during processing. Food Research International, 122, 114–122. Zhao, C. J., Schieber, A., & Gänzle, M. G. (2016). Formation of taste-active amino acids, amino acid derivatives and peptides in food fermentations–A review. Food Research International, 89, 39–47. Zhou, G. H., & Zhao, G. M. (2007). Biochemical changes during processing of traditional Jinhua ham. Meat Science, 77(1), 114–120. Zhu, C. Z., Zhao, J. L., Tian, W., Liu, Y. X., Li, M. Y., & Zhao, G. M. (2018). Contribution of Histidine and Lysine to the Generation of Volatile Compounds in Jinhua Ham Exposed to Ripening Conditions Via Maillard Reaction. Journal of Food Science, 83(1), 46–52.
Science, 67(4), 625–632. Hansen-Møller, J., Hinrichsen, L., & Jacobsen, T. (1997). Evaluation of peptides generated in Italian-style dry-cured ham during processing. Journal of Agriculture and Food Chemistry, 45(8), 3123–3128. Hernández-Cázares, A. S., Aristoy, M. C., & Toldrá, F. (2011). Nucleotides and their degradation products during processing of dry-cured ham, measured by HPLC and an enzyme sensor. Meat Science, 87(2), 125–129. Japan Food Research Laboratories (2004). Analytical Manual for Standard Tables of Food Composition in Japan (5th ed.). Tokyo: Chuouhoki Publishing in Japanese. Jurado, Á., García, C., Timón, M. L., & Carrapiso, A. I. (2007). Effect of ripening time and rearing system on amino acid-related flavour compounds of Iberian ham. Meat Science, 75(4), 585–594. Laureati, M., Buratti, S., Giovanelli, G., Corazzin, M., Lo Fiego, D. P., & Pagliarini, E. (2014). Characterization and differentiation of Italian Parma, San Daniele and Toscano dry-cured hams: A multi-disciplinary approach. Meat Science, 96(1), 288–294. Liu, S., Wang, G., Xiao, Z., Pu, Y., Ge, C., & Liao, G. (2019). 1H-NMR-based water-soluble low molecular weight compound characterization and free fatty acid composition of five kinds of Yunnan dry-cured hams. LWT, 108, 174–182. López-Pedrouso, M., Pérez-Santaescolástica, C., Franco, D., Carballo, J., Zapata, C., & Lorenzo, J. (2019). Molecular insight into taste and aroma of sliced dry-cured ham induced by protein degradation undergone high-pressure conditions. Food Research International, 122, 635–642. Martin, L., Antequera, T., Ventanas, J., Benitez-Donoso, R., & Cordoba, J. J. (2001). Free amino acids and other non-volatile compounds formed during processing of Iberian ham. Meat Science, 59(4), 363–368. Mora, L., Fraser, P. D., & Toldrá, F. (2013). Proteolysis follow-up in dry-cured meat products through proteomic approaches. Food Research International, 54(1), 1292–1297. Mora, L., Hernandez-Cazares, A. S., Sentandreu, M. A., & Toldra, F. (2010). Creatine and creatinine evolution during the processing of dry-cured ham. Meat Science, 84(3), 384–389. Morales, R., Guerrero, L., Aguiar, A. P., Guardia, M. D., & Gou, P. (2013). Factors affecting dry-cured ham consumer acceptability. Meat Science, 95(3), 652–657. Narváez-Rivas, M., Gallardo, E., & León-Camacho, M. (2015). Evolution of volatile hydrocarbons from subcutaneous fat during ripening of Iberian dry-cured ham. A tool to differentiate between ripening periods of the process. Food Research International, 67, 299–307. Pérez-Palacios, T., & Estévez, M. (2020). Analysis of lipids and lipid oxidation products. In Meat Quality Analysis (pp. 217-239): Elsevier. Perez-Santaescolastica, C., Carballo, J., Fulladosa, E., Garcia-Perez, J. V., Benedito, J., & Lorenzo, J. M. (2018). Effect of proteolysis index level on instrumental adhesiveness, free amino acids content and volatile compounds profile of dry-cured ham. Food Research International, 107, 559–566. Perez-Santaescolastica, C., Carballo, J., Fulladosa, E., Munekata, P. E. S., Bastianello Campagnol, P. C., Gomez, B., & Lorenzo, J. M. (2019). Influence of high-pressure processing at different temperatures on free amino acid and volatile compound profiles of dry-cured ham. Food Research International, 116, 49–56. Resano, H., Sanjuan, A. I., Cilla, I., Roncales, P., & Albisu, L. M. (2010). Sensory attributes that drive consumer acceptability of dry-cured ham and convergence with trained sensory data. Meat Science, 84(3), 344–351. Rodriguez, M., Nunez, F., Cordoba, J. J., Bermudez, E., & Asensio, M. A. (1996). Grampositive, catalase-positive cocci from dry cured Iberian ham and their enterotoxigenic potential. Applied Environmental Microbiology, 62(6), 1897–1902. Ruiz, J., Garcı́a, C., del Carmen Dı́az, M. a., Cava, R., Tejeda, J. F., & Ventanas, J. (1999). Dry cured Iberian ham non-volatile components as affected by the length of the curing process. Food Research International, 32 (9), (pp. 643–651). Ruiz, J., Ventanas, J., Cava, R., Andres, A., & Garcia, C. (1999). Volatile compounds of
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