JP6463596B2 - Natural cheese - Google Patents

Description

The present invention relates to a natural cheese excellent in flavor texture.

In recent years, consumption of natural cheese in Japan has been on an increasing trend, but it is still about 1/10 of that in Europe. This is due to the fact that natural cheese has a long history in Europe, and many natural cheeses have been developed to suit the tastes of the European people.
Natural cheese has a wide variety of flavors, textures, and textures depending on the production process, and factors such as milk quality, milk processing methods, lactic acid bacteria, enzymes, bacteria, mold, and aging conditions are factors that contribute to flavor development. Listed as big. In recent years, with the widespread use of natural cheese, natural cheeses with various flavors and textures have come to the market. For example, hard natural cheeses such as gouda cheese, cheddar cheese, grana cheese, and parmesan cheese have characteristic flavors due to lactic acid bacteria, proteins due to the action of enzymes, and flavor components produced by lipolysis and aromatic components during ripening. (Non-Patent Document 1).
It is known that cheese-specific aroma is a complex result of a variety of aroma components. As for the aroma components in cheese, many reports have been made on alcohols, esters, aldehydes, ketones, flow-containing compounds, lactones, etc., and the aroma quality of individual aroma components is also known. These are substances metabolized by the action of enzymes in various microorganisms from fats, amino acids, carbohydrates and the like. Each fragrance is recognized by humans as a variety of scents by mutual enhancement, masking, and composite effects. This perception is also related to eating experience, and the feeling is often different depending on the country or region. The taste of cheese depends on food culture and food experience, and it has been reported that the taste of cheese varies depending on the region (Non-patent Document 1).

These natural cheeses are prepared by adding lactic acid bacteria and milk coagulation enzyme to milk, coagulating, heating and stirring, filling a curd that has been reduced in water content by eliminating whey, and aging through a salting step. Natural cheese-specific flavor is slowly formed during ripening, and the flavor and texture change greatly depending on long-term aging conditions.
Natural cheese is often eaten as it is, but cheddar cheese and gouda cheese are further used as raw materials for processed cheese and are often consumed as processed cheese. In any case, since the flavor varies depending on the ripening timing, it is very important to predict the change during aging in order to provide a product having the most desirable flavor.
Recently, with the evolution of instrumental analysis such as gas chromatography and multivariate analysis operation technology and the enhancement of multivariate analysis software, fatty acids, amino acids and aroma components are extracted from cheese, and then by gas chromatography and liquid chromatography, Attempts to identify the relationship between the aroma components of cheese and the sensory characteristics have been increasing by identifying and quantifying the components and integrating and analyzing the components and sensory evaluation results.
By using multivariate analysis in the field of chemometrics (econometrics), predicting diseases from the analysis results of blood components, and analyzing the spectral characteristics in the near infrared region and chromatographic component dispersion, the quality of food Is being predicted. By using score plots and loading plots based on PCA (principal component analysis) and partial least squares analysis (PLS), the positioning between samples and the characteristic components and sensory items of each sample It is possible to specify related components. For example, there is a report (non-patent document 1) that the oil content of cheddar cheese shows the relationship between sensory characteristics and aroma components, and a report (non-patent document 2) that analyzes the effect of differences in maturity on sensory evaluation points. To do. In addition, there are reports that evaluate the effects of cheese ripening conditions and milking time on ingredients (Non-Patent Document 3), reports that evaluate the effects of milk sterilization conditions on sensory characteristics (Non-Patent Document 4), and the like. . Among them, the OPLS-DA (orthogonal partial least squares project to latent structures-discriminant analysis) method contributes to the difference between these groups in the search for candidate markers and plant metabolites using blood component data of cancer patients and normal individuals. Has been used to identify components that contribute to the progress of metabolite analysis (Non-patent Information 5)
As an element which influences the flavor of natural cheese, it is thought that it is based on compound effects, such as an aromatic component, a taste component, a physical property, and a color tone. Various knowledge about the relationship between the aromatic component and the sensory score, which is each element, the relationship between the hydrophilic component and the sensory score, and the like has been disclosed by applying a multivariate analysis technique (Patent Document 1).

JP 2013-7732 A

Journal of Dairy Science, 93, 5069-5081 (2010) Journal of Dairy Science, 87, 11-19 (2004) International Dairy Journal, 18, 801-810 (2008) International Dairy Journal, 18, 790-800 (2008) Chemometrics and Intelligent Laboratory System, 84, 82-87 (2006)

The deliciousness of cheese is due to the combined effects as described above, but each of the above documents focuses on single components such as only aroma component analysis and only taste components. Moreover, although patent document 1 suggests existence of those compound effects, the optimal value of the combination is unknown. In order to provide natural cheese that meets the tastes of the Japanese, it is necessary to comprehensively analyze fragrance components, taste components, texture, color tone, etc., and grasp the optimum balance.

In order to solve the above-mentioned problems, the present inventors conducted intensive research, and conducted component analysis, physical property measurement, and color tone analysis by instrumental analysis on a plurality of the same type of natural cheese, and combined sensory evaluation results. By applying PLS regression analysis as a multivariate analysis method, it was possible to identify the optimal balance of the above elements corresponding to individual sensory characteristics, leading to natural cheese with high palatability for the Japanese.
The present invention has an acetoin content of 1000 μg / kg or more, an ethanol content of 130 μg / kg or less, a butanoic acid content of 350 μg / kg or less, a hexanoic acid content of 130 μg / kg or less, A natural cheese having a lactic acid content of 1200 mg / 100 g or less, a hardness of 5000 gf or less in texture analyzer analysis, and an adhesion of 4500 g · s or more.

ADVANTAGE OF THE INVENTION According to this invention, the natural cheese excellent in flavor food texture and high palatability for Japanese can be provided.

The figure which shows the score prediction result of the preference by PLS. The figure which shows Coefficients data of each instrumental analysis data.

Natural cheese of the present invention has an acetoin content of 1000 μg / kg or more, an ethanol content of 130 μg / kg or less, a butanoic acid content of 350 μg / kg or less, and a hexanoic acid content of 130 μg / kg. It is a natural cheese having a lactic acid content of not more than kg, a lactic acid content of not more than 1200 mg / 100 g, a hardness of 5000 gf or less in texture analyzer analysis, and an adhesiveness of not less than 4500 g · s .
The natural cheese of the present invention can be manufactured by applying a general natural cheese manufacturing method. (1) The time until milk pasteurization after milking does not exceed 48 hours, (2) lactic acid bacteria and rennet By using two or more treatments in combination among the following three methods: making the lactose content of raw milk before adding the amount of 2.0% by weight or less, and (3) salting as a salting method, Cheese having a preferred flavor can be prepared.

The natural cheese of the present invention is preferably natural cheese with a relatively long ripening period such as gouda, cheddar, edam, samso, parmesan, mimolette, but is limited to the type of cheese, including whether or not it contains mold ripening. It is not something. Moreover, the milk used as a raw material for cheese is not limited to milk, and can be applied to cheese produced using buffalo, sheep milk, and goat milk.

The conditions of the “preferred flavor” of the cheese produced in the present invention are as follows. For the 14 types of Gouda cheeses with different producers and ripening periods, the aroma components by the instrumental analysis, the taste components, the physical properties by the texturizer, and the color tone evaluation by the color difference meter It was determined by performing.

As the aroma component extraction method of the present invention, a headspace-SPME adsorption method and the like were used. The aroma component extraction method is not limited to these methods, and a method such as a dynamic headspace adsorption method using a Tenax resin, a SAFE (Solvent assisted flavor extraction) method, or a steam distillation extraction method can be used. The obtained aroma component extract is separated using gas chromatography (GC), and quantified using a mass spectrometer (MS), smell sniffing method, and hydrogen ionization detector (FID). Hereinafter, aroma component measurement using the headspace-SPME extraction method and the steam distillation extraction method is referred to as SPME-GC / MS method and SDE-GC / MS method, respectively.

The aroma component measurement by SPME-GC / MS method was performed by the following method. 1 g of cheese crushed to about 1 to 2 mm by a food processor was weighed into a 20 mL vial, and an internal standard (trans-2-methyl-2-butenal, 5 ppm 70 mg) was dropped onto the cheese. After filling with nitrogen, it was sealed with a silicon seal and used as a measurement sample. In order to familiarize with the internal standard, stir for about 10 seconds with a vortex mixer, equilibrate for 10 minutes in a 37 ° C constant temperature bath, and likewise with SPME fiber (50/30 DVB / Carboxen / PDMS (SUPELCO)) for 60 minutes at 37 ° C. After adsorption, it was measured by GC / MS. The column used is DB-5ms (60m × 0.32mm id × 0.5μm, manufactured by J & W), the analytical instruments are Agilent 6890 (GC), 5973 (MSD) (Agilent Technology), and the analysis of the measurement results is MSDChemiStation (Agilent)・ Technology Corporation) was used.
The aroma component measurement by SDE-GC / MS method was performed by the following method. 50 g of cheese chopped into strips were prepared, and steam, 150 mL of cheese, ion-exchanged water and 1 drop of silicone were added to a 1000 mL round bottom flask, and 500 mL of condensate containing aroma components was obtained. Place the resulting condensate, 10 g of sodium chloride, and dichloromethane (5000-fold concentrated product for residual agricultural chemicals / PCB test Kanto Chemical) 100 mL into a 1000 mL volume funnel, and transfer the aroma components to the dichloromethane layer. The dichloromethane layer was taken out and dehydrated with anhydrous sodium sulfate. This operation was repeated twice, and the resulting solution was heated in a constant temperature bath at 60 ° C. and concentrated to 0.3 mL. 0.1 mL of an internal standard (Biphenyl 500 ppm) was added to the concentrate to prepare a measurement sample. The measurement was performed twice for each sample. The column used was DB-WAX (30 m × 0.25 mm id × 0.25 μm, manufactured by J & W), and the analytical instrument was a Varian220-MS ion trap GC / MS / MS (manufactured by Varian Technology). The measurement conditions are shown below. Split mode (1:22), inlet temperature 250 ° C, carrier gas He, column initial flow rate 2.4mL / min, oven condition held at 40 ° C for 3 minutes, raised to 230 ° C at 3 ° C / min, then held for 24 minutes did. The MS conditions are shown below. The detector was an ion trap type (EI mode), the measurement was a scan mode, the MS trap temperature was 200 ° C., the transfer temperature was 250 ° C., the mass range was 35 to 500 m / z, and the scan speed was 0.5 sec / scan. The analysis results were analyzed using the analysis software attached to GC / MS and NIST08 for identification.

SPME-GC / MS extracted aroma components include Ethanol, Acetone, Dimethyl sulfide, Ethyl acetate, 3-Methyl-butanal, 2-Methyl-butanal, 2-Pentanone, Acetoin, 3-Methyl-1-butanol, Butanoic acid, 16 components of 2-Heptanone, Hexanoic acid, Limonene, 2-Nonanone, Octanoic acid and Butanoic acid butyl ester were obtained.
SDE-GC / MS extracted aroma components include 2-Undecanone, 2-Tridecanone, Benzyl alcohol, δ-Octalactone, 2-Pentadecanone, δ-Decalactone, Decanoicacid, γ-Undecalactone, δ-dodecalactone, Dodecanoicacid, δ-Tetradecalactone, 13 components of Tetradecanoic acid and Hexadecanoic acid were obtained. Here, the SPME-GC / MS method data was used for the aroma components detected by both the SPME-GC / MS method and the SDE-GC / MS method.

The physical properties of the cheese samples were measured using a texture analyzer (TA-XT2i, Stable Micro Systems Ltd. Germany). Cut a cheese sample into 1cm x 1cm x 1cm cubes and quickly compress the cheese refrigerated at 10 ° C to a compression rate of 0.5mm / sec and a compression rate of 80% using a 75mm diameter probe at room temperature. It was. About hardness and adhesiveness, it is based on the method of the following literature description.

Saint-Eve A. et al., Food Chemistry, 116, 167-175. (2009)

About each sample, sensory evaluation by SD method was implemented about "preference". The evaluators are 30 panelists aged 26 to 54 (17 men and 13 women).
In order to perform PLS regression analysis using the obtained evaluations, all 14 samples are arranged in descending order of “preferred” score, and the 2nd highest (test sample 1) and 8th (test sample 2) The 13th (test sample 3) was used as a test sample, and the remaining 11 samples were divided as calibration samples. The items from the instrumental analysis were used as explanatory variables, and “preference” in sensory evaluation was used as the objective variable for PLS regression. The resulting model had a latent factor of 5, R2 with an RMSEE of 0.080, 0.994, and Q2 with a prediction accuracy of 0.865. As shown in FIG. 1, the scores are arranged on a straight line, and a model that can predict “preference” is obtained. As a result of verifying the model using the test sample, RMSEP was 0.116, which was within 5% of the total score, and it was confirmed that the prediction accuracy was high.
The results of calculating Coefficients by multiple regression analysis for each explanatory variable are shown in FIG. Here, variables whose VIP value is 1 or more are indicated by black bars. As a result, acetoin content and adhesion are selected as factors that contribute positively to “preference”, and ethanol content, butanoic acid content, hexanoic acid content, lactic acid content, hardness Was selected. In the present invention, "preferred" cheese for Japanese is a cheese having high adhesion and low hardness in terms of physical properties, acetoin content, ethanol content, butanoic acid content, hexanoic acid content, The lactic acid content is in a predetermined range.

Table 1 lists the preference scores of the 14 samples in descending order, and shows the instrumental analysis results for each sample. The numbers underlined in the table indicate the minimum value among items that contributed positively, and the items that contributed negatively had negative values. The maximum value is shown. From the above results, the fragrance component acetoin is 1000 μg / kg or more, ethanol is 130 μg / kg or less, butanoic acid is 350 μg / kg or less, hexanoic acid is 130 μg / kg or less, and lactic acid is 1200 mg. / 100g or less, the hardness in the texturer is 5000 gf or less, and the adhesion is 4500 g · s or more.

Examples of the present invention will be described below in detail. In addition, an Example is one of the aspects of this invention, and this invention is not limited to an Example.

The cheese of this example was produced by the following method.
After milking, the raw material milk whose fat content was adjusted to 2.8% by weight was sterilized with a plate-type sterilizer at 75 ° C. for 15 seconds. Here, the time from milking to sterilization was controlled so as not to exceed 48 hours. The obtained raw milk was subjected to ultrafiltration treatment at 40 ° C. using a membrane with a molecular weight cut off of 60000 Da. Lactose, which was 3.6% by weight before membrane treatment, had a fat content of 2.8% by weight in a state of being added to the concentrate, and the lactose content was 1.8% by weight. Milk was processed. Add the LD starter to the raw milk and leave it in a cheese vat with a jacket. One hour later, 3 g of calf rennet (manufactured by Christian Hansen) was added and left still. When about 30 minutes passed, milk coagulation occurred, and after 5 minutes from the start of coagulation, the cheese curd was cut into 10 mm cubes using a cheese knife. After cutting, the whey was poured out from the cheese curd while gently stirring. In order to promote the whey spill, the curd and whey mixture was heated to 38 ° C. with 1 ° C./2 minutes heating. Two hours after the start of stirring, the curd and whey were separated to form a cheese curd. All the cards were put into a 10 kg capacity cheese mold and pressed for 2 hours with a load of 140 kg using a vertical press. After pressing, it was immersed in 20% saline (10 ° C.) for 48 hours to salt, and after salting, it was aged in a 10 ° C. aging cabinet to obtain Gouda cheese as Example 1.

(Comparative Example 1)
In order to confirm the influence of the membrane treatment on the raw milk, the membrane treatment was not carried out in Example 1, milk having a lactose content of 3.6% by weight was used, and the subsequent steps were produced by the same method as in Example 1. The cheese was Comparative Example 1.

Using Lactococcus diacetylactis and Lactococcus cremoris as lactic acid bacteria, membrane-treated milk having a lactose content of 1.8% by weight was produced in the same manner as in Example 1.

(Comparative Example 2)
In order to confirm the influence of the lactose content before salting, non-film-treated milk having a lactose content of 3.6% by weight was used as raw material milk, and a cheese whose other production conditions were the same as in Example 1 was used as Comparative Example 2.

Lactococcus lactis, Streptococcus thermophilus was used as a lactic acid bacterium, cheese prepared using milk having a time from milking to sterilization of 20 hours was set as Example 3, and the lactose content was set to 1.8% by weight by membrane treatment. In the same manner as in No. 1, cheese was prepared.

(Comparative Example 3)
In order to confirm the influence of the time from milking to sterilization, in Example 3, the cheese prepared using the milk whose time from milking to sterilization is 55 hours was set as the comparative example 3.

Lactococcus lactis, Streptococcus thermophilus is used as a lactic acid bacterium, the time from milking to sterilization is 20 hours, no membrane-treated milk is used, and milk with a lactose content of 3.6% by weight is used as a raw material in the same manner as in Example 1. Was prepared.

(Comparative Example 4)
As in Example 4, the membrane-treated milk was not used, milk having a lactose content of 3.6% by weight was used as a raw material, curd and whey were separated, and then the obtained curd was dispersed and mixed with salt. The cheese prepared by putting the curd into a cheese mold with a capacity of 10 kg and pressing it with a vertical press machine for 2 hours under a load of 140 kg was used as Comparative Example 4.

(Comparative Example 5)
Lactococcus diacetylactis and Lactococcus cremoris were used as lactic acid bacteria, and the cheese prepared in the same manner as in Example 1 was added to Comparative Example 5 except that a single flavor of hexanoic acid was added to the curd after whey separation and the mixture was sufficiently stirred. did.

(Comparative Example 6)
Lactococcus diacetylactis and Lactococcus cremoris were used as lactic acid bacteria, a diluted lactic acid solution was added to the curd after whey separation, and the mixture was sufficiently stirred.

(Comparative Example 7)
In order to prepare cheese having hard physical properties as compared with Example 1, using a thermophile, Streptococcus thermophilus, cut the cheese curd into 10 mm cubes and, after cutting, whey from the cheese curd while gently stirring. The cheese adjusted by the same method as Example 1 was made into Example 7 except having promoted the raise of a water | moisture content by raising the whey outflow temperature to 50 degreeC by the process made to flow out.

About Gouda cheese of Examples 1 to 3 and samples of Comparative Examples 1 to 7, parameters determined on the basis of the results of the multiple regression analysis and VIP values, which are related to “preferred” cheese for Japanese, The numerical value of cheese is shown below. The underlined portion in the table indicates a numerical value that is out of the index indicating preference.

Furthermore, sensory evaluation of each Gouda cheese was performed, and the relevance with the results shown in Table 2 was confirmed. “Preferences” were evaluated by a five-step evaluation of -2, -1, 0, +1, +2. Here, -2 is not preferred, and +2 is preferred. The evaluators were 30 panelists aged between 26 and 54 years (17 men and 13 women).
The results of sensory evaluation are as shown in Table 3, and Example 1 had a significant difference (p <0.05) from other comparative examples.

From these results, aroma component acetoin 1000 μg / kg or more, ethanol 130 μg / kg or less, butanoic acid 350 μg / kg or less, hexanoic acid 130 μg / kg or less, lactic acid 1200 mg / 100 g or less It was found that the cheeses of Examples 1 to 4 having a hardness of 5000 gf or less in the texturer analysis and an adhesion of 4500 g · s or more were evaluated to be significantly preferable as compared with Comparative Examples 1 to 7. .
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Claims (2)

The content of acetoin, an aroma component, is 1000 to 3200 μg / kg, the content of ethanol is 100 μg / kg or less, the content of butanoic acid is 350 μg / kg or less, the content of hexanoic acid is 130 μg / kg or less Gouda cheese with a lactic acid content of 1200 mg / 100 g or less, a hardness in the texturer analysis of 5000 gf or less, and an adhesion of 4500 g · s or more. Sterilizing within 48 hours of milking;
A step of reducing the lactose content of raw milk before adding lactic acid bacteria and rennet to 2% or less;
A step of salting brine after card formation;
And having at least two steps,
Acetoin content of 1000-3200 μg / kg, ethanol content of 100 μg / kg or less, butanoic acid content of 350 μg / kg or less, hexanoic acid content of 130 μg / kg or less, lactic acid content A method for producing gouda cheese having an amount of 1200 mg / 100 g or less, a hardness in a texturer analysis of 5000 gf or less, and an adhesion of 4500 g · s or more.
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