KR101991634B1 - Method for Discriminating Organic Milk and Conventional Milk Using Compound-Specific Isotope Analysis - Google Patents

Abstract

The present invention relates to a method for discriminating organic milk and conventional milk by using compound-specific stable isotope analysis. More specifically, the present invention relates to a method for discriminating organic milk and conventional milk by measuring compound-specific stable isotope ratios of fatty acids or amino acids included in milk. According to the present invention, the method for discriminating organic milk and conventional milk by using compound-specific stable isotope analysis confirms that δ^13C values of linoleic acids and myristic acids of milk provide stable year-round threshold values through compound-specific δ^13C and δ^15N analysis of fatty acids and amino acids. Also, it is confirmed that latent structured prediction discriminant analysis (partial least squares-discriminant analysis, PLS-DA) effectively discriminates organic milk. Particularly, it is confirmed that carbon stable isotope values (VIP values 003e#1) of myristic acids, linoleic acids, stearic acids, oleic acids, palmitoleic acids, leucine, methionine, serine, and phenylalanine are useful for the discrimination. It is confirmed that a developed PLS-DA model exhibits excellent model performance for not only organic milk authentication (Q^2 = 0.689) but also organic milk seasonal separation (Q^2 = 0.954) and conventional milk seasonal separation (Q^2 = 0.791).

Description

(Method for Discriminating Organic Milk and Conventional Milk Using Compound-Specific Isotope Analysis)

The present invention relates to a method for distinguishing between organic milk and general milk using the stable isotope analysis of ingredients, and more particularly, to a method for determining the ratio of stable isotopes of fatty acids or amino acids contained in milk to organic milk and general milk The method comprising:

The total global production of organic food was valued at approximately $ 62.9 billion in 2011, and despite the lack of comprehensive statistical data, organic animal products accounted for a large share (International Federation of Organic Agriculture Movements (IFOAM): Bonn, Germany, 2013). Although organic milk is up to 50% more expensive than conventional milk, it has steadily increased its market share in European countries such as Austria, Switzerland and Germany over the past decade, accounting for about 10 to 11% of the total milk market in each country. In addition, Korea's organic milk market has increased 12 times over the past decade to reach $ 60 million worth in 2016 (Molkentin, J., J. Agric. Food Chem. , 57 : 785, 2009; Molkentin, J Giesemann, A., Anal. Bioanal. Chem. , 388: 297, 2007; Ministry of Agriculture, Food and Rural Affairs: Sejong-si, Republic of Korea, 2016).

As the global interest in organic food is heightened, it is possible to protect consumers 'health and producers' interests by tracking accurate organic foods in a complex food chain system. Despite many studies, universal analytical methods for accurate identification of organic foods (Camin, F. et al. , Comp. Rev. Food Sci. Food Saf. , 15: 868, 2006).

For example, changes in milk chemical composition due to differences between specific dairy management systems in feed intake between organic and normal milk are key concepts in organic milk certification (Butler, G. et al. , J. Dairy Sci. , 94 : 24, 2011; Benbrook, CM et al. , PLoS One , 8: e82429, 2013).

Thus, to ensure food safety / quality and to protect both consumers and organic producers from fraudulent organic labeling, research has focused on milk component analysis for organic milk certification. In particular, the concentration of nutritionally favorable milk components such as? -Tocopherol,? -Carotene and / or? -Linoleic acid (ALA, threshold: 0.5%) was characteristic of organic milk.

Among several tools that can be applied to organic milk certification, we have found alternative and reliable means of certifying organic plant and animal products and have found that stable isotope ratio analysis such as carbon, nitrogen or sulfur ; SIRA) has recently been increasingly studied, and isotope analysis is greatly influenced by the components contained in cattle feeds made from other plant sources, so the value of δ ¹³ C in milk is an important marker of organic milk certification (I.e., C3 to C4 type plants). In contrast, δ ¹⁵ N is due to the relatively δ ¹⁵ N range (legumes 1.2 ‰ commercial concentrate was 3.3 ‰ to in) is narrow in, can be considered to be less useful isotope relatively in livestock animal products and in animal feed According to previous studies extensively conducted in Germany, German retail organic milk was always below the maximum δ ¹³ C threshold of -26.5 ‰, but the maximum δ ¹⁵ N threshold never exceeded 5.5 ‰ (Molkentin, J. et al. . J. Agric Food Chem, 57: 785, 2009; Molkentin, J. et al, Anal Bioanal Chem, 398:......... 1493, 2010; Schwertl, M. et al, Agric Ecosyst Environ, 109: 153, 2005).

In addition, the time-resolved mean δ ¹³ C difference between organic milk and normal milk was 4.5 ‰, δ ¹³ C _fat and δ ¹³ C _protein were suitable for organic milk certification, and δ ¹³ C _fat and δ ¹³ C _proteins showed a high correlation (r = 0.99). In another study, the δ ¹³ C threshold for organic milk certification in Italy was -23.5 ‰, which indicates the presence of corn and / or by-products in cattle feed sources (Camin, F. et al. Rapid Commun. Mass Spectrom. , 22: 1690, 2008).

The previous studies of the present inventors confirmed that the average values of δ ¹³ C and δ ¹⁵ N were lower in organic milk than that of normal milk, and that successful discrimination was possible, and time resolution using δ ¹³ C and δ ¹⁵ N 2D plots -resolved comparisons clearly distinguished between organic milk and normal milk, and overcome monthly and seasonal fluctuations of δ ¹³ C and δ ¹⁵ N in organic milk certification. In addition, the present inventors have quantitative chemical model based on the development of α- linolenic acid (α- linoleic acid; ALA) and linoleic acid; was found to be (linoleic acid LA) is the most important chemical markers in organic milk certified, δ ¹³ C is South Korea Kim et al. , Food Chem. , 261: 112, 2018; Chung, I.-M .; Park, I .; Yoon , J.-Y. et al. , Food Chem. , 160: 214, 2014).

On the other hand, the isotopic characteristics of C4 grass (ie, δ ¹³ C) or soybean plants (ie, δ ¹⁵ N) used in organic agricultural production are similar to corn feeds or conventionally produced synthetic fertilizers, respectively. Thus, the use of C4 grass or soybean plants in organic farming has the problem of making organic certification difficult.

Because compound-specific isotope analysis (CSIA) produces more in-depth molecular information for potentially given samples, as compared to bulk isotopic analysis of tissue and biomaterials, recent strong and reliable technology As a result, I became interested in various food discrimination areas. In particular, isotopic analysis of fatty acids and amino acids can be a promising analytical tool because these primary metabolites form an important part of living organisms, resulting in a variety of synthetic pathways and biochemical uses resulting in δ ¹³ C and It may reflect the combined amount of δ ¹⁵ N efficiently.

Δ ¹³ C and δ ¹⁵ N analyzes of milk fat or protein (casein) fractions were all applied for organic milk certification, but no method of organic milk certification using component isotopes has been studied. In addition, despite the continued expansion of the Korean organic milk market, the present inventors have found that in previous studies (Chung, IM et al. , Food Chem. , 261: 112, 2018; Chung, I.-M. ; Yoon, J.-Y. et al. , Food Chem. , 160: 214, 2014) failed to establish a reliable annual δ ¹³ C or δ ¹⁵ N threshold for organic milk certification.

Accordingly, in the present invention, organic milk sold in the Korean retail market is collected and analyzed for δ ¹³ C and δ ¹⁵ N for each component of fatty acid and amino acid for certifying organic milk during the year, thereby clearly discriminating organic milk and general milk sought results, linoleic acid and δ ¹³ C values of myristic acid in milk is a reliable year-round activity (year-round threshold values) it was confirmed that, isoleucine, leucine, methionine, phenylalanine, proline, serine and valine in δ ¹³ provides for C values were found to be useful for discriminating between normal and organic milk.

In addition, the results of the potential structural analysis (PLS-DA) showed that δ ¹³ C _{myristic acid} , δ ¹³ C _{linoleic acid} and δ ¹³ C _{stearic acid} values (VIP value> 1) Confirmed that the PLS-DA model showed excellent model performance for organic milk separation (Q ² = 0.954) and general milk seasoning (Q ² = 0.791), as well as organic milk certification (Q ² = 0.689) Thus completing the present invention.

It is an object of the present invention to provide a method for distinguishing organic milk and general milk using stable isotope analysis by fatty acid or amino acid component.

It is still another object of the present invention to provide a method of discriminating organic milk and general milk using a stable least-squares discriminant analysis (PLS-DA) and a stable borin element analysis by fatty acid or amino acid component.

In order to achieve the above object,

(a) obtaining linoleic acid or myristic acid in a sample of milk and measuring carbon stable isotope consumption;

(b) measuring each isotope index according to Equation (3) using carbon stable isotope consumption of the linoleic acid or myristic acid; And

&Quot; (3) "

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) if the isotope index of _{linoleic acid} (隆¹³ C _{linoleic acid} ) is -31.5 to -33.5 ‰, or the isotopic index of myristic acid (δ ¹³ C _{myristic acid} ) is -27.0 to -28.0 ‰, ;

And a method of distinguishing between organic milk and general milk.

(A) obtaining a fatty acid or an amino acid component by ingredient in the organic milk and the general milk sample which have been judged, and measuring the carbon-stable isotope consumption of each ingredient;

(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;

&Quot; (3) "

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And

(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining whether the unknown milk sample is organic milk or general milk by applying the standard model of step (c);

And a method for distinguishing organic milk and general milk using the stable isotope analysis of each component.

In a preferred embodiment of the present invention, the fatty acid of step (a) is selected from the group consisting of myristic acid, linoleic acid, stearic acid, oleic acid and palmitoleic acid ). ≪ / RTI >

In another preferred embodiment of the present invention, the amino acid of step (a) may be any one selected from the group consisting of leucine, methionine, serine, and phenylalanine.

In another preferred embodiment of the present invention, the quality parameter value by the partial least-squares discriminant analysis (PLS-DA) analysis of step (c) is R ² X = 0.547, R ² It may be Y = 0.865 and Q ² = 0.689.

The present invention also relates to a method for preparing an organic milk or milk milk, comprising the steps of: (a) obtaining a fatty acid or an amino acid component by ingredient in an organic milk or a general milk sample obtained every season, and measuring a carbon-

(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;

&Quot; (3) "

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And

(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining a production season of an unknown milk sample by applying the standard model of step (c);

The present invention provides a method for discriminating the production season of organic milk or general milk using the component-based stable isotope analysis.

In a preferred embodiment of the present invention, in the case of production seasonal determination of organic milk, the fatty acid in step (a) may be one or more selected from the group consisting of oleic acid, palmitoleic acid and iso-pentadecanoic acid, The amino acid of step a) may be one or more selected from the group consisting of valine, threonine, isoleucine, lysine, glycine, leucine, alanine, proline and glutamic acid.

In another preferred embodiment of the present invention, in the case of production seasonal determination of general milk, the fatty acid in step (a) may be palmitoleic acid or myristic acid, and the amino acid in step (a) may be threonine, aspartic acid , Valine, isoleucine, leucine, lysine, and proline.

In another preferred embodiment of the present invention, the quality parameter value by the partial least-squares discriminant analysis (PLS-DA) analysis of step (c) is R ² X = 0.678, R ² Y = 0.990 and Q ² = 0.954, and in the case of ordinary milk, R ² X = 0.683, R ² Y = 0.929 and Q ² = 0.791.

Determining method of the organic milk and cow's milk using the stable isotope analysis-specific components of the present invention are fatty acid and amino acid components by δ ¹³ C and δ ¹⁵ N analyze the δ ¹³ C value of the linoleic acid and myristic acid in milk is stable throughout the year by To provide year-round threshold values.

In addition, a potential structural identification identification analysis (PLS-DA) confirmed the effective discrimination of organic milk. In particular, it was found that the carbon stable isotopic values (VIP value> 1) of myristic acid, linoleic acid, stearic acid, oleic acid, palmitoleic acid, leucine, methionine, serine and phenylalanine were useful for discrimination. -DA model showed good model performance for organic milk separation (Q ² = 0.954) and general milk seasoning (Q ² = 0.791) as well as organic milk certification (Q ² = 0.689).

1 is a graph showing the results of bulk isotope consumption (‰) and isomer consumption (‰) of fatty acid and amino acid components for all organic milk (OM) and conventional milk (CM) The difference is manifested. Bars mean mean ± standard deviation (n = 12 for each milk type).
FIG. 2 compares isotopic values of selected fatty acids and amino acids of organic milk and general milk with monthly milk sample functions. Results are expressed as mean ± standard deviation (n = 3 for each milk type per month sample). The blue dotted line shows the potential threshold for organic certification within one year without statistical analysis (ns: not significant).
Figure 3 is a correlation matrix and hierarchical clustering analysis (HCA) data based on δ ¹³ C values and δ ¹⁵ N values for bulk and amino acid or fatty acid components of organic milk and general milk samples, Each quadrangle represents a Pearson's correlation coefficient for a pair of compounds, and the value of the correlation coefficient represents the intensity of green or red as indicated in the scale.
FIG. 4 shows the results of PLS-DA induced by milk bulk and constituents? 13C and? 15N, with organic milk certification for normal milk. Score plot (A), loading plot (B) in PLS-DA, variability (C) of VIP values obtained in the PLS-DA model and external validation test (D). The ellipse on the score graph represents the 95% confidence interval for Hotelling's T ² .
5 is derived from all bulk and constituent δ ¹³ C and δ ¹⁵ N values of milk for milk seasonal discrimination in organic milk (A: score plot, B: loading plot, C: VIP value, PLS-DA results.
Figure 6 is derived from all bulk and constituent δ ¹³ C and δ ¹⁵ N values of milk for milk seasonal discrimination in general milk (A: score plot, B: loading plot, C: VIP value, PLS-DA results.

Hereinafter, the present invention will be described in detail.

As described above, δ ¹³ C and δ ¹⁵ N assays of milk fat or protein (casein) fractions were applied for the determination of organic milk. However, there has not been studied an organic milk authentication method using isotopes of components, and organic milk A reliable annual δ ¹³ C or δ ¹⁵ N threshold for authentication was not established.

Thus, in the present invention, the above-mentioned problems were solved by measuring values of δ ¹³ C and δ ¹⁵ N for each fatty acid or amino acid of milk. Analysis of δ ¹³ C and δ ¹⁵ N values by fatty acid and amino acid components As a result, it was confirmed that the δ ¹³ C values of linoleic acid and myristic acid in milk provide stable year-round threshold values. In addition, the results of the analysis by the potential structure prediction analysis (PLS-DA) showed that not only organic and general milk can be effectively discriminated, but also milk production season can be discriminated.

Therefore,

(a) obtaining linoleic acid or myristic acid in a sample of milk and measuring carbon stable isotope consumption;

(b) measuring each isotope index according to Equation (3) using carbon stable isotope consumption of the linoleic acid or myristic acid; And

&Quot; (3) "

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) if the isotope index of _{linoleic acid} (隆¹³ C _{linoleic acid} ) is -31.5 to -33.5 ‰, or the isotopic index of myristic acid (δ ¹³ C _{myristic acid} ) is -27.0 to -28.0 ‰, ;

And a method of distinguishing between organic milk and general milk.

In a specific example of the present invention, organic and generic milk produced by the same manufacturer for the discrimination of organic and general milk were collected each season (April, July, October and January 2016) , And δ ¹³ C and δ ¹⁵ N values of each milk sample were measured. As shown in Table 1, the average of δ ¹³ C _bulk and δ ¹⁵ N _bulk was significantly influenced by milk type, sample collection month and interaction effect (type X month). Organic milk showed lower δ ¹³ C _bulk and δ ¹⁵ N _bulk mean values than ordinary milk, and summer milk collected in July 2016 was found to have a low δ ¹³ C _bulk value. On the contrary, the δ ¹³ C _bulk value of winter milk collected from winter of January, 2017 was higher.

In addition, as shown in Table 2, all δ ¹³ C _{fatty acid} values except for palmitic acid were lower in organic milk than in normal milk. Except for myristic acid and stearic acid, most of δ ¹³ C _{fatty acid} values were observed to change monthly. In particular, the δ ¹³ C _{fatty acid} values of milk collected in July 2016 were found to be slightly higher than the other sampling months investigated in the present invention.

Also, when compared to the δ ¹³ C _bulk value, isotope fractionation was observed in all δ ¹³ C _{fatty acids} in both the general milk and the organic milk investigated in the present invention. Despite the lack of statistical significance, it was found that isotopic fractionation was higher in organic milk than normal milk, except for δ ¹³ C _{palmitic acid} (Fig. 1). Isotope fractionation was observed to occur at a minimum of -5.6 ‰ in δ ¹³ C _{myristic acid} of normal milk and up to 14.7 ‰ in δ ¹³ C _{oleic acid} of organic milk.

The δ ¹³ C _{amino acid} values of isoleucine, leucine, methionine, phenylalanine, proline, serine, and valine were significantly higher in general milk than in organic milk, and all δ ¹³ C _{amino acid} values except for phenylalanine were found to change with age . The age variation patterns were born variously displayed according to the individual amino acids, e.g., methionine, and proline of the δ ¹³ C value of the summer milk which was found higher in July, 2016, of alanine, glycine and threonine δ ¹³ C values were higher in January 2017, the winter milk (Table 3).

All δ ¹⁵ N _{amino acid} values except for phenylalanine, serine and threonine were found to be insufficient for discrimination between normal milk and organic milk. In addition, the δ ¹⁵ N _{amino acid} values of alanine, glutamic acid, glycine, leucine, lysine, proline and valine showed significant changes in age. Compared with other seasonal milk samples, winter milk samples collected in January 2017 showed higher δ ¹⁵ N _{amino acids} , while summer milk samples collected in July 2016 showed lower δ ¹⁵ N _{amino acids} . The interaction effect (type X month) was observed only in δ ¹⁵ N _lysine (Table 4). Isotope fractionation of amino acids varied depending on the _{amino acids} and showed the largest change in δ ¹³ C _{amino acid} (-7.2 ‰ ~ 9.8 ‰) compared to δ ¹⁵ N _{amino acid} (-5.6 ‰ ~ 3.8 ‰) I confirmed it. The fractionation effect showed that most of the amino acids were higher in organic milk than in normal milk, and the δ ¹³ C values of isoleucine, lysine, methionine, serine and valine were opposite to δ ¹⁵ N values (Fig. 1).

No clear monthly δ ¹³ C _{fatty acid} and δ ¹³ C _{amino acid} change patterns were observed in organic milk and normal milk samples. However, the difference in δ ¹³ C values of myristic acid, stearic acid, oleic acid and linoleic acid in organic and general milk was found to be higher in summer milk (July 2016) compared to the other seasons (Table 2). Figure 2 shows a representative time-resolved comparison of δ ¹³ C and δ ¹⁵ N in organic and general milk, and similar to previous studies by the present inventors, bulk isotope data analysis of milk was conducted throughout the year But did not provide a single threshold for organic milk certification.

However, as shown in Figures 2A and 2B, δ ¹³ C _linoleic exhibited a threshold value of approximately -33.5 ‰, δ ¹³ C _myristate was confirmed that the visible threshold of about -28 ‰, any season , It was confirmed that it clearly distinguished organic milk and general milk. That is, if the isotope index of _{linoleic acid} (隆¹³ C _{linoleic acid} ) is -31.5 to -33.5 ‰, or the isotopic index of myristic acid (δ ¹³ C _{myristic acid} ) is -27.0 to -28.0 ‰, .

In addition, although δ ¹³ C _leucine showed a time-dependent discrimination between organic milk and normal milk, it was not possible to set annual thresholds for organic milk certification using these parameters (Fig. 2C), δ ¹³ C _{stearic acid} Confirmed that organic milk could be discriminated except for April 2016 (Fig. 2D). The δ ¹³ C values of isoleucine and valine were found to be acceptable for milk collected in January 2017, although organic milk identification was possible from April to October 2016 (see Table 3, Figure 2E and Figure 2F ).

Figure 3 of the present invention shows that Pearson correlation and HCA show three major cluster of compounds, group A is all δ ¹³ C _{fatty acids} (except oleic acid), δ ¹⁵ N _bulk and aspartic acid, methionine, phenylalanine, glutamic acid and proline δ ¹³ C was comprising the _{amino acid} values. Group B contained only δ ¹⁵ N _{amino acid} values of isoleucine, methionine, and phenylalanine, while Group C contained mainly δ ¹³ C _{amino acids} , δ ¹⁵ N _{amino acids} and δ ¹³ C _bulk values. δ ¹³ C _bulk value of δ ¹³ C _{oleic acid} values (r = 0.77; P <0.0001 ) and the δ ¹³ _C-alanine values (r = 0.92; P <0.0001 ) was the naeteot appear to be highly correlated, lysine, leucine and the valine δ ¹⁵ N values (r = 0.51; P <0.05), respectively. In contrast, the value of δ ¹⁵ N showed a weak correlation with the elemental isotopic values of other components. The δ ¹⁵ N _bulk values correlated with δ ¹³ C _{palmitoleic acid} values (r = 0.42; P <0.05) and δ ¹³ C values of isoleucine, lysine, threonine and valine (r = 0.51; P <0.05) .

In the isotopes of fatty acids and amino acids, δ ¹³ C values of myristic acid, stearic acid and linoleic acid were significantly correlated (r>0.86; P <0.0001), δ ¹³ C _valine and δ ¹³ C _isoleucine ( r = 0.98; P <0.0001), δ ¹³ C _isoleucine and δ ¹³ C _leucine ( r = 0.89; P <0.0001), δ ¹⁵ N _threonine and δ ¹⁵ N _serine ( r = 0.90; P < Were strongly correlated with each other.

δ ¹³ C _aspartate showed a negative correlation with the δ ¹³ C values of isoleucine, leucine, lysine, threonine and valine (r ≤ -0.57; P <0.05), while δ ¹³ C _{phenylalanine} showed δ ¹³ C _{oleic acid} except showed a correlation of all the δ ¹³ C _{fatty acid} value and a negative (r ≤ -0.66; P <0.05 ). The correlation between isotopic values for fatty acids and amino acid components is as follows:

δ ¹³ C _{iC15: 0 (iso-penta teka acid)} and δ ¹³ _C-alanine (r = -0.79; P <0.0001 );

? ¹³ C _{oleic acid} and? ¹³ C _serine ( r = 0.76; P <0.0001);

? ¹³ C _glycine and? ¹⁵ N _lysine ( r = 0.70; P <0.0001);

δ ¹³ C _proline and δ ¹⁵ N _lysine / δ ¹⁵ N _valine ( r = -0.63; P <0.01).

Previous studies have shown that the δ ¹⁵ N _bulk value of German retail organic milk did not exceed 5.50 ‰, which is considered the maximum threshold, and that milk production methods (general and organic) in the time series during the year 18 months (Molkentin, J. and Giesemann, A. Anal. Bioanal. Chem. , 398: 1493, 2010). In addition, in a one-year case study in Korea, despite the statistical differences between organic milk (mean δ ¹⁵ N: 4.85 ‰) and common milk (mean δ ¹⁵ N: 5.08 ‰), organic milk (4.39 to 5.40 ‰) (Chung, IM et al. , Food Chem. , 261: 112, 2018), because the δ ¹⁵ N _bulk values of milk (4.69 ‰ to 5.31 ‰) overlap. In other studies, it has been reported that δ ¹⁵ N _bulk or δ ¹⁵ N _casein is inadequate for the determination of food intake related to corn content (Camin, F. et al. , Rapid Commun. Mass Spectrom. , 22: 1690, 2008; , N. et al. , Anal. Bioanal. Chem. , 386: 104, 2006).

The above-mentioned findings are consistent with the results of the present invention, which reported an inadequacy of the δ ¹⁵ N _bulk value for organic certification, due to the small overlap of δ ¹⁵ N values between organic milk and normal milk and considerable overlap. Unlike the previous maximum value of δ ¹⁵ N of 5.50 ‰ in Germany, the present invention fails to derive an annual threshold that can be applied to δ ¹³ C and δ ¹⁵ N values for all bulk and amino acid components. However, by comparing the time decomposition of δ ¹³ C _leucine , we have clearly distinguished organic milk and plain milk for several months (January, April, July, and October) that represent four seasons in Korea. In addition, δ ¹³ C _isoleucine and δ ¹³ C _valent values were confirmed to be applicable to the determination of organic milk except for the milk produced during the winter season of January 2017 (FIG. 2).

In addition, in the present invention, the δ ¹³ C _{fatty acid} value was mostly depleted by ¹³ C more than the δ ¹³ C _{amino acid} value, indicating that the δ ¹³ C _casein value due to the specific isotope fractionation during lipid synthesis in plants and animals Lower δ ¹³ C _fat values are similar to previous studies (Camin, F. et al. , Rapid Commun. Mass Spectrom. , 22: 1690, 2008). Comparing the δ ¹³ C _bulk and δ ¹⁵ N _bulk values of milk, the fractionation of δ ¹³ C _fatty acids tends to increase with increasing fatty acid length and higher unsaturation, while the δ ¹³ C and δ ¹⁵ N The fractionation did not show any specific sorting tendency in the present invention. Furthermore, fractionation of alanine, aspartic acid, glutamic acid, glycine and proline may δ ¹³ C _bulk and δ ¹⁵ N, while the _bulk is δ ¹³ C and δ ¹⁵ N value increases in proportion to, leucine and threonine fractionation is δ ¹³ C and δ ¹⁵ N (FIG. 1). The results are similar to previous studies describing dietary-tissue isotopic differentiation of different amino acids in the same tissue (Edgar Hare, P. et al. , J. Archaeol. Sci. , 18: 277, 1991) .

A strong correlation between δ ¹³ C _protein and δ ¹³ C _fat (r = 0.99) and δ ¹³ C _protein and δ ¹⁵ N _bulk (r = 0.66) from the milk samples obtained was confirmed in previous studies (Molkentin, J. and Giesemann, A. Anal. Bioanal. Chem. , 398: 1493, 2010). The results were in part similar to the results of the present invention illustrating the correlation (≤ 0.51; P <0.05) between δ ¹³ C of δ ¹⁵ N _bulk and isoleucine, lysine, threonine and valine in milk. In contrast, δ ¹³ C _iso- pentatecanoic _acid and δ ¹³ C _alanine (r = -0.79; P <0.0001) as well as δ ¹³ C _{phenylalanine} and most δ ¹³ C _{fatty acid} values (r ≤ -0.66; ) Were observed. Thus, the similarity / dissimilarity of these correlations can explain the complexity of how the isotopic fraction is affected during milk production by assimilation / metabolism of fatty acids and amino acids and feed.

(A) obtaining a fatty acid or an amino acid component by ingredient in the organic milk and the general milk sample which have been judged, and measuring the carbon-stable isotope consumption of each ingredient;

(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;

&Quot; (3) &quot;

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And

(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining whether the unknown milk sample is organic milk or general milk by applying the standard model of step (c);

And a method for distinguishing organic milk and general milk using the stable isotope analysis of each component.

In the present invention, the fatty acid in step (a) may be selected from the group consisting of myristic acid, linoleic acid, stearic acid, oleic acid and palmitoleic acid. And the like.

In the present invention, the amino acid of step (a) may be any one selected from the group consisting of leucine, methionine, serine, and phenylalanine.

In the present invention, the quality parameter values by the partial least-squares discriminant analysis (PLS-DA) analysis of step (c) are R ² X = 0.547, R ² Y = 0.865 and Q ² = 0.689.

In another specific embodiment of the present invention, the stable isotope data obtained above are used for partial iso-squares discriminant analysis (ANOVA) to select reliable isotope markers that can distinguish organic milk and general milk. PLS-DA).

The supervisory analysis PLS-DA based on the PLS model is a projection method that rotates the principal component analysis to divide the observation group as much as possible and is considered to be a suitable method for distinguishing the milk type and the sampling season (FIGS. 4 to 6). The PLS-DA model evaluation parameters consist of R ² X, R ² Y and Q ² , respectively, which represent the description, suitability and predictability. Therefore, in the present invention, R ² X means the percentage of all the isotope variables described by the model. In particular, since most of the δ ¹⁵ N _{amino acid} values are low (Table 4), δ ¹⁵ N _{amino acid} values were not used in the development of the PLS-DA model in the present invention. R ² Y means all observations or percentages of the sample variables described by the model, and Q ² means all observations predicted by the model or a percentage of the sample variable.

As shown in Figure 4A, the PLS-DA score plot showed clear clustering, with the highest ranked two PCs accounting for 46.9% of the total variance in the data set. In particular, the first major component, which accounts for 29.2% of total variance, isotope characterization of organic milk and general milk. In the PLS components 1, the largest contributing factor was the higher δ ¹³ C _{fatty acid} levels in cow's milk than organic milk, were each represented by δ ¹³ C of 0.397 and δ ¹³ of _myristic C _linoleic 0.395 eigenvalues (Fig. 4B). Also, the VIP value describes the extent to which the variable contributes to the projection, and one or more VIP values are typically used as a reference to identify variables that are important to the model. Thus, as shown in FIG. 4C, the nine variables including the most important δ ¹³ C _{myristic acid} (VIP: 1.806), δ ¹³ C _{linoleic acid} (VIP: 1.796) and δ ¹³ C _{stearic acid} It was observed as a significant isotopic feature to discriminate milk.

The PLS actively applies the data to the model, almost always separates the class, and the validation is an important step in securing the reliability of the developed PLS model. Although there is no comparison criterion or threshold for inferring significance, Q ^{2, which} is a quality assessment statistic, is generally reported as a result of cross validation. Generally, a Q ² value higher than the 0.5 threshold is good for the developed model It means predictability. As shown in FIG. 4D, in the external verification, the entire data was divided into a training set (n = 19) and a test set (n = 5), and the test set was used to evaluate the model performance quality. The PLS-DA model proposed in the present invention showed good performance (R ² X = 0.547 R ² Y = 0.865 and Q ² = 0.689).

Further, the present invention relates to a method for preparing a milk product, comprising the steps of: (a) obtaining a fatty acid or an amino acid component by ingredient in an organic milk or a general milk sample obtained seasonally, and measuring a carbon stable isotope consumption per ingredient;

(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;

&Quot; (3) &quot;

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And

(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining a production season of an unknown milk sample by applying the standard model of step (c);

The present invention provides a method for discriminating the production season of organic milk or general milk using the component-based stable isotope analysis.

In the present invention, in the case of production seasonal determination of organic milk, the fatty acid in step (a) may be at least one selected from the group consisting of oleic acid, palmitoleic acid and iso-pentadecanoic acid. ) Amino acid is at least one selected from the group consisting of valine, threonine, isoleucine, lysine, glycine, leucine, alanine, proline and glutamic acid.

In the present invention, in the case of production seasonal determination of general milk, the fatty acid in step (a) may be palmitoleic acid or myristic acid. The amino acid of step (a) may be threonine, aspartic acid, valine , Isoleucine, leucine, lysine, and proline.

In the present invention, the quality parameter value by the partial least-squares discriminant analysis (PLS-DA) analysis of step (c) is R ² X = 0.678 and R ² Y = 0.990 and Q ² = 0.954, and in the case of ordinary milk, R ² X = 0.683, R ² Y = 0.929 and Q ² = 0.791.

In another specific embodiment of the present invention, the PLS-DA model of the present invention showed a relatively clear separation between organic milk and normal milk samples (FIGS. 5 and 6). PLS component 1 had a significant impact on the separation of the organic milk and general milk sampling seasons (April / January and July / October), while PLS component 2 had a significant effect on summer (July) and autumn Month) milk samples were effectively classified as organic milk or normal milk. Overall, the R ² X, R ² Y and Q ² parameters in the developed PLS-DA model were 0.678, 0.990 and 0.954 for organic milk and 0.683, 0.929 and 0.791 for common milk, respectively. In particular, the δ ¹³ C values of valine and threonine have been identified as important components for clear seasonal separation of organic milk and common milk (Figures 5 and 6, VIP of organic milk: δ ¹³ C _valine 1.401, δ ¹³ C _threonine 1.394; Normal milk VIP value: δ ¹³ C _valine 1.450, δ ¹³ C _threonine 1.551).

As shown in Figure 5, in the case of the production season determination of organic milk, δ ¹³ _C-valine, δ ¹³ _C-threonine, δ ¹³ _{C-isoleucine,} δ ¹³ _C-lysine, δ ¹³ C _glycine, δ ¹³ C _{Oleic acid,} δ ¹³ C _{palmitate It} was confirmed that the VIP value of _tolestone , δ ¹³ C _leucine , δ ¹³ C _alanine , δ ¹³ C _proline , δ ¹³ C _{glutamic acid} and δ ¹³ C _{iso-pentatecanoic acid} was 1 or more. As shown in FIG. 6, in the case of the production season determination, δ ¹³ _C-threonine, δ ¹³ _{C-aspartic acid,} δ ¹³ _C-valine, δ ¹³ _{C-isoleucine,} δ ¹³ _C-leucine, δ ¹³ _C-lysine, δ ¹³ C _{palmitoleic resan,} δ ¹³ C _myristic it was confirmed that the _acid value of the VIP and the δ ¹³ _C-proline 1 or more.

In general, principal component analysis (PCA), potential structural identification analysis (PLS-DA), and orthogonal projection to latent structure-discriminant analysis (ANOVA) are used to identify organic milk and general milk. OPLS-DA, meta analysis, and redundancy analysis are used. In this paper, we propose a linear discriminant analysis (OCR) method, which is a supervised pattern recognition method that minimizes the ratio between classes and maximizes the ratio between classes. , LDA) were found to enhance the discriminating ability of organic wheat (Paolini, M .; Ziller, L. et al. , J. Agric. Food Chem., 2015, 63 , 5841-5850).

In an earlier study (Chung, IM et al. , Food Chem. , 261: 112, 2018), the OPLS-DA model based on bulk isotopes, fatty acids and tocopherol profiling data showed that alpha-linolenic (Q ² = 0.969) for identifying organic milk using important markers such as acid and linolenic (VIP value> 1), and showed relatively good seasonal separation except spring iron . However, the model has a problem that the predictive power for seasonal discrimination is weak in organic milk (Q ² = 0.4863) and general milk (Q ² = 0.433).

The PLS-DA model developed through isotope analysis of fatty acids and amino acid components of the present invention clearly distinguished seasonal separation of organic milk (Q ² = 0.954) and general milk (Q ² = 0.791). δ ¹³ C _valine and δ ¹³ C _threonine value (VIP value> 1) were the most important markers of milk seasonal discrimination.

In the present invention, δ ¹³ C and δ ¹⁵ N analyzes of fatty acids and amino acids contained in milk were performed to improve the organic certification, and the δ ¹³ C values of linoleic acid and myristic acid were compared with a stable year- round threshold values. In addition, a potential structural identification identification analysis (PLS-DA) confirmed the effective discrimination of organic milk. In particular, it was found that the carbon stable isotopic values (VIP value> 1) of myristic acid, linoleic acid, stearic acid, oleic acid, palmitoleic acid, leucine, methionine, serine and phenylalanine were useful for discrimination. -DA model showed good model performance for organic milk separation (Q ² = 0.954) and general milk seasoning (Q ² = 0.791) as well as organic milk certification (Q ² = 0.689).

Hereinafter, the present invention will be described in more detail with reference to Examples.

It is to be understood by those skilled in the art that these embodiments are merely illustrative of the present invention and that the scope of the present invention is not construed as being limited by these embodiments.

Stable isotope analysis of milk bulk

1-1: Milk sample collection

Organic milk and common milk (2 liters, n = 3, respectively) produced by the same manufacturer were collected in April, July, October, and January, 2016, All milk production and processing, such as cleanliness, homogenization and pasteurization, were performed according to previously known methods (Molkentin, J. and Giesemann, A. Anal. Bioanal. Chem. , 388 : 297, 2007; Chung, IM et al. , Food Chem. , 261: 112, 2018).

The organic milk collected from the above was produced in accordance with the Law on the Management and Support of Environmentally Friendly Rural Fisheries and Organic Foods issued in Korea and was certified by the International Organic Movement Federation (IFOAM). In addition, organic milk samples were certified by an inspection agency designated by the Korean Agricultural Products Quality Management Authority before being sold in the retail market.

A total of 24 milk samples were frozen at -70 ° C and then lyophilized at about -40 ° C prior to δ ¹³ C and δ ¹⁵ N analysis by fatty acid and amino acid composition.

1-2: Bulk δ ¹³ C  And δ ¹⁵ N  analysis

For each of the bulk δ ¹³ C and δ ¹⁵ N analyzes, each lyophilized milk sample (about 2 mg) obtained in Example 1-1 was dissolved in a tin capsule (3.5 mm × 17 mm, IVA Analysentechnik eK, Dusseldorf , Germany) and analyzed with an elemental analysis (EA, Elementar Analysensysteme GmbH, Hanau, Germany) combined with isotope ratio mass spectrometry (IRMS, Isoprime Ltd., Stockford, UK) . The δ ¹³ C and δ ¹⁵ N values were expressed as one thousandth (‰) as an international standard, and the isotope index (δ) was measured according to the following equations (1) and (2)

[Equation 1]

隆¹³ C _bulk (‰) = [(R _bulk / R _{standard sample} ) - 1] × 1000

The R _bulk is the total carbon stable isotope consumption ( ¹³ C _bulk / ¹² C _bulk ) of the milk sample and the R _{standard sample} is the international standard value (carbon: VPDB (Vienna Pee Dee Belemnite).

&Quot; (2) &quot;

δ ¹⁵ N _bulk (‰) = [(R _bulk / R _{standard sample} ) - 1] × 1000

The R _bulk is the total nitrogen stable isotope consumption of the milk sample ( ¹⁵ N _bulk / ¹⁴ N _bulk ) and the R _{standard sample} is the international standard value (nitrogen: atmospheric N ₂ value).

Statistical analysis was performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA) and the most significant difference test was performed at a 0.05 probability level. The δ ¹³ C and δ ¹⁵ N values of laboratory standards (small liver, nylon 5) previously calibrated against international reference materials (IAEA-N1, IAEA-N2, IAEA-N3, USGS-40 or USGS- , -21.69 ‰ and 7.72 ‰ in the liver of cattle, -27.72 ‰ and -10.31 ‰ in nylon 5, respectively. In the present invention, the analytical accuracy of the δ ¹³ C and δ ¹⁵ N measurements was confirmed to be within ± 0.1 ‰ in the form of ± standard deviation as compared with the laboratory reference material.

Bulk δ ¹³ C and δ ¹⁵ N values of organic milk and general milk collected in Korea between 2016 and 2017
Organic milk Plain milk April 2016 July 2016 October 2016 January 2017 Average April 2016 July 2016 October 2016 January 2017 Average δ ¹³ C _bulk -22.26 -23.55 -22.50 -21.38 -22.43 -21.90 -22.19 -22.13 -21.91 -22.03 δ ¹⁵ N _bulk 4.40 4.92 5.40 5.05 4.94 4.81 5.24 5.24 5.30 5.15

As shown in Table 1, the average of δ ¹³ C _bulk and δ ¹⁵ N _bulk was significantly influenced by milk type, sample collection month and interaction effect (type X month). Organic milk showed lower δ ¹³ C _bulk and δ ¹⁵ N _bulk mean values than ordinary milk, and summer milk collected in July 2016 was found to have a low δ ¹³ C _bulk value. On the contrary, it was confirmed that δ ¹³ C _bulk value of winter milk collected from winter of January, 2017 is higher.

Isotopic analysis of fatty acids in milk

2-1: Preparation of chemicals and reagents

12.1 M hydrochloric acid (HCl), 50 vol% NaOH and HPLC grade methanol from ACS (American Chemical Society) grade were purchased from Thermo Fisher Scientific (USA) for acid hydrolysis and derivatization. 2,2-dimethoxypropane (DMP), methyl chloroformate, pyridine, anhydrous sodium sulfate, and triethylamine can be used in combination with Sigma-Aldrich (Sigma-Aldrich, USA).

Acetyl chloride and anhydrous ethyl acetate were purchased from Acros Organics, Belgium, and acetic anhydride was purchased from Alfa Aesar, USA . Sulfuric acid (H2SO4) was purchased from Daejung Chemical & Materials Co., Ltd., Korea, and benzene and heptane were purchased from Junsei, Japan.

All internal standards and chemical standards used in calibration, scale standardization and quality assurance are 99% pure fatty acid methyl esters (FA) and 98% pure L-amino acids (AAs) Were purchased from Matreya LLC (USA), Spectrum Chemicals (USA), Sigma-Aldrich (USA) or Alfa Aesar (USA).

2-2: δ by fatty acid component ¹³ C analysis

Fatty acids were extracted from milk samples and converted to methyl esters (FAMEs) according to known methods (Chung, IM, et al. , Food Chemistry, 196: 138, 2016). First, the sample prepared by freeze-drying in Example 1-1

A precisely weighed 50 mg milk sample was transferred to a Teflon ™ cap tube and nonadecanoic acid (0.2 mg; C19: 0) was added as an internal standard. Then 200 μl of heptanes and methylation reagent (methanol: benzene: DMP: H 2 SO 4, 39: 20: 5: 2, v / v / v / v) were added to the tube for fat extraction, In a constant temperature bath for 2 hours. The resulting supernatant (~ 300 μl) was then cooled at room temperature and then centrifuged at about 45 g for 2 minutes and then passed through a sealed-cap GC vial (2 ml volume, OD x length = 12 x 32 mm). The FAME conversion procedure was performed three times for each milk sample, and a total of 900 占 퐇 of supernatant was obtained.

It was performed to fatty acid δ ¹³ C analysis using the thus obtained supernatant, fatty acid δ ¹³ C analysis, GC-C-Ⅲ combustion interface (GC-C-Ⅲ combustion interface ) the Thermodynamic MAT 253 mass spectrometer (Thermo MAT 253 mass through gt; GC &lt; / RTI &gt; chromatography (Agilent 6890 GC gas chromatograph) coupled to a spectrometer.

The calibrated internal reference material (total 20 μg C; C12: 0) was added to each sample, quality control and assurance standards mixture for use in δ ¹³ C and total carbon calibration.

1 μl of the milk sample supernatant was injected in a splitless mode and each FAME was separated on a SGE BP5 column (30 m length × 0.25 mm outer diameter, 0.25 μm film thickness) at a constant flow rate of 1.4 ml / min (min) Respectively. The inlet temperature was set at 280 DEG C, the initial oven temperature was set at 110 DEG C, held for 1 minute, then increased from 4 DEG C / min to 220 DEG C, increased from 10 DEG C / min to 290 DEG C, . The separated FAMEs were quantitatively converted to carbon dioxide (CO ₂ ) in a CuO / NiO oxidation reactor at 980 ° C. and the gas was dried through a Nafion drier and exposed to an isotope mass spectrometer (IRMS).

The measured δ ¹³ C values were first calibrated using the internal reference material (C 12: 0) selected based on the sample composition and the temporary values, and then corrected for the standard reference materials of the National Institute of Standards and Technology (NIST) (IAEA-600, USGS-40, USGS-41, USGS-42, USGS-43, USGS-61, USGS-64 and USGS-65).

In addition, the carbon isotope values of methanol used in the FAME conversion were also corrected to ensure accurate δ13C _{fatty acid} analysis by dissolved organic carbon (DOC) - IRMS (Osburn, CL, and St-Jean, G. , Limnology and Oceanography: Methods , 5: 296, 2007). The mean δ ¹³ C value of methanol used for the FAME conversion was -42.78 ± 0.10 ‰ (n = 4). Two reference mixtures consisting of pure FAME containing calibrated δ ¹³ C (FMIX 1 and FMIX 2) were analyzed with the samples. FMIX1 is used for isotope correction of the δ ¹³ C analysis, but FMIX 2 is used as the primary quality assessment reference and is not involved in calibration. Repeated reference material (FMIX1 and FMIX2) measurements Average standard deviation was less than ± 0.5 ‰ for all FAMEs.

The δ ¹³ C value was expressed in one thousandth (‰) as an international standard, and the isotope index (δ) was measured according to the following equation (3).

&Quot; (3) &quot;

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

Statistical analysis was performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA) and the most significant difference test was performed at a 0.05 probability level.

Δ ¹³ C values of fatty acids according to milk samples
Organic milk Plain milk 2016
April 2016
In July 2016
October 2017
Jan Average 2016
April 2016
In July 2016
October 2017
January Average δ ¹³ C _{Myristic acid} -28.24 -28.66 -28.44 -28.33 -28.42 -27.61 -27.40 -27.59 -27.90 -27.63 δ ¹³ C _{palmitic acid} -29.90 -29.71 -30.06 -30.33 -30.00 29.89 -29.73 -29.83 -30.16 -29.90 δ ¹³ _{C palmitoleic acid} -35.90 -34.67 -35.16 -36.71 -35.61 -35.18 -34.72 -34.32 -34.54 -34.69 δ ¹³ C _{stearic acid} -33.30 -34.12 -33.96 -34.04 -33.85 -33.14 -32.21 -33.03 -32.87 -32.81 ? ¹³ C _{oleic acid-cis} -33.26 -33.35 -33.51 -33.86 -33.50 -32.96 -32.13 -33.31 -32.84 -32.81 δ ¹³ C _{oleic acid-trans} -37.13 -38.68 -38.05 -35.48 -37.13 -36.90 -35.61 -36.67 -36.18 -36.29 δ ¹³ C _{linoleic acid} -34.33 -34.86 -34.45 -35.20 -34.71 -33.16 -32.32 -32.99 -33.26 -32.93 δ ¹³ C _{iso-pentatecanone} -35.24 -32.90 -34.51 -35.83 -34.62 -33.94 -33.73 -33.85 -34.19 -33.92

As shown in Table 2, all δ ¹³ C _{fatty acid} values except for palmitic acid were lower in organic milk than in normal milk. In addition, except for myristic acid and stearic acid, most of the δ ¹³ C _{fatty acid} values were observed on a monthly basis. In particular, the δ ¹³ C _{fatty acid} values of milk collected in July 2016 were found to be slightly higher than the other sampling months investigated in the present invention.

Also, when compared to the δ ¹³ C _bulk value, isotope fractionation was observed in all δ ¹³ C _{fatty acids} in both the general milk and the organic milk investigated in the present invention. Despite the lack of statistical significance, it was found that isotopic fractionation was higher in organic milk than normal milk, except for δ ¹³ C _{palmitic acid} (Fig. 1). Isotope fractionation was observed to occur at a minimum of -5.6 ‰ in δ ¹³ C _{myristic acid} of normal milk and up to 14.7 ‰ in δ ¹³ C _{oleic acid} of organic milk.

Isotopic analysis of amino acids in milk

3-1: Acid hydrolysis and derivatization of amino acids

Samples for carbon stable isotope and nitrogen stable isotope analysis by amino acid composition were prepared according to known methods (Yarnes, CT, and Herszage, J., Rapid Communications in Mass Spectrometry, 31: 693, 2017).

Briefly, the lyophilized milk samples prepared in Example 1-1 obtained individual amino acids through acid hydrolysis. First, crushed milk (10 mg) and 6M HCl (2 ml) were added to a borosilicate glass bottle, and then the headspace was washed with nitrogen (N ₂ ) and sealed. For a while. After cooling, the acid hydrolyzate was treated with 200 [mu] l chloroform, the vial was gently vortexed, and the organic layer was removed to remove the remaining lipid soluble components before drying. Finally, the sample was dried in a heating block at 60 ° C under a gentle stream of N ₂ to prepare an acid hydrolyzate of the amino acid.

3-2: Derivatization for the determination of carbon stable isotopes by amino acid composition

For the amino acid components by δ ¹³ C analysis, the Examples 3-1 the acid hydrolyzate of methoxyl carbonyl methyl ester obtained in (methoxylcarbonyl methyl ester; MOC) method (Walsh, RG, He, S., and Yarnes, CT, Rapid Communications in Mass Spectrometry, 28 : 96, 2014).

First, a mixture of hydrolyzate and amino acid (less than 10 μmol total) was dissolved in 200 μl of 0.4 M HCl. Regardless of the sample matrix, the secondary derivatization of glutamic acid was avoided and performed at low pH (pH <1) to determine the exact isotopic compositional values. Subsequently, 100 μl of the obtained solution was added to a GC vial having a fixed insert of 350 μl, an internal standard solution (L-norleucine and L-homophenylalanine for calculation of a temporary δ ¹³ C amino acid, (L-homophenylalanine)), 50 [mu] l of methanol and 30 [mu] l of pyridine, and vortexed gently. Then 15 유 of the derivatization reagent (methyl chloroformate) was added to the vial and the mixture was vortexed and left at room temperature for 10 minutes. Thereafter, 100 占 퐇 of chloroform was added, and the mixture was vortexed to obtain an emulsion. When complete phase separation (generally after 5 minutes) was achieved, the organic layer was transferred to a fresh GC vial with 350 μl of fixed insert (containing Na ₂ SO ₄ to remove residual moisture in the organic layer). Methoxylcarbonyl methyl ester (MOC) derivatives for δ13C analysis were analyzed within one day after sample preparation.

3-3: Derivatization for the determination of nitrogen stable isotope by amino acid composition

For analysis of δ ¹⁵ N for each amino acid component, the acid hydrolyzate obtained in Example 3-1 and an amino acid mixture (less than 10 μmol in total) were analyzed by N-acetyl isopropyl ester (NAIP) method Yarnes, CT, and Herszage, J., Rapid Communications in Mass Spectrometry, 31: 693, 2017). First, 20 μl of the internal standard solution as described above was added to the acid hydrolyzate, mixed, and then dried under a gentle stream of N ₂ . Subsequently, 1 ml of 1.85 M acidified isopropanol prepared above on ice was added to the reaction vial and then heated at 100 ° C for one hour. The remaining isopropanol was removed under a N ₂ stream at 40 ° C and 250 μl of chloroform was added to the vial followed by drying in a cold block under N ₂ to remove excess residual reagent. The partial derivative was acetylated with a mixture of acetic anhydride, trimethylamine and acetone (1 ml; 1: 2: 5, v / v / v) N was evaporated reagent from the _second stream under 0 ℃ cold block. After drying, 2 ml of ethyl acetate and 1 ml of saturated aqueous NaCl were added and the mixture was vortexed. After separating the phases, the aqueous phase was removed and the organic phase was concentrated in a 0 ° C cold block under an N ₂ stream. Then, 100 μl of ethyl acetate was added to the vial, and the resulting solution of N-acetyl amino acid isopropyl esters was transferred to a GC vial with inserts. N-acetyl isopropyl ester (NAIP) derivatives for δ ¹⁵ N analysis were analyzed within one day after sample preparation.

3-4: δ by amino acid component ¹³ C and? ¹⁵ N analysis

Analysis of δ ¹³ C and δ ¹⁵ N by amino acid composition was done by gas chromatography (Trace) connected to a Delta V Advantage IRMS instrument via GC IsoLink combustion interface (Thermo Electron Corp., Germany) GC-C-IRMS system including a GC Ultra gas chromatograph.

After chromatographic separation, each compound was completely burned with carbon dioxide and nitrogen and inserted into an isotope analyzer. A combustion reactor (Thermo Scientific, PN 1255321) composed of NiO tubes containing CuO / NiO wires was maintained at 1000 ° C. After removing moisture with a Nafion drier, the gas to be analyzed was applied to an isotope analyzer. To avoid isobaric interference in the ion source during δ 15N analysis, liquid nitrogen traps were used to remove carbon dioxide from the carrier stream after combustion.

The MOC derivative was injected in a splitless mode (1 minute) at 240 DEG C and then injected into a capillary column (DB-23 capillary column, length 30 m, 0.25 mm OD, film thickness 0.25 m) Flow rate. The temperature was raised to 120 占 폚 at a rate of 15 占 폚 / min, the temperature was raised to 175 占 폚 at a rate of 2 占 폚 / min, maintained for 5 minutes, increased to 195 占 폚 at a rate of 2 占 폚 / The temperature was raised to 250 DEG C at a rate of minute, and the temperature was maintained for 9 minutes.

The NAIP derivative was injected in a splitless mode (1 minute) at 255 DEG C and then passed through a column (Agilent DB-1301 column (60 m length x 0.25 mm ID, 1 μm film thickness) at a constant flow rate of 1.2 ml / Maintained at 70 DEG C for 2 minutes, raised to 140 DEG C at a rate of 15 DEG C / minute, increased to 255 DEG C at a rate of 8 DEG C / minute, and then held for 40 minutes.

To calibrate and calibrate the obtained isotope values, the temporal isotopic values of each sample peak were calculated during the analysis. For this purpose, pure reference gas (carbon dioxide and nitrogen) was used first. Next, all amino acid isotopic values were adjusted using an internal standard and readjusted based on the known isotopic composition of the normalized mixture. Standardization and quality assessment mixtures (UCD AA 1, 2, 3) contain pure amino acids (alanine, aspartic acid, glutamic acid, glycine, isoleucine, leucine, lysine, phenylalanine, proline and valine) with calibrated δ ¹³ C and δ ¹⁵ N values. . These mixtures contain a range of δ ¹⁵ N values for individual amino acids, ranging from -7.08 to +50.19 for δ ¹⁵ N and -44.88 to 2.46 for δ ¹³ C. In addition, two natural substances (baleen and fish muscle) were analyzed with sample and used as secondary quality assurance material.

Quality control (amino acid mixture; UCD AA 1, 2) and quality assessment materials (amino acid mixture UCD AA 3, natural materials (whale and fish muscle)) were monitored for accuracy and precision at each calibration step. The standardization and quality assessment mixtures consist of purely calibrated pure amino acids by isotope mass spectrometry (EA-IRMS) in conjunction with an elemental analyzer.

The results of the EA-IRMS are based on the revised supplementary reference material for the National Institute of Standards and Technology (NIST) standards such as IAEA-N1, IAEA-N2, IAEA-N3, USGS-40 and USGS- Lt; / RTI &gt; The GC-C-IRMS measurement was repeated two times and three repeated measurements were performed when the standard deviation exceeded the expected measurement error (± 1 ‰). Based on the results obtained for the calibrated mixtures with the same characteristics, the mean standard deviation of QC / QA material is ± 0.53 for δ ¹⁵ N and ± 0.54 for δ ¹³ C. Sample repeat measurements did not exceed ± 1.25 ‰ between amino acids (in samples) and samples (in amino acids).

The isotope index (?) Was measured according to the following equations (3) and (4).

&Quot; (3) &quot;

δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).

&Quot; (4) &quot;

δ ¹⁵ N per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000

The above R _component is the carbon stable isotope consumption (by ¹⁵ N _component / ¹⁴ N _component ) of fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (nitrogen: atmospheric N ₂ value).

Statistical analysis was performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA) and the most significant difference test was performed at a 0.05 probability level.

Δ ¹³ C values of amino acids according to milk samples
Organic milk Plain milk 2016
April 2016
In July 2016
October 2017
January Average 2016
April 2016
In July 2016
October 2017
January Average δ ¹³ C _alanine -18.29 -23.30 -20.38 -15.74 -19.40 -18.60 -20.41 -19.27 -18.36 -19.16 δ ¹³ C _{aspartic acid} -18.35 -15.87 -16.06 -15.48 -16.44 -18.77 -14.73 -13.95 -18.48 -16.48 δ ¹³ C _{glutamic acid} -18.44 -17.35 -15.57 -18.82 -17.55 -18.44 -15.67 -17.15 -18.14 -17.35 δ ¹³ C _glycine -17.80 -18.25 -18.83 -14.19 -17.27 -16.48 -17.96 -17.21 -17.29 -17.23 δ ¹³ C _isoleucine -22.90 -24.76 -25.52 -23.06 -24.06 -22.48 -23.47 -24.48 -23.05 -23.37 δ ¹³ C _leucine -28.40 -30.50 -30.52 -29.02 -29.61 -27.52 -28.20 -29.00 -27.96 -28.17 [delta] ¹³ C _lysine -16.92 -17.90 -19.65 -16.68 -17.79 -16.97 -17.51 -20.55 -17.35 -18.10 δ ¹³ C _methionine -22.18 -21.55 -22.61 -21.92 -22.07 -20.99 -19.70 -22.16 -21.46 -21.08 δ ¹³ C _{phenylalanine} -27.56 -26.97 -27.22 -27.47 -27.31 -26.61 -25.91 -27.10 -26.99 -26.65 δ ¹³ C _proline -18.66 -18.12 -18.31 -20.61 -18.93 -19.13 -16.37 -17.75 -18.82 -18.02 δ ¹³ C _serine -12.58 -14.31 -13.29 -12.17 -13.09 -12.27 -12.36 -12.34 -11.81 -12.20 δ ¹³ C _threonine -24.82 -25.90 -27.71 -24.23 -25.67 -24.14 -25.68 -27.34 -24.25 -25.36 δ ¹³ C _valine -25.35 -27.46 -28.11 -24.96 -26.47 -24.75 -25.87 -27.18 -25.22 -25.75

Δ ¹⁵ N values of amino acids according to milk samples
Organic milk Plain milk 2016
April 2016
In July 2016
October 2017
January Average 2016
April 2016
In July 2016.
October 2017.
January Average δ ¹⁵ N _alanine 4.22 4.66 4.92 6.81 5.15 7.73 5.29 5.95 7.90 6.72 δ ¹⁵ N _{aspartic acid} 6.09 6.04 5.80 6.78 6.18 6.13 5.44 5.79 6.51 5.97 δ ¹⁵ N _{glutamic acid} 7.95 7.96 7.88 8.79 8.14 7.99 7.85 8.30 8.28 8.11 δ ¹⁵ N _glycine 5.92 5.25 4.95 7.54 5.91 8.65 5.10 6.04 7.95 6.94 δ ¹⁵ N _isoleucine 8.84 6.57 10.10 9.37 8.72 7.70 9.64 10.09 6.54 8.49 δ ¹⁵ N _leucine 4.94 3.37 4.29 4.42 4.26 5.05 3.92 4.66 4.98 4.65 ? ¹⁵ N _lysine 2.32 2.23 2.28 5.48 3.08 2.95 2.42 2.29 2.53 2.55 δ ¹⁵ N _methionine 0.49 -0.26 0.62 0.53 0.34 0.69 1.52 1.33 -0.05 0.87 δ ¹⁵ N _{phenylalanine} 5.95 5.86 5.78 6.87 6.12 5.07 5.26 5.70 5.65 5.42 δ ¹⁵ N _proline 6.72 6.37 6.44 6.76 6.57 7.13 6.43 6.75 7.12 6.86 δ ¹⁵ N _serine 3.43 3.80 3.30 3.24 3.44 5.14 3.66 3.91 4.36 4.26 δ ¹⁵ N _threonine -0.50 -0.6 ^b -0.34 -1.16 -0.66 0.90 -0.77 0.16 0.04 0.08 δ ¹³ N _valine 8.21 6.91 8.19 9.30 8.15 8.22 7.11 7.11 8.43 7.72

As shown in Table 3, the δ ¹³ C _{amino acid} values of isoleucine, leucine, methionine, phenylalanine, proline, serine, and valine were significantly higher in general milk than in organic milk, and all δ ¹³ C _{amino acids} The value of the change in age was confirmed. The amino _acid values of δ ¹³ C of methionine and proline were higher in summer milk in July 2016, δ ¹³ C _{amino acid} values of alanine, glycine and threonine were higher in winter milk In January, 2017, which is the highest level in the world.

In addition, as shown in Table 4, all δ ¹⁵ N _{amino acid} values except for phenylalanine, serine, and threonine were found to be insufficient for discriminating between normal milk and organic milk. The δ ¹⁵ N _{amino acid} values of alanine, glutamic acid, glycine, leucine, lysine, proline and valine showed significant changes in age. Compared with other seasonal milk samples, winter milk samples collected in January 2017 showed higher δ ¹⁵ N _{amino acids} , while summer milk samples collected in July 2016 showed lower δ ¹⁵ N _{amino acids} . The interaction effect (type X month) was observed only in δ ¹⁵ N _lysine .

On the other hand, as shown in Fig. 1, the isotope fractionation of amino acids varied depending on the _{amino acids} . Compared with δ ¹⁵ N _{amino acids} (-5.6 ‰ to 3.8 ‰), δ ¹³ C _{amino acids} (-7.2 ‰ to 9.8 ‰ ) Showed the greatest change. The fractionation effect showed that most of the amino acids were higher in organic milk than in normal milk, and the δ ¹³ C values of isoleucine, lysine, methionine, serine and valine were opposite to δ ¹⁵ N values.

No clear monthly δ ¹³ C _{fatty acid} and δ ¹³ C _{amino acid} change patterns were observed in organic milk and normal milk samples. However, the difference in δ ¹³ C values of myristic acid, stearic acid, oleic acid and linoleic acid in organic and general milk was found to be higher in summer milk (July 2016) compared to other seasons.

Figure 2 shows a representative time-resolved comparison of δ ¹³ C and δ ¹⁵ N in organic and general milk, and similar to previous studies by the present inventors, bulk isotope data analysis of milk was conducted throughout the year But did not provide a single threshold for organic milk certification.

However, as shown in Figures 2A and 2B, δ ¹³ C _linoleic exhibited a threshold value of approximately -33.5 ‰, δ ¹³ C _myristate was confirmed that the visible threshold of about -28 ‰, any season , It was confirmed that it clearly distinguished organic milk and general milk. That is, if the isotope index of _{linoleic acid} (隆¹³ C _{linoleic acid} ) is -31.5 to -33.5 ‰, or the isotopic index of myristic acid (δ ¹³ C _{myristic acid} ) is -27.0 to -28.0 ‰, .

In addition, although δ ¹³ C _leucine showed a time-dependent discrimination between organic milk and normal milk, it was not possible to set annual thresholds for organic milk certification using these parameters (Fig. 2C), δ ¹³ C _{stearic acid} Confirmed that organic milk could be discriminated except for April 2016 (Fig. 2D). The δ ¹³ C values of isoleucine and valine were found to be acceptable for milk collected in January 2017, although organic milk identification was possible from April to October 2016 (see Table 3, Figure 2E and Figure 2F ).

Milk determination by multivariate statistical analysis

4-1: Pearson correlation and hierarchical clustering analysis

Clusters for carbon / nitrogen isotope consumption by fatty acid and amino acid components were identified based on Pearson correlations and hierarchical clustering analysis (HCA).

Figure 3 is a correlation matrix and hierarchical clustering analysis (HCA) data based on δ ¹³ C values and δ ¹⁵ N values for bulk and amino acid or fatty acid components of organic milk and general milk samples, Each quadrangle represents a Pearson's correlation coefficient for a pair of compounds, and the value of the correlation coefficient represents the intensity of green or red as indicated in the scale.

As shown in Figure 3, Group A contained the δ ¹³ C _{amino acid} values of all δ ¹³ C _{fatty acids} (excluding oleic acid), δ ¹⁵ N _bulk and aspartic acid, methionine, phenylalanine, glutamate and proline. Group B contained only δ ¹⁵ N _{amino acid} values of isoleucine, methionine, and phenylalanine, while Group C contained mainly δ ¹³ C _{amino acids} , δ ¹⁵ N _{amino acids} and δ ¹³ C _bulk values. δ ¹³ C _bulk value of δ ¹³ C _{oleic acid} values (r = 0.77; P <0.0001 ) and the δ ¹³ _C-alanine values (r = 0.92; P <0.0001 ) was the naeteot appear to be highly correlated, lysine, leucine and the valine δ ¹⁵ N values (r = 0.51; P <0.05), respectively. In contrast, the value of δ ¹⁵ N showed a weak correlation with the elemental isotopic values of other components. The δ ¹⁵ N _bulk values correlated with δ ¹³ C _{palmitoleic acid} values (r = 0.42; P <0.05) and δ ¹³ C values of isoleucine, lysine, threonine and valine (r = 0.51; P <0.05) .

In the isotopes of fatty acids and amino acids, δ ¹³ C values of myristic acid, stearic acid and linoleic acid were significantly correlated (r>0.86; P <0.0001), δ ¹³ C _valine and δ ¹³ C _isoleucine ( r = 0.98; P <0.0001), δ ¹³ C _isoleucine and δ ¹³ C _leucine ( r = 0.89; P <0.0001), δ ¹⁵ N _threonine and δ ¹⁵ N _serine ( r = 0.90; P < Were strongly correlated with each other.

δ ¹³ C _aspartate showed a negative correlation with the δ ¹³ C values of isoleucine, leucine, lysine, threonine and valine (r ≤ -0.57; P <0.05), while δ ¹³ C _{phenylalanine} showed δ ¹³ C _{oleic acid} except showed a correlation of all the δ ¹³ C _{fatty acid} value and a negative (r ≤ -0.66; P <0.05 ). The correlation between isotopic values for fatty acids and amino acid components is as follows:

δ ¹³ C _{iC15: 0 (iso-penta teka acid)} and δ ¹³ _C-alanine (r = -0.79; P <0.0001 );

? ¹³ C _{oleic acid} and? ¹³ C _serine ( r = 0.76; P <0.0001);

? ¹³ C _glycine and? ¹⁵ N _lysine ( r = 0.70; P <0.0001);

δ ¹³ C _proline and δ ¹⁵ N _lysine / δ ¹⁵ N _valine ( r = -0.63; P <0.01).

4-2: Milk discrimination using partial least-squares discriminant analysis (PLS-DA)

In the present invention, stable isotope consumption measured by milk fatty acid and amino acid components of Examples 2 and 3 was applied to partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis was performed using the statistical analysis program SIMCA-P (version 13.0; Umetrics, Umea, Sweden) and the similarities / dissimilarities between the isotope data groups were determined. Before analysis, the data file was scaled by unit variance scaling. Since most of the δ ¹⁵ N _{amino acid} values are low (Table 4), δ ¹⁵ N _{amino acid} values were not used in the development of the PLS-DA model in the present invention.

As shown in Figure 4A, the PLS-DA score plot showed clear clustering, with the highest ranked two PCs accounting for 46.9% of the total variance in the data set. In particular, the first major component, which accounts for 29.2% of total variance, isotope characterization of organic milk and general milk. In the PLS components 1, was the show great contribution factor was the higher δ ¹³ C _{fatty acid} levels in cow's milk than organic milk, δ ¹³ C respectively of 0.397 and δ ¹³ of _myristic C _linoleic 0.395 Unique Vector ( 4B).

Also, the VIP value describes the extent to which the variable contributes to the projection, and one or more VIP values are typically used as a reference to identify variables that are important to the model. Therefore, as shown in FIG. 4C, the myristic acid, the linoleic acid, the stearic acid, the oleic acid, the palmitoleic acid, the leucine, the methionine methionine), serine (serine) and was found to be greater than the VIP value for δ ¹³ C of phenylalanine (phenylalanine) 1, those of δ ¹³ C _myristate ^{(VIP: 1.806), δ 13} C _{linoleic acid} (VIP: 1.796 ) And δ ¹³ C _{stearic acid} (VIP: 1.572) were observed as important isotopic features in discriminating organic milk.

As shown in FIG. 4D, in the external verification, the entire data was divided into a training set (n = 19) and a test set (n = 5), and the test set was used to evaluate the model performance quality. The PLS-DA model proposed in the present invention showed good performance (R ² X = 0.547 R ² Y = 0.865 and Q ² = 0.689).

In addition, as shown in FIGS. 5 and 6, the PLS-DA model of the present invention showed a relatively clear separation between organic milk and normal milk samples.

PLS component 1 had a significant impact on the separation of the organic milk and general milk sampling seasons (April / January and July / October), while PLS component 2 had a significant effect on summer (July) and autumn Month) milk samples were effectively classified as organic milk or normal milk.

Overall, the R ² X, R ² Y and Q ² parameters in the developed PLS-DA model were 0.678, 0.990 and 0.954 for organic milk and 0.683, 0.929 and 0.791 for common milk, respectively. In particular, the δ ¹³ C values of valine and threonine have been identified as important components for clear seasonal separation of organic milk and common milk (Figures 5 and 6, VIP of organic milk: δ ¹³ C _valine 1.401, δ ¹³ C _threonine 1.394; General milk VIP values: δ ¹³ C _valine 1.450, δ ¹³ C _threonine 1.551).

As shown in Figure 5, in the case of the production season determination of organic milk, δ ¹³ _C-valine, δ ¹³ _C-threonine, δ ¹³ _{C-isoleucine,} δ ¹³ _C-lysine, δ ¹³ C _glycine, δ ¹³ C _{Oleic acid,} δ ¹³ C _{palmitate It} was confirmed that the VIP value of _tolestone , δ ¹³ C _leucine , δ ¹³ C _alanine , δ ¹³ C _proline , δ ¹³ C _{glutamic acid} and δ ¹³ C _{iso-pentatecanoic acid} was 1 or more. As shown in FIG. 6, in the case of the production season determination, δ ¹³ _C-threonine, δ ¹³ _{C-aspartic acid,} δ ¹³ _C-valine, δ ¹³ _{C-isoleucine,} δ ¹³ _C-leucine, δ ¹³ _C-lysine, δ ¹³ C _{palmitoleic resan,} δ ¹³ C _myristic it was confirmed that the _acid value of the VIP and the δ ¹³ _C-proline 1 or more.

Claims (12)

(a) obtaining linoleic acid in a sample of milk and measuring carbon stable isotope consumption;
(b) measuring each isotope index according to Equation (3) using carbon stable isotope consumption of the linoleic acid; And
&Quot; (3) &quot;
δ ¹³ C _Component (‰ [(R _component / R _{standard sample} ) - 1] × 1000
The above R _component is carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of fatty acid or amino acid component of milk sample, and R _{standard sample} is Vienna Pee Dee Belemnite (carbon standard: VPDB).
(c) If the isotope index of _{linoleic acid} (delta ¹³ C _{linoleic acid} ) is -31.5 to -33.5, discrimination is made with organic milk;
&Lt; / RTI &gt;
(a) obtaining a fatty acid or amino acid component by ingredient in the organic milk and general milk samples which have been judged, and measuring the carbon stable isotope consumption by ingredient;
(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;
&Quot; (3) &quot;
δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000
The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).
(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And
(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining whether the unknown milk sample is organic milk or general milk by applying the standard model of step (c);
A method for distinguishing organic milk and general milk using the stable isotope analysis of each component.
The method of claim 2, wherein the fatty acid in step (a) is selected from the group consisting of myristic acid, linoleic acid, stearic acid, oleic acid and palmitoleic acid. Wherein the organic milk is at least one selected from the group consisting of organic milk and normal milk.
3. The method according to claim 2, wherein the amino acid in step (a) is at least one selected from the group consisting of leucine, methionine, serine and phenylalanine. Lt; / RTI &gt;
3. The method of claim 2, wherein the quality parameter values by the partial least squares discriminant analysis (PLS-DA) analysis of step (c) are R ² X = 0.547, R ² Y = 0.865, and Q ² = 0.689. &Lt; / RTI &gt;
(a) obtaining a fatty acid or an amino acid component by ingredient in an organic milk or a milk sample obtained seasonally, and measuring a carbon-stable isotope consumption of each ingredient;
(b) measuring each isotope index according to the following equation (3) using carbon stable isotope consumption for each component;
&Quot; (3) &quot;
δ ¹³ C per _component (‰) = [(R _component / R _{standard sample} ) - 1] × 1000
The R- _component is the carbon stable isotope consumption (by ¹³ C _component / ¹² C _component ) of the fatty acid or amino acid component of the milk sample, and the R _{standard sample} is the international standard value (carbon dioxide: Vienna Pee Dee Belemnite).
(c) establishing a standard model by applying the isotope index to a partial least-squares discriminant analysis (PLS-DA); And
(d) obtaining a fatty acid or amino acid component by component from an unknown milk sample, performing the steps (a) and (b) above to measure a carbon stable isotope index for an unknown milk sample by fatty acid or amino acid component, Determining a production season of an unknown milk sample by applying the standard model of step (c);
A method of seasonal production of organic milk or general milk using component stable isotope analysis.
[7] The method according to claim 6, wherein in the case of production seasonal determination of organic milk, the fatty acid in step (a) is at least one selected from the group consisting of oleic acid, palmitoleic acid and iso-pentadecanoic acid. Analysis of seasonal production of organic milk or general milk using.
The method according to claim 6, wherein the amino acid in step (a) is at least one selected from the group consisting of valine, threonine, isoleucine, lysine, glycine, leucine, alanine, proline and glutamic acid in the production season of organic milk. Seasonal Determination of the Production of Organic Milk or Normal Milk Using the Stable Isotope Analysis of the Components.
7. The method according to claim 6, wherein, in the case of production seasonal determination of general milk, the production of organic milk or general milk using the stable isotope analysis of ingredients, wherein the fatty acid in step (a) is palmitoleic acid or myristic acid Identification method.
The method according to claim 6, wherein, in the case of production seasonal determination of general milk, the amino acid of step (a) is at least one selected from the group consisting of threonine, aspartic acid, valine, isoleucine, leucine, lysine, Seasonal Determination of Production Milk or Milk Using Organic Stable Isotope Analysis.
The method according to claim 6, wherein the quality parameter value by the partial least squares discriminant analysis (PLS-DA) analysis of step (c) is R ² X = 0.678 for organic milk, R ² Y = 0.990. &Lt; Desc / Clms Page number 20 &gt; 6. A method for determining the production time of organic milk or general milk using stable isotope analysis of components.
The method according to claim 6, wherein the quality parameter value by the partial least squares discriminant analysis (PLS-DA) analysis of step (c) is R ² X = 0.683, R ² Y = 0.929 and Q ² = 0.791. The method for determining the production time of organic milk or general milk using the stable isotope analysis of each component.

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