Fatty Acid- and Amino Acid-Specific Isotope Analysis for Accurate

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Food Safety and Toxicology

Fatty Acid- and Amino Acid-Specific Isotope Analysis for Accurate Authentication and Traceability in Organic Milk Ill-Min Chung, Jae Kwang Kim, Christopher T. Yarnes, Yeon-Ju An, Chang Kwon, So-Yeon Kim, Yu-Jin Yang, Hee-Youn Chi, and Seung-Hyun Kim J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b05063 • Publication Date (Web): 13 Dec 2018 Downloaded from http://pubs.acs.org on December 18, 2018

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Journal of Agricultural and Food Chemistry

Fatty Acid- and Amino Acid-Specific Isotope Analysis for Accurate Authentication and Traceability in Organic Milk

Ill-Min Chung†, Jae-Kwang Kim‡, Christopher T. Yarnes§, Yeon-Ju An†, Chang Kwon†, So-Yeon Kim†, Yu-Jin Yang†, Hee-Youn Chi†, Seung-Hyun Kim†*

† Department

of Crop Science, College of Sanghuh Life Science, Konkuk University,

Seoul 05029, Republic of Korea ‡

Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon 406-772, Republic of Korea

§

UC Davis Stable Isotope Facility, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA

* To whom correspondence should be addressed: Tel: +82-02-2049-6163; Fax: +82-02-455-1044; E-mail: [email protected]

Running title: Compound-specific isotope analysis for organic milk discrimination

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ABSTRACT The present study describes compound-specific δ13C and δ15N analyses of fatty acids and amino acids for improving the accurate authentication of organic milk (OM) against conventional milk (CM) collected in Korea. Most δ13Cfatty-acid and δ13Camino-acid values were lower in OM than in CM (P < 0.05); however, most δ15Namino-acid values displayed weak discriminative power for OM authentication. Higher isotopic fractionation was observed in δ13Cfatty-acid than in δ13Camino-acid and δ15Namino-acid, with fractionation trends differing with individual amino acid. In particular, δ13Clinoleic-acid of -33.5‰ and δ13Cmyristicacid

of -28‰ were determined to be promising year-round threshold values for Korean

OM authentication. The δ13Cbulk was highly correlated with δ13CAla (r = 0.92) and δ13Coleic-acid, trans (r = 0.77), and strong positive correlations were observed between δ13CVal and δ13CIle (r = 0.98), and between δ15NThr and δ15NSer (r = 0.90). Chemometric modelling for OM authentication produced a high quality model (R2X = 0.547 R2Y= 0.865 and Q2 = 0.689) with reliable chemical markers, notably δ13Cmyristic-acid, δ13Clinoleicacid,

and δ13Cstearic-acid. Furthermore, the models developed for seasonal separation in

OM (Q2 = 0.954) and CM (Q2 = 0.791) were of good quality. Our findings, based on compound-specific isotope data, improve the reliability of OM authentication in cases where bulk stable isotope ratio analysis alone is insufficient. They also provide valuable insight into the control of fraudulent OM labeling in Korea, with potential application in other countries. KEYWORDS: compound-specific isotope analysis, organic authentication, isotope fingerprinting, milk, multivariate model 2


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INTRODUCTION Total global production of organic foodstuffs was valued at approximately $62.9 billion (USD) in 2011, with organic animal products forming a significant portion of this, despite a lack of comprehensive statistical data.1 While organic milk (OM), generally producing without the use of pesticides, synthetic fertilizers, bovine growth hormones (BGH), and antibiotics, is up to 50% more expensive than conventional milk (CM), producing a common dairy farming practice using the concentrated feed, antibiotics and certain growth hormones, its market-share has been consistently growing over the past decade in European countries such as Austria, Switzerland, and Germany, where it accounts for approximately 10–11% of the total milk market in each country.2, 3 Moreover, the Korean domestic OM market has increased 12-fold over the past decade, reaching a value of ~$60 million in 2016.4 With global interest in organic foods increasing, accurate organic food traceability in the complicated food chain system has become a cornerstone of food safety policy, protecting consumer health as well as producer interests. Unfortunately, universal analytical methods for accurate authentication of organic foodstuffs have not yet been reported, despite great effort on the part of the organic food society.5 Variation in the chemical composition of milk resulting from differences between specific dairy farming management systems, in feeding regimens between OM and CM production for example, is a key concept in OM authentication.6, 7 Thus, to ensure food safety/quality and protect both consumers and organic producers from fraudulent OM labeling, several studies have focused on the analysis of milk components for OM authentication. 3



In particular, the higher concentration of nutritionally-desirable milk components such as α-tocopherol, β-carotene, and/or α-linolenic acid (ALA, a threshold value: 0.5%) have been well described as OM features.2, 8-12 Meanwhile, the ALA threshold value of 0.5% is often exceeded in CM under atypical conditions, such as pasture feeding in Alpine highlands. However, in these atypical cases, a time-resolved comparison of milk data, instead of a year-around limit, can help improve OM authentication.2, 13 Among several tools applicable for OM authentication, the importance of stable isotope ratio analysis (SIRA) of light elements like carbon, nitrogen, or sulfur has recently increased as a result of the search for alternative and more reliable means for authentication of organic plant and animal products. In addition, the SIRA is also a valuable tool for discriminating the geographical origin for other foods like honey14, 15 and cereals16. The δ13C value in milk, in particular, is considered a particularly promising marker for OM authentication, because it is significantly influenced by the dairy cow’s diet, which is composed of different plant sources (i.e. C3 vs C4 type plants). In contrast, the δ15N may be considered a relatively less useful isotope marker for husbandry animal products than plant products, due to the relatively narrow δ15N range (1.2‰ for leguminous plants to 3.3‰ for commercial concentrates) in dairy animal dietary sources17, 18 According to prior studies, which have been extensively conducted in Germany2, 3, 13, 19, the German retail OM was always below the maximum δ13C threshold value of -26.5‰ and never exceeded a maximum δ15N threshold value of 5.5‰. Additionally, the time-resolved average δ13C difference between OM and CM was 4.5‰, and δ13Cfat and δ13Cprotein were equally suitable for OM authentication, resulting a 4


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high correlation (r = 0.99) between δ13Cfat and δ13Cprotein. Another study suggested a δ13C threshold value of -23.5‰ for Italian OM authentication, and that values above this may indicate the presence of corn and/or its byproducts in the dietary sources.20 Our prior reports also found lower mean δ13C and δ15N values in OM than in CM, allowing for successful discrimination.9, 21 In particular, a time-resolved comparison using δ13C and δ15N 2D plots clearly discriminated OM from CM, and overcame the monthly and seasonal variations of δ13C and δ15N in OM authentication. Additionally, based on the chemometric models we developed, ALA and linoleic acid (LA) were found to be the most crucial chemical markers for OM authentication, while δ13C was the most important contributor to seasonal discrimination between OM and CM produced in Korea.9 Meanwhile, isotopic features of C4 grasses (i.e. δ13C) or leguminous plants (i.e. δ15N) used in organic farming production are similar to corn-feeding or synthetic fertilizer used for conventional production, respectively. Therefore, the increase of the aforementioned diets in organic farming makes unequivocal organic authentication more difficult.17, 22 As compared to the bulk isotope analysis of tissues and organisms, compoundspecific isotope analysis (CSIA) has recently attracted interest in various food authenticity areas as a more powerful and reliable technique, as it potentially produces more in-depth molecular information about a given sample.23 In particular, CSIA of fatty acids (FAs) and amino acids (AAs) can be a promising analytical tool, since these primary metabolites constitute a significant portion of living organisms, and effectively reflect the extent of δ13C and δ15N incorporation as a consequence of their various 5



synthetic pathways and subsequent biochemical uses.24 Both δ13C and δ15N analyses of milk fat, or of the milk protein (casein) fraction, have been reported for OM authentication3, 13; however, to our knowledge, no report has thus far evaluated the applicability of CSIA for authentication of organic milk. Besides, our prior studies9, 21 did not establish a reliable year-round δ13C or δ15N threshold value for OM authentication, despite the continual expansion of the OM market in Korea. Therefore, this study demonstrated FA- and AA-specific isotopic profiling characteristics for accurate yearround OM authentication in Korea using a gas chromatography-combustion-isotope ratio mass spectrometer (GC-C-IRMS). Potential isotope markers for OM authenticity were elucidated using chemometric tools.

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MATERIALS AND METHODS Chemicals and reagents. ACS-grade 12.1 M hydrochloric acid (HCl), 50 vol% sodium hydroxide (NaOH), and HPLC-grade methanol were obtained from Thermo Fisher Scientific (Waltham, MA, USA) and used for acid hydrolysis and derivatization. 2,2-Dimethoxypropane (DMP), methyl chloroformate, pyridine, anhydrous sodium sulfate (Na2SO4), and triethylamine were sourced from Sigma-Aldrich (St. Louis, MO, USA). Acetyl chloride and anhydrous ethyl acetate were purchased from Acros Organics (Geel, Belgium), and acetic anhydride was procured from Alfa Aesar (Ward Hill, MA, USA). Sulfuric acid (H2SO4) was obtained from Daejung Chemical & Materials Co., Ltd. (Gyeonggi-Do, Korea), and benzene and heptanes were obtained from Junsei (Tokyo, Japan). All fatty acid methyl esters (FAMEs, at 99% purity) and L-amino acids (AAs, at >98% purity) standards used for compound-specific calibration, scale normalization, and quality assurance (QA) were provided from Matreya LLC (State College, PA USA), Spectrum Chemicals (New Brunswick, NJ, USA), Sigma-Aldrich (St. Louis, MO USA), or Alfa Aesar (Tewksbury MA, USA).24, 25 Milk collection. OM and CM (0.2 L, n = 3 for each) produced by the same manufacturer were collected in April, July, and October 2016, and in January 2017. Information about all the milk production and processing like cleanness, homogenization, and pasteurization were previously ascribed in detail.9 The OM investigated in this study was produced by the Act on the Promotion of Environment-Friendly Agriculture and Fisheries and the Management of and Support for Organic Foods issued in Korea and were also certified by the IFOAM. In addition, the OM samples were certified by an 7



inspection body, as designated by the National Agricultural Products Quality Management Service in Korea prior to the selling at retail market. A total of 24 milk samples were frozen at -70 °C, and then lyophilized at -40 °C for approximately 5 days prior to compound-specific δ13C and δ15N analysis of fatty acid and amino acid. Bulk δ13C and δ15N analysis by IRMS. Lyophilized milk samples (~2 mg) were weighed in a tin capsule and bulk δ13C and δ15N were measured using an elemental analyzer coupled with IRMS.26 δ13C and δ15N were calculated as δ, ‰ = [(Runknown Rstandard)/Rstandard], where Runknown is the C or N stable isotope ratio (i.e., 13C/12C, 15N/14N) of the milk sample, and Rstandard is the value of the corresponding international reference standard (Vienna Pee Dee Belemnite for carbon and atmospheric N2 for nitrogen). The reference δ13C and δ15N values of laboratory reference materials (bovine liver, nylon 5), which were previously calibrated against the international established reference materials (IAEA-N1, IAEA-N2, IAEA-N3, USGS-40, or USGS-41) were -21.69‰ and +7.72‰ for the bovine liver, and -27.72‰ and -10.31‰ for the nylon 5, respectively. In this study, the analytical precision of the δ13C and δ15N measurements was within ±0.1‰, in the form of ± standard deviation relative to the laboratory reference materials. Fatty acid-specific δ13C analysis in milk by GC-C-IRMS. Milk fatty acids (FAs) were extracted and simultaneously converted into FAMEs prior to GC-C-IRMS analysis.27 A 50 mg lyophilized milk sample and 0.2 mg of internal standard (nonadecanoic acid, C19:0) were transferred to a Teflon™-lined cap tube; subsequently heptanes (200 µL), for fat extraction, and a methylation reagent (340 µL; methanol : benzene : DMP : H2SO4 (39:20:5:2, v/v/v/v) were added to the same tube, then the mixture was gently 8


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shaken in a water bath at 80 °C for 2 h. The resultant supernatant (~300 µL) was transferred to a sealed-cap GC vial (OD × length = 12 × 32 mm) after cooling to room temperature and centrifugation at ~45 g for 2 min. The FA extraction and FAME conversion process was conducted for a total of three times for each sample replicate and ~900 µL of the supernatants were pooled to use δ13Cfatty-acid analysis. An Agilent 6890 GC gas chromatograph coupled to a Thermo MAT 253 mass spectrometer via a GC-C-III combustion interface was used for δ13Cfatty-acid analysis. For the purposes of δ13C and total carbon calibration, a calibrated internal standard (total 20 μg; C12:0) was added to each sample, and to the quality control and assurance reference mixtures, prior to δ13Cfatty-acid analysis. A 1 μL sample aliquot was injected in splitless mode and FAMEs were separated on an 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−1. GC conditions were as follows: inlet temperature: 280 °C; oven temperature: initial 110 °C held for 1 min; increased to 220 °C at 4 °C min−1; increased to 290 °C at 10 °C min−1, and held for 10 min. The separated FAMEs were quantitatively converted to CO2 in a CuO/NiO oxidation reactor at 980 °C, and the resultant gas was dried by passage through a Nafion dryer and subjected to IRMS. A representative GC-C-IRMS chromatogram for FAMEs from milk for the analysis of 13C was shown in Figure 1A. The measured δ13C values were first corrected using the calibrated internal reference material (C12:0), which was chosen based on sample composition and provisional values, and then corrected again using the laboratory reference material (FMIX1, see below in detail) comprising several FAMEs calibrated against NIST standard reference 9



materials (IAEA-600, USGS-40, USGS-41, USGS-42, USGS-43, USGS-61, USGS-64, and USGS-65). Additionally, the isotopic value of the carbon source in methanol used for FAME conversion was also corrected to ensure accurate δ13Cfatty-acid analysis by DOC-IRMS.28 The mean δ13C value of methanol used for the above FAME conversion was determined as −43.89 ± 0.14‰ (n = 4). Two reference mixtures comprising pure FAMEs with calibrated δ13C (FMIX 1 and FMIX 2) were co-analyzed with the investigated samples. FMIX1 was used for the isotopic calibration of δ13C measurements using a linear regression of the measured and known δ13C values, while FMIX 2 was used as a primary quality assessment reference material, and was not used in corrections. The standard deviations of replicate reference material (FMIX1 and FMIX2) measurements were less than ±0.5‰ across all FAMEs (see Supporting Information, SI, QA 1). Acid hydrolysis in milk. Milk δ13Camino-acid and δ15Namino-acid analyses were performed as described elsewhere.25 A milk sample (10 mg) and 2 mL of 6 M HCl were transferred to a borosilicate glass vial, the headspace was flushed with N2, and then it was sealed and placed in an oven at 150 °C for 70 min. After cooling, the acid hydrolysate was reconstituted in 200 µL of chloroform and gently vortexed. The organic layer was discarded to remove any remaining lipid-soluble components prior to drying. Finally, the remainder of the acid hydrolysate was dried in a heating block at 60 °C under a gentle stream of N2. Methoxycarbonyl methyl ester (MOC) derivatization for δ13Camino-acid analysis. The hydrolysate and AA mixtures (1). Hence, compound-specific δ13C and δ15N analyses combined with a PLS-DA provides for reliable OM authentication in Korea, regardless of the extent of seasonal variation in isotopic values in milk. In summary, we developed a highly-feasible FA- and AA-specific isotope analysis which, combined with PLS-DA, improves OM authentication. Our study elucidates features of the compound-specific δ13C and δ15N data of FA and AA in OM and CM produced in different seasons, and may improve current authentication procedures, facilitating the detection of fraudulent OM labeling. Further, our findings can be also used for identifying milk producing time (season). However, our results must be interpreted cautiously, as a limited number of milk samples were tested. Therefore, future studies should evaluate a larger number of milk samples from different years/production regions to establish global isotope markers for reliable OM authentication on a wider scale.

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Acknowledgements This paper was supported by Konkuk University in 2017. The authors thank the reviewers for their perceptive and helpful comments.

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FIGURE CAPTIONS Figure 1. Representative GC-C-IRMS chromatograms for the CSIA of fatty acid and amino acid in milk samples. Fatty acid methyl esters (FAMEs) from milk for the analysis of 13C. Methyl dodecanoate (C12:0) calibrated for 13C was added as an internal reference material (A). Methoxycarbonyl amino acid methyl esters (MOC) from milk for the analysis of 13C (B). N-acetyl amino acid isopropyl esters (NAIP) from milk for the analysis of 15N (C). L-Norleucine (Nle) and L-homophenylalanine (HPhe) calibrated for 15N was added as an internal reference material. Figure 2. Differences (∆Bulk-CSIA, ‰) between bulk isotope ratios and compound-specific isotope ratios of fatty acid and amino acid for all OM and CM samples examined in this study. Bars represent mean value ± SD (n = 12 for each milk type). Figure 3. Comparison of the selected compound-specific isotope values of fatty acids and amino acids in OM and CM as a function of milk sampling month. Results are expressed as mean value ± SD (n = 3 for each milk type per each sampling month). Blue dashed line is for illustrative purpose only, representing a potential threshold value for OM authentication in a whole year, but without statistical analysis. ns: non-significant. Figure 4. Correlation matrix of all bulk and compound-specific δ13C and δ15N in milk. Each square indicates the Pearson’s correlation coefficient of a pair of compounds, and the values of the correlation coefficients are represented by the intensity of green or red colors, as indicated on the color scale. Figure 5. PLS-DA results derived from all bulk and compound-specific δ13C and δ15N of milk for OM authenticity in comparison to CM. Score plot (A), loading plot from 27



PLS-DA (B), variable importance in the projection (VIP) values obtained from the PLS-DA model (C), external validation test (D). The ellipse on the score plots represents the 95% confidence region for Hotelling’s T2. Figure 6. PLS-DA results derived from all bulk and compound-specific δ13C and δ15N of milk for the milk seasonal separation in OM (A: score plot, B: loading plot, C: VIP values, D: external validation test) and CM (E: score plot, F: loading plot, G: VIP values, H: external validation test). The ellipse on the score plots represents the 95% confidence region for Hotelling’s T2.

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Westerhuis, J. A.; Hoefsloot, H. C. J.; Smit, S.; Vis, D. J.; Smilde, A. K.; van Velzen, E. J. J.; van Duijnhoven, J. P. M.; van Dorsten, F. A. Assessment of PLSDA cross validation. Metabolomics 2008, 4, 81-89. Worley, B.; Powers, R. Multivariate Analysis in Metabolomics. Curr. Metabolomics 2013, 1, 92-107. Eriksson, I.; Johansson, E.; Kettaneh-Wold, N.; Wold, S., Multi- and Megavariate Data Analysis Principles and Applications. Umetrics AB: Umeå, Sweden, 2001. Slots, T.; Butler, G.; Leifert, C.; Kristensen, T.; Skibsted, L. H.; Nielsen, J. H. Potentials to differentiate milk composition by different feeding strategies. J. Dairy Sci. 2009, 92, 2057-2066.

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Table 1. Summary of bulk and compound (fatty acid and amino acid)-specific δ13C and δ15N values of OM and CM collected in Korea, 2016 – 2017, and the associated ANOVA P-value for main factor and its interactions. Milk type (T), n=12 per each type

　

OM

　

CM

LSD0.05

Bulk isotope ratio, ‰ -22.43±0.81b δ13Cbulk 15 4.94±0.37b δ Nbulk

-22.03±0.14a 5.15±0.21a

δ13Cfatty acid, ‰ δ13CMyristic acid δ13CPalmitic acid δ13CPalmitoleic acid δ13CStearic acid δ13COleic acid-cis δ13COleic acid-trans δ13CLinoleic acid δ13Ciso-C15:0

-28.42±0.22b -30.00±0.28 -35.61±0.87b -33.85±0.43b -33.50±0.33b -37.13±1.33b -34.71±0.50b -34.62±1.18b

δ13Camino acid, ‰ δ13CAlanine δ13CAspartic acid δ13CGlutamic acid δ13CGlycine δ13CIsoleucine δ13CLeucine δ13CLysine δ13CMethionine δ13CPhenylalanine δ13CProline δ13CSerine δ13CThreonine δ13CValine δ15Namino acid, ‰ δ15NAlanine δ15NAspartic acid δ15NGlutamic acid

Milk sampling month (M), n=6 per each sampling month

P-value

APR 2016

JUL 2016

OCT 2016

JAN 2017

LSD0.05

0.02 0.03

-22.08±0.20b 4.60±0.23d

-22.87±0.74d 5.08±0.18c

-22.32±0.21c 5.32±0.09a

-21.65±0.29 a 5.17±0.14b

-27.63±0.21a -29.90±0.21 -34.69±0.49a -32.81±0.44a -32.81±0.58a -36.29±0.70a -32.93±0.49a -33.92±0.32a

0.12 0.14 0.36 0.25 0.31 0.50 0.33 0.29

-27.93±0.39a -29.90±0.19ab -35.55±0.50b -33.22±0.36 -33.11±0.31ab -37.04±0.38b -33.75±0.71a -34.59±0.78c

-28.03±0.70ab -29.72±0.13a -34.69±0.34a -33.17±1.06 -32.74±0.71a -36.84±1.68b -33.59±1.46a -33.31±0.56a

-28.02±0.48ab -29.94±0.17b -34.74±0.66a -33.49±0.53 -33.41±0.50b -37.22±0.77b -33.72±0.87a -34.18±0.38b

-19.40±2.87 -16.44±1.47 -17.55±1.78 -17.27±2.06 -24.06±1.18b -29.61±0.97b -17.79±1.37 -22.07±0.54b -27.31±0.70b -18.93±1.14b -13.09±1.00b -25.67±1.46 -26.47±1.42b

-19.16±0.97 -16.48±2.37 -17.35±1.85 -17.23±1.31 -23.37±0.78a -28.17±0.58a -18.10±1.63 -21.08±1.05a -26.65±0.62a -18.02±1.17a -12.20±0.51a -25.36±1.40 -25.75±0.97a

0.41 0.82 1.36 1.03 0.17 0.13 0.64 0.43 0.55 0.41 0.50 0.42 0.20

-18.44±0.28b -18.56±0.81c -18.45±0.26b -17.14±1.09ab -22.69±0.23a -27.96±0.49a -16.95±0.61a -21.59±0.76b -27.08±0.58 -18.90±0.28c -12.42±0.41ab -24.48±0.52a -25.05±0.34a

-21.80±1.59d -15.30±0.87a -16.51±2.76a -18.10±1.42b -24.11±0.73c -29.35±1.27c -17.71±0.30a -20.63±1.09a -26.44±0.74 -17.25±1.01a -13.34±1.27c -25.79±0.52b -26.66±0.90b

5.15±1.61 6.18±0.71 8.14±0.50

6.72±2.50 5.97±0.47 8.11±0.26

1.81 0.46 0.25

5.97±3.17 6.11±0.38ab 7.97±0.25b

4.98±1.10 5.74±0.58b 7.91±0.24b

Main factor

Interaction 　

T

M

0.02 0.04

**** ****

**** ****

**** ****

-28.12±0.26b -30.24±0.17c -35.62±1.24b -33.46±0.72 -33.35±0.60b -35.83±0.86a -34.23±1.09b -35.01±0.97d

0.17 0.20 0.51 0.36 0.44 0.71 0.46 0.41

**** ns **** **** **** ** **** ****

ns *** *** ns * ** * ****

*** ns ** *** ns *** * ****

-19.82±0.71c -15.00±1.55a -16.36±1.30a -18.02±1.48b -25.00±0.60d -29.76±0.84d -20.10±0.81b -22.39±0.52c -27.16±0.91 -18.03±0.73b -12.82±0.62bc -27.53±0.51c -27.64±0.54c

-17.05±1.55a -16.98±1.89b -18.48±0.51b -15.74±1.83a -23.06±0.24b -28.49±0.60b -17.01±1.03a -21.69±0.57b -27.23±0.47 -19.71±1.05d -11.99±0.60a -24.24±0.40a -25.09±0.29a

0.58 1.16 1.92 1.46 0.24 0.19 0.91 0.61 0.77 0.58 0.70 0.60 0.28

ns ns ns ns **** **** ns *** * *** ** ns ****

**** **** * * **** **** **** *** ns **** ** **** ****

**** ** ns * *** **** ns ns ns ** ns ns

5.43±0.75 5.80±0.47b 8.09±0.28b

7.36±2.59 6.65±0.57a 8.53±0.46a

2.57 0.65 0.36

ns ns ns

ns * **

ns ns ns

33


T*M

****

Journal of Agricultural and Food Chemistry δ15NGlycine δ15NIsoleucine δ15NLeucine δ15NLysine δ15NMethionine δ15NPhenylalanine δ15NProline δ15NSerine δ15NThreonine δ13NValine

5.91±1.32 8.72±2.36 4.26±0.78 3.08±1.52 0.34±0.89 6.12±0.71a 6.57±0.30 3.44±0.42b -0.66±0.48b 8.15±1.19

6.94±2.37 8.49±2.92 4.65±0.71 2.55±1.08 0.87±0.87 5.42±0.61b 6.86±0.45 4.26±1.01a 0.08±1.01a 7.72±1.05

1.45 2.26 0.53 0.83 0.72 0.55 0.30 0.64 0.63 0.83

7.28±2.54ab 8.27±2.47 4.99±0.59a 2.63±0.63b 0.59±0.50 5.51±0.85 6.93±0.32a 4.28±1.09 0.20±1.09a 8.21±0.53ab

5.17±0.92c 8.11±3.27 3.65±0.75b 2.33±1.20b 0.63±1.44 5.56±0.72 6.40±0.17b 3.73±0.43 -0.71±0.44b 7.01±1.30c

5.50±0.64bc 10.10±0.41 4.48±0.44a 2.29±0.37b 0.98±0.57 5.75±0.42 6.59±0.22ab 3.61±0.40 -0.09±0.34ab 7.65±1.04bc

a–d

Page 34 of 42 7.75±1.98a 7.95±3.23 4.71±0.57a 4.01±1.92a 0.24±0.89 6.26±0.81 6.95±0.57a 3.80±1.25 -056±1.13ab 8.86±0.68a

2.05 3.20 0.75 1.17 1.02 0.78 0.42 0.90 0.89 1.17

ns ns ns ns ns * ns * * ns

* ns ** * ns ns * ns ns *

ns ns ns * ns ns ns ns ns ns

Values with different superscripts differ significantly with respect to each milk type or milk sampling months (P < 0.05). ns: nonsignificant, *: P

Fatty Acid- and Amino Acid-Specific Isotope Analysis for Accurate

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