Comparison of the meat metabolite composition of Linwu and Pekin ducks using 600 MHz 1H nuclear magnetic resonance spectroscopy

MOLECULAR AND CELLULAR BIOLOGY Comparison of the meat metabolite composition of Linwu and Pekin ducks using 600 MHz 1 H nuclear magnetic resonance spectroscopy Xiangrong Wang,∗,†,‡ Chengkun Fang,∗ Jianhua He,∗ Qiuzhong Dai,∗,†,‡,1 and Rejun Fang∗,1 ∗

College of Animal Science and Technology, Hunan Agricultural University, NO. 1 Nongda Road, Changsha 410128, Hunan, PR China; † Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, NO. 348 Xianjiahu West Road, Changsha 410205, Hunan, PR China; and ‡ Department of Animal Nutrition and Feed Technology, Hunan Institute of Animal Science and Veterinary Science, NO. 8 Changlang Road, Changsha 410131, Hunan, PR China identify the distinguishing metabolites of breast meat between two breeds of ducks. Compared with 42-d-old Pekin duck meat, breast from 72-d-old Linwu duck has higher concentration of anserine, carnosine, homocarnosine, and nicotinamide, but significantly lower concentration of succinate, creatine, and myo-inositol. These results contribute to a better understanding of the differences in meat metabolite composition between 72d-old Linwu and 42-d-old Pekin ducks, which could be used to help assess the quality of duck meat as a food.

ABSTRACT In an effort to further understand of the differences of meat flavor and texture between Linwu ducks and Pekin ducks at market age, we investigated the meat metabolite composition of the two breeds of ducks using 600 MHz 1 H nuclear magnetic resonance (NMR) spectroscopy. Comprehensive multivariate data analysis including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) were applied to analyze the 1 H-NMR profiling data to

Key words: metabolite profiling, duck meat, multivariate data analysis, nuclear magnetic resonance 2017 Poultry Science 96:192–199 http://dx.doi.org/10.3382/ps/pew279

INTRODUCTION

or strain in carcass yield, meat quality, amino acid, and fatty acid profiles (Aronal et al., 2012; Choi et al., 2014; Smith et al., 2015). However, little is known of meat metabolite profiling in Linwu ducks and the differences in meat metabolite composition between Linwu and Pekin ducks at their market ages. It is known that differences in lipid, protein, and chemical or metabolite composition will impact flavor and texture on poultry meat (Chumngoen and Tan, 2015; Qiao et al., 2016). Therefore, research into the meat metabolite composition of Linwu and Pekin ducks at market age of each breed may contribute to the understanding of the differences of meat flavor and texture in the two duck breeds. Metabolomics is a systematic approach focusing on the profile of low molecular weight metabolites in biological fluids, cell, and tissues extracts (Fiehn, 2002). It is currently used as a model of research in many disciplines of medical, food science, and other fields, including disease diagnosis (Emwas et al., 2013), biomarker screening (Bogdanov et al., 2008), nutrition research (Brennan, 2014), quality identification of food (Jakes et al., 2015; Trimigno et al., 2015), and so on. Many powerful analytical techniques are commonly applied to identify and characterize small molecules, including liquid chromatography (LC) coupled with mass spectrometry (MS), gas chromatography MS, and nuclear

Ducks have been farmed for thousands of years, possibly starting in Southeast Asia (Kiple and Ornelas, 2000). It is becoming one of the most popular poultry commodities besides chicken in Asia, especially in China. There are 2,700 million ducks in the world, within approximately 2,080 million in China. In 2010, approximately 70% of the world duck meat is produced in China (Chen et al., 2015). Although Pekin duck is the predominant breed used for meat production in China, still many other local duck species are raised. Linwu duck is one of the local high-quality meat breeds with a lengthy and good reputation and was served to Emperors in different dynasties as a tribute. Linwu ducks have smaller average body weight (1.6 kg) and longer rearing period (10 to 11wk) than Pekin ducks (3.2 kg; 6 wk). Linwu ducks have a unique meat flavor and texture, and are renowned for their tender meat with high protein and low fat (Chen et al., 2008). Previous studies have reported the differences among duck breeds  C 2016 Poultry Science Association Inc. Received February 22, 2016. Accepted June 30, 2016. 1 Corresponding authors: [email protected], daiqiuzhong@caas. cn (Dai); [email protected] (Fang)

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MEAT METABOLITE COMPOSITION OF LINWU AND PEKIN DUCKS

magnetic resonance (NMR) (Farag et al., 2012; Graham et al., 2012). Because NMR is a rapid, noninvasive, and non-destructive technique that can provide complete structural analysis of a wide range of organic molecules in complex mixtures, NMR-based metabolomics analysis has rapidly developed and has been successfully used in meat analysis, such as quantitative determination of fatty acid chain composition in pork meat products (Siciliano et al., 2013), authentication of beef versus horse meat (Jakes et al., 2015), determination of conjugated linoleic acid concentrations in beef (Prema et al., 2015), and identification of molecular markers in the traceability of dried beef (Shintu et al., 2007). Up to now, few studies have focused on the NMR-based metabolomics analysis of duck meat. Only one report used NMR-based metabolomics to investigate the influence of age on the metabolite composition of duck meat (Liu et al., 2013). Multivariate data analysis techniques mainly include the unsupervised (principal component analysis, PCA) and supervised (partial least squares discriminant analysis, PLS-DA) methods (Worley et al., 2013). In order to enhance the predictive power of the model in NMRbased metabolomics studies, orthogonal projection to latent structure-discriminant analysis (OPLS-DA) is a type of supervised classification and regression method used to visualize the metabolic alterations of different sample (Kind et al., 2007). In the present study, we applied 1 H-NMR to compare the metabolic composition of breast meat between Linwu and Pekin ducks at market ages and to identify distinguishing metabolites between the two breeds of duck using multivariate data analysis techniques. These distinguishing metabolites potentially reveal the differences of meat flavor and texture, which could be used to help identify and assess the quality of meat of these two breeds of ducks at their market age. The role and underlying mechanism of metabolites in meat development deserve further investigation. Breast meat was examined in the present study because it is one of the major high-value cuts.

MATERIALS AND METHODS Sample Collection One-d-old female hatchlings, 20 each of Pekin duck (Beijing Golden Star Duck Co. Ltd, Beijing, China) and Linwu duck (Shunhua Duck Industrial Development Co,. Ltd, Linwu, China) were used. All ducks entered the experiment at the same time and were distributed into one cage for each breed. They were fed the same corn- and soybean meal-based diet which met or exceeded the nutrient recommendations of National Research Council (NRC, 1994) and were raised under the same environmental conditions to control any nutritional or environmental differences except appetite, food intake, and inter-individual variability. Feed and water were provided ad libitum during the experiment. Downloaded from https://academic.oup.com/ps/article-abstract/96/1/192/2706279 by guest on 11 April 2018

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Following a 12-h overnight fast, 7 ducks of similar body weights from each breed were selected and slaughtered at market ages of 42 d for Pekin ducks and 72 d for Linwu ducks by captive-blot stunning and exsanguination. The breast meat from left side was rapidly taken and immediately snap-frozen using liquid nitrogen and stored at −80◦ C, at 48 h after the slaughter, breast meat of both Pekin ducks and Linwu ducks were evaluated by NMR spectroscopy. The animal protocol was approved by the Animal Care Committee of the College of Animal Science and Technology, Hunan Agricultural University.

Sample Extraction The extraction method of duck meat sample was according to the procedure of Liu et al. (2013). Each sample (70 mg) was put into a 2.0 mL Eppendorf tube with 0.60 mL of aqueous methanol solution (CH3 OH:H2 O = 2:1), homogenized by Tissuelyser for 2 min and discontinuous ultrasonication on wet ice for 10 min, then centrifuged at 11,180 × g for 10 min at 4◦ C. The upper layer was transferred to a new Eppendorf tube; the residue was re-extracted twice. The extracted liquids were combined and centrifuged at 16,099 × g for 10 min at 4◦ C, then concentrated under vacuum and freezedried to yield meat extracts. Finally, each sample was mixed with 0.6 mL 0.15 M phosphate buffer dissolved in D2 O and centrifuged at 16,099 × g for 10 min at 4◦ C. A 0.55 mL supernatant was transferred into a 5-mm outer diameter NMR tube (Norell, ST500-7; Norell, Inc., Landisville, NJ) for NMR analysis.

NMR Measurement 1

H NMR spectra of all duck meat extracts were acquired at 298 K on a Bruker Avance III 600 MHz NMR spectrometer (600.13 MHz for proton frequency) equipped with an inverse cryogenic probe (Bruker Biospin, Germany). One-dimensional 1 H NMR spectra were acquired using the first increment of the gradient selected NOESY pulse sequence (recycle delay-G1 -90◦ t1 -90◦ -tm -G2 -90◦ -acquisition) with water pre-saturation during both the recycle delay (2 s) and mixing time (tm , 100 ms). A total of 64 transients were collected into 32 k data points over a spectral width of 20 ppm with the 90◦ pulse length adjusted to about 10 μs for each sample.

Data Analysis All free induction decays were multiplied by an exponential function with a line broadening factor of 1 Hz and zero-filled to 128 k prior to Fourier transformation. All NMR spectra were phase- and baseline-corrected manually using TOPSPIN software (Version 3.0, Bruker Biospin, Germany). All spectra were referenced to the chemical shift of TSP (δ 0.00). NMR spectra (δ 0.5 to 10) were binned with each region of 0.002 ppm wide and automatically integrated with the AMIX package

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(Version 3.8.5, Bruker Spectrospin Ltd.). The region δ 4.3 to 5.18 was removed to avoid the effects of imperfect water suppression. Each integral region was normalized to the sum of all integral regions for each spectrum prior to pattern recognition analyzes. An overview of the data distribution and intersample similarities (e.g., clusterings and outliers) for each meat, extracts were first investigated by PCA, which was performed with the software SIMCA-P+ 11.0 (Umetrics, Sweden). Further analysis on NMR spectral data was processed using PLS-DA and OPLS-DA model with unit variance scaling. The loadings in the coefficient plots were calculated from the coefficients combining the weight of the variables contributing to the sample clustering in the model (He et al., 2012). The PLS-DA models were cross-validated by a permutation analysis (200 times) (Martin et al., 2008). The coefficient plots were generated using an in-house developed MATLAB (MathWorks, Natick, MA) script and were color coded with absolute value of coefficients (|r|). The coefficient plot showed the variables (resonances) that contributed to clustering and the significance of such contribution. In the present study, a correlation coefficient of |r| was used as the cutoff value for the statistical significance based on the discrimination significance at the level of P value (0.05), which was determined according to the test for the significance of the Pearson’s productmoment correlation coefficient. The quality of the 7-fold

cross-validated OPLS-DA models was described by the parameters R2 X, R2 Y, and Q2 , and further evaluated with a permutation test (He et al., 2012).

RESULTS AND DISCUSSION 1H NMR Spectra of Duck Meat Extract Representative 1 H NMR spectra for breast meat of 42-d-old Pekin and 72-d-old Linwu ducks are shown in Figure 1. From these spectra, 29 metabolites were unambiguously identified, and their chemical shifts and peak multiplicity along with the corresponding 1 H NMR chemical shifts and signal multiplicities are presented in Table 1. The 29 metabolites include eleven amino acids (valine, leucine, isoleucine, alanine, lysine, glutamate, glutamine, aspartate, taurine, tyrosine, phenylalanine), seven organic acids (3-hydroxybutyrate, lactate, acetate, succinate, fumarate, formate, creatine), two volatile amines (dimethylamine, trimethylamine), two sugars (glucose, glycogen), three peptides (anserine, carnosine, homocarnosine), and four other metabolites (inosine, ADP, nicotinamide, and myo-inositol). Liu et al. (2013) studied the metabolic composition of Cherry Valley duck (Pekin duck breed) using 1 H NMR spectroscopy, and 21 metabolites were reported. However, this is the first report about the analysis of complete metabolome of

Figure 1. Two typical 600 MHz 1 H NMR spectra of duck breast meat extracts of Linwu and Pekin ducks at market ages. The region δ 9.5 to 5.0 (see the dot box) in two breeds of ducks was expanded 4 times, relative to the region δ 4.7 to 0.8. Keys for metabolites are given in Table 1. (1) Valine, (2) leucine, (3) isoleucine, (4) 3-hydroxybutyrate (3-HB), (5) lactate, (6) alanine, (7) lysine, (8) acetate, (9) glutamate, (10) glutamine, (11) succinate, (12) aspartate, (13) dimethylamine, (14) trimethylamine, (15) creatine, (16) taurine, (17) anserine, (18) glucose, (19) glycogen, (20) fumarate, (21) tyrosine, (22) phenylalanine, (23) carnosine, (24) formate, (25) nicotinamide, (26) inosine, (27) ADP, (28) homocarnosine, (29) myo-inositol. Downloaded from https://academic.oup.com/ps/article-abstract/96/1/192/2706279 by guest on 11 April 2018

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Table 1. NMR for duck meat metabolites. No.

Metabolites

Moieties

δ 1 H (ppm) and multiplicitya

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Valine Leucine Isoleucine 3-Hydroxybutyrate Lactate Alanine Lysine Acetate Glutamate Glutamine Succinate Aspartate Dimethylamine Trimethylamine Creatine Taurine Anserine

γ CH3 ; γ  CH3 ; β CH; α CH δ CH3 ; δ  CH3 ; γ CH; α CH2 γ CH3 ; δ CH3 ; β CH; α CH γ CH3 ; α CH2 ; α  CH2 ; β CH β CH3 ; α CH β CH3 ; α CH γ CH2 ; δ CH2 ; β CH2 ; εCH2 ; α CH CH3 α CH; β CH2 ; γ CH2 α CH; β CH2 ; γ CH2 CH2 β -CH; β  -CH; α -CH CH3 CH3 CH2 ; CH3 -CH2 -SO3 ; -CH2 -NH2 CH3 ; 3-CH; COCH2

18 19 20 21 22 23

Glucose Glycogen Fumarate Tyrosine Phenylalanine Carnosine

24 25 26

Formate Nicotinamide Inosine

27 28 29

ADP Homocarnosine Myo-Inositol

α CH resonances CH(OH); 2-CH CH CH; CH 2H & 6H; 4H; 3H & 5H 3-CH; 5-CH; 1 -CH2 ; 2 -CH; CH2 NH2 H-COOH 2-CH; 6-CH; 4-CH; 5-CH 2-CH; 7-CH; 2 -CH; 4 -CH; CH2 ; ‘CH2 ; 5-CH’ 2-CH; 3-CH; 2 -CH C = CH; N = CH 2-CH; 1-CH; 4-CH; 5-CH

0.98(d); 1.04(d); 2.27(m); 3.61(d) 0.95(d); 0.96(d); 1.69(m); 3.73(t) 0.93(t); 1.00(d); 1.99(m); 3.68(d) 1.20(d); 2.31(dd); 2.38(dd); 4.16(m) 1.33(d); 4.11(q) 1.47(d); 3.78(q) 1.49(m); 1.70(m); 1.89(m); 3.02(t); 3.76(t) 1.92(s) 2.07(m); 2.33(m); 3.72(m) 2.13(m); 2.44(m); 3.76(m) 2.41(s) 2.68(dd); 2.80(dd),3.89(dd) 2.72(s) 2.88(s) 3.03(s); 3.92(s) 3.27(t); 3.42(t) 2.69(m); 3.03(m); 3.22(m); 3.23(m); 3.76(m); 4.49(m); 7.05(m); 8.09(d) 5.24(d); 4.65(d); 3.3-3.9 5.41(d); 3.6 (m) 6.52(s) 6.89(d); 7.18(d) 7.31(m); 7.37(m); 7.42(m) 3.02(m); 3.21(m); 4.48(m); 7.05(m); 8.12(d)

a

8.45(s) 8.95(t); 8.72(dd); 8.26(dd); 7.60(dd) 3.84(m); 3.92(m); 4.28(dd); 4.45(dd); 6.10(d); 8.25(s); 8.35(s) 4.62(m); 6.12(d); 8.27(s); 8.54(s) 7.06(s); 8.03(s) 3.29(t); 3.54(dd); 3.63(t); 4.07(t)

Multiplicity: s, singlet; d, doubles; t, triples; m, multiplets; q, quartet; dd, double doublet.

Linwu duck meat including primary and secondary metabolites, and most of the metabolites. Amino acids, organic acids, sugars, nucleotide metabolites have been reported (Soncin et al., 2007; Dai et al., 2011; Liu et al., 2013), but some compounds such as volatile amine, 3hydroxybutyrate, carnosine, homocarnosine, and myoinositol have been rarely reported in duck meat. Visual inspection of the 1 H NMR spectra showed visible differences in breast meat metabolites between 42-d-old Pekin duck and 72-d-old Linwu duck.

Multivariate Statistical Analysis for Discrimination of Breast In order to obtain more detailed information of metabolic differences between these two duck breeds, multivariate data analyses including PCA, PLS-DA, and OPLS-DA were performed. We performed PCA for breast meat metabolites at first. In the PCA score plots of the normalized NMR data for 72 d Linwu ducks and 42 d Pekin ducks (Figure 2), PC1 and PC2 explained 77.0% of the total variance. The PCA analysis showed some class differentiation for the two breeds, but there were noticeable overlaps, possibly due to the structured variation within each breed. To address this problem, all samples were used in PLS-DA and OPLS-DA analyses to maximize information. This step is integral to Downloaded from https://academic.oup.com/ps/article-abstract/96/1/192/2706279 by guest on 11 April 2018

Figure 2. PCA scores plot of duck meat extracts, R2 X = 77.0%, Q2 = 0.53.

stringent validation of the statistical model but has not been performed in most metabolomics studies employing PCA analysis (Kang et al., 2008). The corresponding PLS-DA model parameters for the explained variation, R2 X (=40.6%), R2 Y (=0.973), and the predictive capability, Q2 (=0.861), were high, indicating that it is an excellent model suitable for data analysis (Figure 3A). Permutation analysis (200 repeats)

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Figure 3. PLS-DA scores plot of duck meat extracts (A) and statistical validation of the corresponding PLS-DA model by permutation analysis (B). R2 is the explained variance, and Q2 is the predictive ability of the model. R2 X = 40.6%, R2 Y = 0.973, Q2 = 0.861.

Figure 4. OPLS-DA scores and correlation coefficient plots derived from NMR data for duck breast extracts associated with 72-d-old Linwu ducks (green circles) vs. 42-d-old Pekin ducks (black squares) are shown. Each symbol represents the metabolic profile obtained from the meat extracts of two breeds of ducks.

indicated that none of the distributions formed by the permuted data were better than the observed statistic based on the original data, revealing that the PLSDA model was good for predictability and goodness of fit. The OPLS-DA approach was used to investigate the metabolites that showed the greatest differences of 42-d-old Pekin ducks and 72-d-old Linwu ducks, and the results are shown as cross-validated score plots (Figure 4). The values for R2 X (=40.6%) and Q2 (=0.864), were employed to evaluate the model quality of OPLS-DA. Furthermore, permutation analysis were also performed in the PLS-DA model to validate each OPLS-DA model (Lee et al., 2010). This indicated that the OPLS-DA model can reliably differentiate classes even in the presence of structured variation and that OPLS-DA is more appropriate than PCA in discriminating the origins of breast meat samples.

crimination significance at the P < 0.05 level. OPLS– DA correlation coefficient plots shows that the distinguishing metabolites make the largest contributions to the differentiation of the two breeds at market ages (Figure 4). These results reveal that, compared with the 42-d-old Pekin duck meat, 72-d-old Linwu duck meat have significantly higher concentration of anserine, carnosine, homocarnosine, and nicotinamide, but significantly lower concentration of succinate, creatine, and myo-inositol (Table 2). According to metabolic pathway on the Kyoto Encyclopedia of Genes and Genomes database (http://www.genome.jp/kegg/), we outlined the main metabolic pathways, which are closely related to meat quality. These metabolic pathways consisted of amino acid metabolism, nicotinate and nicotinamide metabolism, TCA cycle, lipid metabolism.

Distinguishing Metabolites

Relationship between Distinguishing Metabolites and Meat Quality

In this study, we explored the OPLS-DA model to identify the distinguishing metabolites underlying the separation of breast meat. The metabolites with correlation coefficients greater than 0.707 were considered to be significant, which corresponds to a dis-

The most important aspects contributing to meat quality are taste, flavor, texture, and juiciness, the taste and flavor are determined by chemical composition (Ritota et al., 2012). Carnosine, anserine, and homocarnosine are endogenous bioactive compounds

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Table 2. OPLS-DA coefficients of metabolites in duck meat extracts. Correlation coefficient (r)a Metabolites Succinate Creatine Anserine Myo-inositol Carnosine Homocarnosine Nicotinamide

Linwu ducks vs Pekin ducks (R2 X = 40.6%, Q2 = 0.864)

Chemical shiftb 2.41(s) 3.03(s); 3.92(s) 2.69(m); 3.03(m); 3.22(m); 3.23(m); 3.76(m); 4.49(m); 7.05(m); 8.09(d) 3.29(t); 3.54(dd); 3.63(dd); 4.07(t) 3.02(m); 3.21(m); 4.48(m); 7.05(m); 8.12(d) 7.06(s); 8.03(s) 7.60(dd); 8.26(dd); 8.72(dd); 8.95(t)

− 0.707 − 0.746 0.931 − 0.769 0.839 0.720 0.908

a Correlation coefficients, positive and negative signs indicate positive and negative correlation in the concentrations, respectively. The correlation coefficient of |r| > 0.707 (degree = 6) was used as the cutoff value for the statistical significance based on the discrimination significance at the level of P = 0.05. b Multiplicity: s, singlet; d, doublet; t, triplet; dd, doublet of doublets; m, multiplet.

belonging to carnosine related compounds (CRCs), with strong buffering roles and antioxidant properties (Peiretti et al., 2011; Peiretti et al., 2012). The CRCs could be considered additional nutritional quality factors of meat (Jayasena et al., 2015). Previous research show that the influences of CRCs content on meat may differ depending on animal species (Peiretti et al., 2011; Mateescu et al., 2012; Jung et al., 2013). In the present study, breast meat of 72-d-old Linwu ducks contained a higher concentration of anserine, carnosine, and homocarnosine than those of 42-d-old Pekin ducks. The results of our study verified that the influences of CRCs content on meat differ depending on animal breed. The difference in carnosine content may be associated with the more frequent exercise and longer rearing period of Linwu ducks. Breast meat is predominantly composed of type II muscle fibers (Cheng, 2014) and during exercise require large amounts of dipeptides (e,g., histidine dipeptides) as a physico-chemical buffer against the protons produced due to anaerobic glycolysis in muscle, which results in carnosine accumulation (Dunnett and Harris, 1995). Nicotinamide is one of the pyridine derivatives with a fairly high concentration in poultry meat (Ahn and Maurer, 1990). As a precursor of nicotinamide adenine dinucleotide, nicotinamide influences cellular energy metabolism (Park et al., 2010) and could maintain efficient DNA repair (Surjana et al., 2013). It is thought to be a convenient agent with potential for chemoprevention of skin cancer (Thompson et al., 2015). Hence, nicotinamide also could be considered a kind of additional nutritional quality factors of meat. The succinate can be to reduce oxidative stress and to increase its systemic and liver tissue uptake. Succinate is also used to improve mitochondrial function in mice with steatotic livers (Evans et al., 2009). Creatine is a key compound that plays important roles in muscle energy metabolism (Wyss and Kaddurah-Daouk, 2000) and can improve muscle performance (Demant and Rhodes, 1999). Increased creatine content in the Downloaded from https://academic.oup.com/ps/article-abstract/96/1/192/2706279 by guest on 11 April 2018

muscle may delay post mortem lactate formation and postpone the pH decline, hence potentially improving the water-holding capacity (Nissen and Young, 2006). The content of creatine in meat is associated with the type of muscle metabolism (Mora et al., 2008; Reig et al., 2013). The present findings clearly show significant differences in creatine content of breast meat in 72d-old Linwu and 42-d-old Pekin ducks. The result may help to explain the differences of meat pH and waterholding capacity between Linwu and Pekin ducks. Myoinositol can regulate lipid transport and metabolism in the blood and liver (Diao et al., 2010). In the current study, breast meat of 72-d-old Linwu ducks contained lower concentration of myo-inositol than that of 42-dold Pekin ducks. Croze et al. (2013) demonstrated that mice treated with myo-inositol exhibited a decreased white adipose tissue accretion. This may be due to differences of lipid metabolism in skeletal muscle of Linwu duck and Pekin duck, which requires further study.

CONCLUSIONS Species and ages plays a crucial role in influencing the quality of duck meat. Therefore, both of them are crucial to establish differences in the metabolic profiles of breast meat between Linwu ducks and Pekin ducks and thus contribute to a better understanding of the meat quality of ducks at market age. The results from this study demonstrated differences between 72d-old Linwu ducks and 42-d-old Pekin ducks in several metabolic compositional profile. These distinguishing metabolites may be as potential biomarkers for identification of duck at market age. But there are some compounds that could not be detected by NMR, such as fatty acids and aromatic hydrocarbons, which are particularly important in meat quality and flavor development. However, metabolomics analysis that is based on NMR is an effective technique for investigating and

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assessing the chemical composition and quality of duck meat.

ACKNOWLEDGMENTS This work was supported by the Modern Agricultural Technical System Foundation of China (CARS-43-17), the Hunan Co-Innovation Center of Animal Production Safety (CICAPS), the Agricultural Science and Technology Innovation Program (ASTIP) of Chinese Academy of Agricultural Sciences, the Planning Subject of ‘the Twelfth Five-Year-Plan’ in National Science and Technology for the Rural Development in China (2011BAD26B03-5-2). Thanks also to Professor Olayiwola Adeola, Purdue University, West Lafayette, IN, USA, a “Shennong Scholar” Chair Professor in Hunan Agricultural University for his kindness in English language revision of this manuscript.

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