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Rapid Quality Discrimination and Amino Nitrogen Quantitative Evaluation of Soy Sauces by Tri-Step IR and E-nose

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Abstract

Despite the fact that soy sauce has been one of the most popular seasonings in Eastern Asia, rapid and holistic methods for its authentication and discrimination are still lacking. This research is sought to develop a novel method for rapid discrimination and amino nitrogen quantitative evaluation of different qualities of soy sauces (Chinese traditional fermentation soy sauce (CTFSS), Japanese traditional fermentation soy sauce (JTFSS), high-salt liquid-state fermentation soy sauce (HLFSS), and low-salt solid-state fermentation soy sauce (LSFSS)) based on tri-step infrared spectroscopy (IR) and partial least squares (PLS). Global nutrition fingerprints (saccharides, proteins, amino acids, and other compositions) of each quality soy sauce at the three levels of enhanced spectral resolution and nutrition profile variations among different soy sauces are synthetically interpreted with fast evaluation of their relative contents based on spectral peak intensity. Complementarily, electronic sensory combined with SPME-GC-MS distinguishes four species of soy sauces effective in smell with 90 discrimination indexes. Specifically, FT-IR peak intensity at about 1409 cm−1 (C–N band) exhibits regular enhancement with the increasing concentration of amino acid nitrogen. Thus, a quantitative prediction model based on IR spectra is established by PLS (R2, 0.9956; RMSEC, 0.233). It has been demonstrated that the developed method is applicable for rapid (5 min) discrimination and quantitative analysis of amino acid nitrogen in soy sauce.

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References

  • Arzberger U, Lachenmeier DW (2008) Fourier transform infrared spectroscopy with multivariate analysis as a novel method for characterizing alcoholic strength, density, and total dry extract in spirits and liqueurs. Food Anal Methods 1(1):18–22

    Article  Google Scholar 

  • Barth A (2007) Infrared spectroscopy of proteins. Biochim Biophys Acta 1767(9):1073–1101

    Article  CAS  PubMed  Google Scholar 

  • Bassbasi M, Luca MD, Ioele G, Oussama A, Ragno G (2014) Prediction of the geographical origin of butters by partial least square discriminant analysis (PLS-DA) applied to infrared spectroscopy (FTIR) data. J Food Compos Anal 33(2):210–215

    Article  CAS  Google Scholar 

  • Caswell DS, Spiro TG (1987) Proline signals in ultraviolet resonance Raman spectra of proteins: cis-trans isomerism in polyproline and ribonuclease A. J Am Chem Soc 109(9):2796–2800

    Article  CAS  Google Scholar 

  • Chirgadze YN, Fedorov OV, Trushina NP (2010) Estimation of amino acid residue side-chain absorption in the infrared spectra of protein solutions in heavy water. Biopolymers 14(4):679–694

    Article  Google Scholar 

  • Dong H, Xiao K (2017) Modified QuEChERS combined with ultra high performance liquid chromatography tandem mass spectrometry to determine seven biogenic amines in Chinese traditional condiment soy sauce. Food Chem 229:502–508

    Article  CAS  PubMed  Google Scholar 

  • Fabian H, Schultz C, Backmann J, Hahn U, Saenger W, Mantsch HH, Naumann D (1994) Impact of point mutations on the structure and thermal stability of ribonuclease T1 in aqueous solution probed by Fourier transform infrared spectroscopy. Biochemistry 33(35):10725–10730

    Article  CAS  PubMed  Google Scholar 

  • Feng YZ, Cai Y, Su GW, Zhao HF, Wang CX, Zhao MM (2014) Evaluation of aroma differences between high-salt liquid-state fermentation and low-salt solid-state fermentation soy sauces from China. Food Chem 145:126–134

    Article  CAS  PubMed  Google Scholar 

  • Feng Y, Su G, Sun-Waterhouse D, Cai Y, Zhao H, Cui C, Zhao M (2017) Optimization of headspace solid-phase micro-extraction (HS-SPME) for analyzing soy sauce aroma compounds via coupling with direct GC-Olfactometry (D-GC-O) and gas chromatography-mass spectrometry (GC-MS). Food Anal Methods 10(3):713–726

    Article  Google Scholar 

  • Gan JH, Xu CH, Zhu HZ, Mao F, Yang F, Zhou Q, Sun SQ (2015) Analysis and discrimination of ten different sponges by multi-step infrared spectroscopy. Chin Chem Lett 26(2):215–220

    Article  CAS  Google Scholar 

  • Gerwert K, Hess B, Engelhard M (1990) Proline residues undergo structural changes during proton pumping in bacteriorhodopsin. FEBS Lett 261(2):449–454

    Article  CAS  Google Scholar 

  • Gu D-C, Zou M-J, Guo X-X, Yu P, Lin Z-W, Hu T, Wu Y-F, Liu Y, Gan J-H, Sun S-Q, Wang X-C, Xu C-H (2017) A rapid analytical and quantitative evaluation of formaldehyde in squid based on tri-step IR and partial least squares (PLS). Food Chem 229:458–463

    Article  CAS  PubMed  Google Scholar 

  • Gurbanov R, Gozen AG, Severcan F (2017) Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method. Spectrochim Acta A Mol Biomol Spectrosc 189:282

    Article  CAS  PubMed  Google Scholar 

  • Hasegawa K, Ono TA, Noguchi T (2000) Vibrational spectra and Ab initio DFT calculations of 4-methylimidazole and its different protonation forms: infrared and Raman markers of the protonation state of a histidine side chain. J Phys Chem B 104(17):16320–16330

    Article  CAS  Google Scholar 

  • Hoang NX, Ferng S, Ting C-H, Huang W-H, Chiou RY-Y, Hsu C-K (2016) Optimizing the initial moromi fermentation conditions to improve the quality of soy sauce. LWT Food Sci Technol 74:242–250

    Article  CAS  Google Scholar 

  • Hu W, Guo XX, Wang XC, Zhao Y, Sun SQ, Xu CH, Liu Y (2016) Rapid discrimination of different grades of white croaker Surimi by tri-step infrared spectroscopy combined with soft independent modeling of class analogy (SIMCA). Food Anal Methods 9(4):831–839

    Article  Google Scholar 

  • Imamura M (2016) Descriptive terminology for the sensory evaluation of soy sauce. J Sens Stud 31(5):393–407

    Article  Google Scholar 

  • Johnston N, Krimm S (2010) An infrared study of unordered poly-L-proline in CaCl 2 solutions. Biopolymers 10(12):2597–2605

    Article  Google Scholar 

  • Kobayashi Y, Mayer SG, Park JW (2017) FT-IR and Raman spectroscopies determine structural changes of tilapia fish protein isolate and surimi under different comminution conditions. Food Chem 226:156–164

    Article  CAS  PubMed  Google Scholar 

  • Lee SM, Seo BC, Kim YS (2006) Volatile compounds in fermented and acid-hydrolyzed soy sauces. J Food Sci 71(3):C146–C156

    Article  CAS  Google Scholar 

  • Lee S, Lee JB, Hwang J, Lee KG (2015) Effect of various food additives on the levels of 4(5)-methylimidazole in a soy sauce model system. J Food Sci 81(1):T262–T267

    Article  CAS  PubMed  Google Scholar 

  • Liu HJ, Xu CH, Zhou Q, Wang F, Li WM, Yi MH, Sun SQ (2013) Analysis and identification of irradiated Spirulina powder by a three-step infrared macro-fingerprint spectroscopy. Radiat Phys Chem 85(4):210–217

    Article  CAS  Google Scholar 

  • Lord RC (1964) Introduction to infrared and Raman spectroscopy. Academic Press

  • Machado M, Machado N, Gouvinhas I, Cunha M, De Almeida J, Barros A (2015) Quantification of chemical characteristics of olive fruit and oil of cv cobran double dagger osa in two ripening stages using MIR spectroscopy and chemometrics. Food Anal Methods 8(6):1490–1498

    Article  Google Scholar 

  • Mansor TST, Man YBC, Rohman A (2011) Application of fast gas chromatography and Fourier transform infrared spectroscopy for analysis of lard adulteration in virgin coconut oil. Food Anal Methods 4(3):365–372

    Article  Google Scholar 

  • Mellado-Mojica E, Seeram NP, López MG (2016) Comparative analysis of maple syrups and natural sweeteners: carbohydrates composition and classification (differentiation) by HPAEC-PAD and FTIR spectroscopy-chemometrics. J Food Compos Anal 52:1–8

    Article  CAS  Google Scholar 

  • Naik VM, Krimm S (1984) Vibrational analysis of peptides, polypeptides, and proteins. In: Logistics@s The Emerging Frontiers of Transportation and Development in China (pp 1255–1261)

  • Park SW, Lee SJ, Sim YS, Choi JY, Park EY, Noh BS (2017) Analysis of ethanol in soy sauce using electronic nose for halal food certification. Food Sci Biotechnol 26(2):311–317

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Peris M, Escuder-Gilabert L (2009) A 21st century technique for food control: electronic noses. Anal Chim Acta 638(1):1–15

    Article  CAS  PubMed  Google Scholar 

  • Pinchas S, Laulicht I (1971) Infrared spectra of labelled compounds. Academic Press

  • Sagara T, Fiechter G, Pachner M, Mayer HK, Vollmann J (2017) Soybean spermidine concentration: genetic and environmental variation of a potential ‘anti-aging’ constituent. J Food Compos Anal 56:11–17

    Article  CAS  Google Scholar 

  • Steinhaus P, Schieberle P (2007) Characterization of the key aroma compounds in soy sauce using approaches of molecular sensory science. J Agric Food Chem 55(15):6262–6269

    Article  CAS  PubMed  Google Scholar 

  • Takeuchi H, Harada I (1986) Normal coordinate analysis of the indole ring. Spectrochim Acta A Mol Spectrosc 42(9):1069–1078

    Article  Google Scholar 

  • Tenenhaus M, Naes T (2001) Special issue—PLS methods. Chemom Intell Lab Syst 58(2):75–75

    Article  CAS  Google Scholar 

  • Tian H, Li F, Qin L, Yu H, Ma X (2014) Discrimination of chicken seasonings and beef seasonings using electronic nose and sensory evaluation. J Food Sci 79(11):S2346–S2353

    Article  CAS  PubMed  Google Scholar 

  • Voort FRVD, Ghetler A, Garcíagonzález DL, Li YD (2008) Perspectives on quantitative mid-FTIR spectroscopy in relation to edible oil and lubricant analysis: evolution and integration of analytical methodologies. Food Anal Methods 1(3):153–163

    Article  Google Scholar 

  • Xu CH, Sun SQ, Guo CQ, Zhou Q, Tao JX, Noda I (2006) Multi-steps infrared macro-fingerprint analysis for thermal processing of Fructus viticis. Vib Spectrosc 41(1):118–125

    Article  CAS  Google Scholar 

  • Xu C, Jia X, Xu R, Wang Y, Zhou Q, Sun S (2013a) Rapid discrimination of Herba Cistanches by multi-step infrared macro-fingerprinting combined with soft independent modeling of class analogy (SIMCA). Spectrochim Acta A Mol Biomol Spectrosc 114(10):421–431

    Article  CAS  PubMed  Google Scholar 

  • Xu CH, Liu SL, Zhao SN, Li SZ, Sun SQ (2013b) Unveiling ontogenesis of herbal medicine in plant chemical profiles by infrared macro-fingerprinting. Planta Med 79(12):1068–1076

    Article  CAS  PubMed  Google Scholar 

  • Zhu Y, Yang Y, Zhou Z, Li G, Jiang M, Zhang C, Chen S (2010) Direct determination of free tryptophan contents in soy sauces and its application as an index of soy sauce adulteration. Food Chem 118(1):159–162

    Article  CAS  Google Scholar 

Download references

Funding

This work is financially supported by the National Key Research and Development Program of China (2016YFD0401501), the National Natural Science Foundation of China (Grant No. 31401571), the Project of Science and Technology Commission of Shanghai Municipality (15320502100),the Key Project of Shanghai Agriculture Prosperity through Science and Technology (2016 (4-4)),Tianjin science and technology innovation fund (06FZZDSH00408); Tianjin Natural Science Fund (14JCQNJC11900) and Key Projects in the National Science and Technology Pillar Program during the Twelfth 5-year Plan Period (Grant No. 2015BAD17B01 and Grant No. 2015BAD17B02).

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Authors and Affiliations

  1. College of Food Science and Technology, Shanghai Ocean University, Shanghai, 201306, China

    Li Zhu, Yu Yan, Dong-Chen Gu, Ying Lu, Jian-Hong Gan, Ning-Ping Tao, Xi-Chang Wang & Chang-Hua Xu

  2. Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai, 201306, People’s Republic of China

    Li Zhu, Yu Yan, Dong-Chen Gu, Ying Lu, Jian-Hong Gan, Ning-Ping Tao, Xi-Chang Wang & Chang-Hua Xu

  3. Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai, 201306, China

    Li Zhu & Chang-Hua Xu

  4. Department of Pharmacology, Yale University, New Haven, CT, 06520, USA

    Chang-Hua Xu

  5. National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Shanghai, 201306, China

    Chang-Hua Xu

Authors
  1. Li Zhu
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  2. Yu Yan
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  3. Dong-Chen Gu
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  4. Ying Lu
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  5. Jian-Hong Gan
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  6. Ning-Ping Tao
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  7. Xi-Chang Wang
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  8. Chang-Hua Xu
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Correspondence to Xi-Chang Wang or Chang-Hua Xu.

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Conflict of Interest

Chang-Hua Xu has no conflict of interest. This manuscript has not been published in whole or in part nor is it being considered for publication elsewhere. Li Zhu declares that he has no conflict of interest. Yu Yan declares that he has no conflict of interest. Dong-Chen Gu declares that he has no conflict of interest. Ying Lu declares that she has no conflict of interest. Fu-Lan Guan has no conflict of interest.  Jian-Hong Gan declares that he has no conflict of interest. Ning-Ping Tao declares that he has no conflict of interest. Yue Zhang has no conflict of interest. Xi-Chang Wang declares that he has no conflict of interest. Chang-Hua Xu declares that he has no conflict of interest.

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Zhu, L., Yan, Y., Gu, DC. et al. Rapid Quality Discrimination and Amino Nitrogen Quantitative Evaluation of Soy Sauces by Tri-Step IR and E-nose. Food Anal. Methods 11, 3201–3210 (2018). https://doi.org/10.1007/s12161-018-1284-0

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  • DOI: https://doi.org/10.1007/s12161-018-1284-0

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