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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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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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