Xue Xiao

Publications (2)6.62 Total impact

• Article: Classification and analysis of corn steep liquor by UPLC/Q-TOF MS and HPLC.

  Xue Xiao, Yuanyuan Hou, Yang Liu, Yanjie Liu, Hongzhi Zhao, Linyi Dong, Jun Du, Yiming Wang, Gang Bai, Guoan Luo
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  ABSTRACT: Corn steep liquor (CSL), an important raw material with high nutritional value, serves as a nitrogen source in the fermentation industry. The CSL quality directly affects the yield and quality of fermentation products. In this work, a fingerprinting technique was used to identify the potential markers of CSL. Forty-two CSL samples from different manufacturers were profiled by ultra-performance liquid chromatography with tandem quadrupole time-of-flight mass spectrometry. Sixteen compounds, almost all of which were amino acids and their derivatives, were considered as the potential markers. Then, o-phthalaldehyde-9-fluorenylmethyl chloroformate precolumn derivatization by high-performance liquid chromatography was performed to identify the free amino acids in CSL. Principal component analysis (PCA) was used to distinguish among the samples from different manufacturers. The results demonstrated that the fingerprinting technique combined with PCA analysis was a powerful tool for determining the CSL quality.
  Talanta 03/2013; 107C:344-348. · 3.79 Impact Factor
• Article: Determination of main categories of components in corn steep liquor by near-infrared spectroscopy and partial least-squares regression.

  Xue Xiao, Yuanyuan Hou, Jun Du, Yang Liu, Yanjie Liu, Linyi Dong, Qionglin Liang, Yiming Wang, Gang Bai, Guoan Luo
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  ABSTRACT: Corn steep liquor (CSL) is an important raw material that has a high nutritional value and serves as a nitrogen source. This study aimed to develop a fast, versatile, cheap, and environmentally safe analytical method of quantifying the total acidity (TA) of CSL as well as its contents of dry matter (DM), total sugars (TS), total reducing sugars (TRS), total free amino acids (TFAA), total nitrogen (TN), and total sulfite (TSu). The near-infrared (NIR) spectroscopy measurements of 66 samples (22 batches) of CSL were analyzed by partial least-squares regression using several spectral preprocessing methods. Multivariate models developed in the NIR area showed good predictive abilities for DM, TA, TS, TRS, TFAA, TN, and TSu determination. These results confirm the feasibility of the multivariate spectroscopic approach as a replacement for expensive and time-consuming conventional chemical methods. Thus, a convenient and feasible method for the quality control of fermentation raw materials for food additives and fine chemicals, especially in CSL, is established.
  Journal of Agricultural and Food Chemistry 07/2012; 60(32):7830-5. · 2.82 Impact Factor