Multicomposition analysis and pattern recognition of Chinese geographical indication product: vinegar

• DOI: 10.1007/s00217-013-2135-2
• Publication Date: 2013-12-28T08:35:38Z
• Authors: Yanjie Zheng; Guihua Ruan; Bifang Li; Cen Xiong; Sujuan Chen; Meizhong Luo; Yongle Li; Fuyou Du
• Keywords: 0404 agricultural biotechnology; 04 agricultural and veterinary sciences; 0405 other agricultural sciences

Multicomposition fingerprints with several chemical compositions containing inorganic elements and organic compounds (amino acids, polyhydric alcohols, organic acids) were measured to distinguish two geographical indication-protected vinegars (GIs) from general vinegars (nGIs). The two of GIs were named Shanxi extra aged vinegar and Zhenjiang vinegar from Shanxi and Jiangsu province, respectively. Principal component analysis and Fisher linear discriminant methods were applied for the pattern recognition and classification of GI product. It was not suitable by simply using one kind of composition to make a distinction between GIs and nGIs. However, by using multicomposition to build a classify model, the classification of SXVs was described by Co, As, Al, Mg, Ca, erythritol, arabitol, sorbitol, proline, lysine and pyruvic acid, while ZJVs classification was described by threonine, serine, glycine, lysine, Ba, erythritol, xylitol and lactic acid. The GI samples can be classified with high accuracy according to the discriminant model, of which the false rate is 3.88 % in SXVs model and 10.85 % in ZJVs model. This method can be a useful method for protecting the geographical indication vinegars from the fake or adulterate vinegar commodities.