JIA Junjie, ZHANG Suyi, XU Tao, et al. Discrimination of Strong Aroma-type Baijiu of Different Origins Based on Ag Nanoprism Etching Mechanism[J]. Science and Technology of Food Industry, 2024, 45(10): 254−262. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023070018.
Citation: JIA Junjie, ZHANG Suyi, XU Tao, et al. Discrimination of Strong Aroma-type Baijiu of Different Origins Based on Ag Nanoprism Etching Mechanism[J]. Science and Technology of Food Industry, 2024, 45(10): 254−262. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023070018.

Discrimination of Strong Aroma-type Baijiu of Different Origins Based on Ag Nanoprism Etching Mechanism

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  • Received Date: July 04, 2023
  • Available Online: March 20, 2024
  • Discriminating strong aroma-type Baijiu (SAB) of different origins was significant for product quality control and origin protection. In this study, a 4×3 sensor array was constructed based on the Ag nanoprism (AgNPR) etching mechanism, in which four AgNPRs varying in shape and size were used as sensing materials, and two metal ions and one oxide anion were used as oxidation etchants. With this array, colorimetric reaction was conducted on 41 representative SAB samples from Sichuan, Jianghuai and North China. The obtained colorimetric signal values were subjected to linear discriminant analysis (LDA). Furthermore, some samples of unknown origin were selected to perform external validation on the discrimination model. Based on the results of colorimetric reaction mechanism, the samples could promote the etching effect of AgNPRs, which might be related to various organic acids contained in Baijiu. Sample discrimination showed that single array produced a comparatively low effect on samples of different origins. The combination of three arrays significantly improved the discrimination effect, whose rate of origin discrimination was up to 99% for 41 samples, and was up to 98% for 15 unknown samples. With combined array, the discriminant rates of 21 samples from 5 brands in Sichuan and 13 samples from 3 brands in Jianghuai could reach 99% and 100%, respectively, while all the discriminant rates could reach 100% for different grades of products from various manufacturers in Sichuan with single array. Being simple and fast, the nanocolorimetric sensing method adopted in this study is not only applicable to product identification and anti-counterfeiting, but also be auxiliarily used for quality control in production process, laying a research foundation for intelligent quality monitoring of Baijiu.
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