Distinction and Recognition of the 'Black Pearl' Fresh Corn Origin Based on Electronic Nose and BP Neural Network

MA Hongjiang; HAO Xiyu; GAO Ming; YU Youqiang; YANG Shuheng; LIU Shiwei; MA Xishan; WANG Wenxin; DUAN Shenglin; WANG Xue

doi:10.13386/j.issn1002-0306.2023070135

Volume 45 Issue 13

Jun. 2024

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Science and Technology of Food Industry > 2024 > 45(13): 239-245. > DOI: 10.13386/j.issn1002-0306.2023070135

MA Hongjiang, HAO Xiyu, GAO Ming, et al. Distinction and Recognition of the 'Black Pearl' Fresh Corn Origin Based on Electronic Nose and BP Neural Network[J]. Science and Technology of Food Industry, 2024, 45(13): 239−245. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023070135.

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Distinction and Recognition of the 'Black Pearl' Fresh Corn Origin Based on Electronic Nose and BP Neural Network

1.
Heilongjiang Beiwei 47 Green Organic Food Co., Ltd., Qiqihar 161532, China
2.
Heilongjiang Feihe Dairy Co., Ltd., Beijing 100016, China
3.
China National Research Institute of Food & Fermentation Industries Co., Ltd., Beijing 100015, China

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Received Date: July 16, 2023
Available Online: April 26, 2024

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Abstract

Abstract

: 'Black pearl' fresh corns from different regions were analyzed using an electronic nose to capture the aroma profile. Principal component analysis (PCA) and discriminant function analysis (DFA) were used for multivariate statistical analysis of 200 data from two regions. Based on this, the judgment model of samples from Heilongjiang production area was built using a soft independent modeling class analysis (SIMCA) algorithm, and a back propagation neural network model was established by Pytorch software to identify and differentiate samples from different regions. The results illustrated that, although the volatile flavor of 'black pearl' fresh corns from different origins were similar, it also showed obvious origin characteristics. SIMCA model could effectively distinguish whether unknown samples come from Heilongjiang (the accuracy rate was 97%), while BP neural network model could predict and identify the origin of 'black pearl' fresh corns from unknown production areas, and the average accuracy rate was 99.44%. The combination of electronic nose technology and BP neural network model could accurately distinguish and identify the origin of 'black pearl' fresh corns.

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