Food and Fermentation Industries >

2022 , Vol. 48 >Issue 20: 36 - 43

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.029991

Tracing the origin of Red Fuji apple based on variable optimization and near-infrared spectroscopy

  • 张立欣 ,
  • 杨翠芳 ,
  • 陈杰 ,
  • 张晓果 ,
  • 张楠楠 ,
  • 张晓
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  • 1(College of Information Engineering, Tarim University, Alar Xinjiang Uygur Autonomous Region, Alaer 843300, China)
    2(School of Science, Nanjing University of Science and Technology, Nanjing 210094, China)
    3(School of Mathematics and Physics, Henan University of Urban Construction, Pingdingshan 467036, China)

Received date: 2020-11-06

  Revised date: 2021-12-17

  Online published: 2022-11-18

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Abstract

Near-infrared spectrum data of Red Fuji apples from Aksu, Jingning, Lingbao, and Yantai were collected to trace the origin of Red Fuji apples. Nine methods including normalization (NOR), centralization (CEN), first derivative (1-DER), second derivative (2-DER), standard normal transform (SNV), multivariate scattering correction (MSC), wavelet transform (WT), SG smoothing transform (SG), and Fourier transform (FT) were used to preprocess the original spectrum. Results showed that the model after multivariate scattering correction pretreatment had the highest recognition rate of 97.5%, and the recognition rates of Aksu, Jingning, Lingbao, and Yantai were 100%, 100%, 90%, and 100%, respectively. To simplify the model, principal component analysis (PCA), successive projection algorithm (SPA), competitive adaptive reweighted sampling (CARS), random frog (RF), and their combination algorithms were used to select characteristic variables. Results showed that the total recognition rate of MSC-CARS-SPA-PNN was 98.75%, and the recognition rates of Red Fuji apples from four producing areas were 100%, 100%, 95%, and 100%, respectively, which could provide theoretical reference for the origin discrimination of Red Fuji apples.

Key words： apple; near-infrared spectrum; probabilistic neural network; successive projection algorithm; competitive adaptive reweighted sampling

Cite this article

张立欣 , 杨翠芳 , 陈杰 , 张晓果 , 张楠楠 , 张晓 . Tracing the origin of Red Fuji apple based on variable optimization and near-infrared spectroscopy[J]. Food and Fermentation Industries, 2022 , 48(20) : 36 -43 . DOI: 10.13995/j.cnki.11-1802/ts.029991

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