Quality of Vegetable Products: Assessment of Physical, Chemical, and Microbiological Changes in Vegetable Products by Nondestructive Methods

  • Wenqian Huang
  • Jiangbo Li
  • Baohua Zhang
  • Shuxiang Fan
Part of the Food Microbiology and Food Safety book series (FMFS)


This chapter focuses on quality and safety evaluation of the vegetable products using different sensing technologies, imaging processing, and chemometric methods. It provides an overview of the instruments used for evaluating the quality of vegetable products such as computer vision, multispectral imaging, near-infrared spectroscopy, and hyperspectral imaging (refer to Sect. 2). Then, the basic analysis methods and chemometrics are introduced in detail (Sect. 3), including image/spectral preprocessing and correction/calibration, feature and band extraction and sample selection, and analysis models and evaluation. Finally, the potential applications of the instruments and the basic analysis methods in vegetable product quality and safety analysis and control are explained (Sect. 4). The external qualities such as shape, size, color, texture, and defects; internal qualities such as soluble solid content (SSC), acid content, and internal defects; and microbiological changes such as microbial and fecal contamination are discussed in detail. Conclusions and future works are proposed (Sect. 5).


Vegetable products Quality Safety Computer vision Near-infrared spectroscopy Spectral imaging Chemometrics 



Artificial neural network


Attenuated total reflectance


Airborne visible/infrared imaging spectrometer


Band difference


Backward/forward interval partial least squares


Band ratio


Competitive adaptive reweighted sampling


Charge-coupled device


Computer vision system


Discriminant analysis


Discrete cosine transform


Discrete Fourier transform


Discriminant partial least squares


Fourier transform infrared


Fourier transform near-infrared


Genetic algorithms


Genetic algorithm interval partial least squares


Good agricultural practices


Good manufacturing practices


Hazard analysis of critical control points


Hyperspectral imaging system


Hue, saturation, and intensity


Independent component analysis


Interval partial least squares


International Organization for Standardization


Kernel nonlinear analysis


Kernel neural network




Linear discriminant analysis


Least squares support vector machine


Latent variable


Multilayer perceptron


Multiple linear regression


Multiplicative scatter correction


Moving window partial least squares regression


National Aeronautics and Space Administration


Near-infrared spectroscopy


Orthogonal signal correction


Principal component analysis


Principal component regression


Partial least squares


Partial least squares discriminant analysis


Partial least squares regression


Correlation coefficient


Radial basis function


Red, green, blue


Root mean square error of calibration


Root mean square error of cross-validation


Root mean square error of prediction


Root mean square error of validation


Receiver operating characteristic


Residual predictive deviation


Random sampling


Relative standard deviation


Regression trees


Simulated annealing algorithm


Standard error of calibration


Standard error of cross-validation


Scanning electron microscopy


Standard error of prediction


Standard error of validation


Spectral information divergence


Soft independent modeling of class analogy


Synergy interval partial least squares


Standard normal variate


Successive projection algorithm


Sample set partitioning based on joint x–y distances


Soluble solids content




Elimination of uninformative variables


Variable importance in projection


Visible and near-infrared


Wavelet transformation


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Wenqian Huang
    • 1
    • 2
    • 3
    • 4
  • Jiangbo Li
    • 1
    • 2
    • 3
    • 4
  • Baohua Zhang
    • 1
    • 2
    • 3
    • 4
  • Shuxiang Fan
    • 1
    • 2
    • 3
    • 4
  1. 1.Beijing Research Center for Information Technology in AgricultureBeijingChina
  2. 2.Beijing Research Center of Intelligent Equipment for AgricultureBeijingChina
  3. 3.National Engineering Research Center for Information Technology in AgricultureBeijingChina
  4. 4.National Research Center of Intelligent Equipment for AgricultureBeijingChina

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