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A Hybrid Model for Nondestructive Measurement of Internal Quality of Peach

  • Yongni Shao
  • Yong He
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 345)

Abstract

A nondestructive optical method for determining the sugar and acidity contents of peach was investigated. Two types of preprocessing were used before the data were analyzed with multivariate calibration methods of principle component analysis (PCA) and partial least squares (PLS). A hybrid model combined PLS with PCA was put forwarded. Spectral data set as the logarithms of the reflectance reciprocal was analyzed to build a best model for predicting the sugar and acidity contents of peach. A model with a correlation coefficient of 0.94/0.92, a standard error of prediction (SEP) of 0.50/0.07 and a bias of 0.02/−0.01 showed an excellent prediction performance to sugar/acidity. At the same time, the sensitive wavelengths corresponding to the sugar content and acidity of peaches or some element at a certain band were proposed on the basis of regression coefficients by PLS.

Keywords

Sugar Content Principle Component Analysis Partial Little Square Model Near Infrared Spectroscopy Multivariate Calibration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yongni Shao
    • 1
  • Yong He
    • 1
  1. 1.College of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhouChina

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