Non-destructive apple bruise detection with Raman spectroscopy and its virtual instrumentation

Xiaoyang Gao, Paul Heinemann, Joseph Irudayaraj

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A prototype automated inspection system was developed to classify apples based on bruising in real time. A Nicolet FT-Raman Spectroscope was employed to obtain apple spectra. The spectroscope utilized OMNIC E. S. P. 5.1 software. The unbruised and bruised spectra were analyzed and classified by WinDAS using canonical variate analysis (CVA) and principal component analysis (PCA) models, on both the training and testing sets. The PCA and CVA model analysis satisfactorily classified the apples by bruise, then the UNEQ class modeling was used and the square of Mahalanobis distance passed X2 test. Besides, LabWIEW was applied to develop apple grading control system, and prototype of virtual instrumental system was fabricated. The experiments show that the Raman spectroscope permits non-destructive bruise determination with good results and the virtual instrument grading system has a good accuracy.

Original languageEnglish (US)
Pages (from-to)130-133
Number of pages4
JournalNongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Volume21
Issue number3
StatePublished - Mar 1 2005

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences(all)
  • Mechanical Engineering

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