Comparison of models and visualization of total volatile basic nitrogen content in mutton using hyperspectral imaging and variable selection methods

Yuanyuan Qiu, Rongguang Zhu, Zhongjian Fan, Xuedong Yao, Elfed Lewis

Research output: Contribution to journalArticlepeer-review

Abstract

Hyperspectral imaging combined with variable selection methods was used to perform the rapid and accurate detection and visualization of total volatile basic nitrogen content in mutton. For each sample, several spectra were extracted from the region of muscle pixels for modeling, and the model performance was improved and better than the model established with average spectrum extracting from each sample. By two steps of variable screening with competitive adaptive reweighted sampling and stepwise regression methods, the efficient dimensionality reduction of spectral data was achieved, and the important characteristic variables were selected. The nonlinear model significantly improved the model predictive capability, and the visualization distribution map based on the model was consistent with the actual change of meat spoilage.

Original languageEnglish
Pages (from-to)226-235
Number of pages10
JournalSpectroscopy Letters
Volume51
Issue number5
DOIs
Publication statusPublished - 28 May 2018
Externally publishedYes

Keywords

  • Characteristic variable selection
  • hyperspectral imaging
  • rapid and accurate detection
  • total volatile basic nitrogen
  • visualization

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