title: Prediction of total volatile basic nitrogen contents using wavelet features from visible/near-infrared hyperspectral images of prawn (Metapenaeus ensis).
abstract: A visible/near-infrared hyperspectral imaging (HSI) system (400-1000 nm) coupled with wavelet analysis was used to determine the total volatile basic nitrogen (TVB-N) contents of prawns during cold storage. Spectral information was denoised by conducting wavelet analysis and uninformative variable elimination (UVE) algorithm, and then three wavelet features (energy, entropy and modulus maxima) were extracted. Quantitative models were established between the wavelet features and the reference TVB-N contents by using three regression algorithms. As a result, the LS-SVM model with modulus maxima features was considered as the best model for determining the TVB-N contents of prawns, with an excellent RP(2) of 0.9547, RMSEP=0.7213 mg N/100g and RPD=4.799. Finally, an image processing algorithm was developed for generating a TVB-N distribution map. This study demonstrated the possibility of applying the HSI imaging system in combination with wavelet analysis to the monitoring of TVB-N values in prawns.
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China.
authors.forename: Qiong
authors.initials: Q
authors.lastname: Dai
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China.
authors.forename: Jun-Hu
authors.initials: JH
authors.lastname: Cheng
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China; Food Refrigeration and Computerized Food Technology, Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland. Electronic address: dawen.sun@ucd.ie.
authors.forename: Da-Wen
authors.initials: DW
authors.lastname: Sun
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Zhu
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Pu
mesh_terms: D000465:Algorithms; D000818:Animals; D005504:Food Analysis; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D009584:Nitrogen / Q000032:analysis*; D033561:Penaeidae / Q000737:chemistry*; D017747:Seafood / Q000032:analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D058067:Wavelet Analysis
chemical_list: D009584:Nitrogen
keywords: Hyperspectral image; Prawn; TVB-N; Total volatile basic nitrogen; Wavelet analysis