Rapid Identification of Pseudomonas spp. in Chicken by Near-infrared Spectroscopy
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Pseudomonas spp. is the main bacteria involved chicken degradation which ultimately affects the meat quality and the potential of posing health public health threats. The use of near infrared spectroscopy (NIRS) for rapid identification and monitoring of four strains of Pseudomonas spp. in degrading chicken was attempted. Initially, four Pseudomonas strains namely Pseudomonas gessardii, Pseudomonas psychrophila, Pseudomonas fragi and Pseudomonas fluorescens were isolated from samples of degrading chicken and identified via polymerase chain reaction (PCR) technology. The different isolated Pseudomonas spp. were cultured in trypticase soy broth (TSB) and incubated at 30℃ for 12 h to growth. The four isolates of Pseudomonas spp. and their combined mixture in equal proportions were all prepared from the incubated inoculum by using 100mL∶5mL and each replicated 40 times. The preprocessed data outcomes of the 200 samples using standard normal variable transformation (SNV) exhibited superiority compared with other deployed data preprocessing algorithms such as multiplicative scatter correction (MSC), calibration standard score, first derivative (DB1) and second derivative (DB2). Synergy interval partial least squares (SiPLS) was employed to select relevant characteristics wavelengths such as 3999.64~4597.46cm-1, 6406.37~7004.19cm-1, 8211.41~8805.38cm-1 and 8809.24~9403.20cm-1. Principal component analysis (PCA) was performed prior to the model development with loadings of 97.02% in PC1, 2.47% in PC2 and 0.27% in PC3 which indicated the possibility of developing models for the classification of the different samples of Pseudomonas spp. The recognition rates for KNN (65.00%, 63.75%), SVM (91.67%, 86.25%) and BP-ANN (99.17%, 95.00%) were obtained in the training and prediction sets. The model results obtained for SVM was sufficiently high and may be combined with NIRS system for the possible Pseudomonas spp. classification. However, the best result was obtained with BP-ANN built model. These high recognition rates implied near-infrared spectroscopy combined with BP-ANN can be deployed for the rapid detection of different Pseudomonas spp. strains in chicken for the purpose of safeguarding its deteriorating chicken quality.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 16,2016
  • Revised:
  • Adopted:
  • Online: August 10,2017
  • Published: