Food and Bioprocess Technology

, Volume 7, Issue 5, pp 1496–1504 | Cite as

Prediction of Aerobic Plate Count on Beef Surface Using Fluorescence Fingerprint

  • Masatoshi Yoshimura
  • Junichi SugiyamaEmail author
  • Mizuki Tsuta
  • Kaori Fujita
  • Mario Shibata
  • Mito Kokawa
  • Seiichi Oshita
  • Naomi Oto
Original Paper


The potential of fluorescence fingerprint (FF) spectroscopy was investigated to develop a nondestructive prediction method of aerobic plate count on a beef surface. Sixty samples (e.g., 30 lean meat slices each of Australian cattle and Japanese cattle) stored aerobically at 15 °C were analyzed by front-face fluorescence spectrophotometry. FF and aerobic plate count (APC) were measured after 0, 12, 24, 36, and 48 h of storage. FFs were collected in both excitation and emission wavelength ranges of 200–900 nm. Partial least-squares regression (PLSR) performed on an FF dataset predicted an APC in the bacterial contamination load range from 1.7 to 7.8 log colony-forming units (cfu)/cm2 with a prediction error of 0.752 log cfu/cm2. The regions where the regression coefficient of the PLSR model was relatively high were consistent with those of the FF peaks of five intrinsic fluorophores: tryptophan, NAD(P)H, vitamin A, porphyrins, and flavins. This suggests that changes in the autofluorescence of these intrinsic fluorophores due to the metabolism of bacterial flora on meat are reflected in the PLSR model for predicting APC from the FF dataset. FF spectroscopy coupled with multivariate analysis appeared to be applicable to the nondestructive determination of APC on the surface of lean beef.


Aerobic plate count Sanitary control Excitation emission matrix Partial least-squares regression Beef 



This research was funded by the research and development projects for application in promoting new policy of the Ministry of Agriculture, Forestry and Fisheries (22040), Japan.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Masatoshi Yoshimura
    • 1
  • Junichi Sugiyama
    • 1
    Email author
  • Mizuki Tsuta
    • 1
  • Kaori Fujita
    • 1
  • Mario Shibata
    • 1
  • Mito Kokawa
    • 2
  • Seiichi Oshita
    • 2
  • Naomi Oto
    • 2
  1. 1.Food Engineering Division, National Food Research InstituteNational Agriculture and Food Research OrganizationTsukubaJapan
  2. 2.Graduate School of Agricultural and Life SciencesThe University of TokyoTokyoJapan

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