Use of near infrared spectroscopy to predict microbial numbers on Atlantic salmon

The potential of a near infrared spectroscopy (NIR) method to detect as well as predict microbial spoilage on Atlantic salmon ( Salmo salar ) was investigated. Principal component analysis (PCA) of the NIR spectra showed clear separation between the fresh salmon fillets and those stored for nine day...

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Bibliographic Details
Published in:Food Microbiology
Main Authors: Tito, NB, Rodemann, T, Powell, SM
Format: Article in Journal/Newspaper
Language:English
Published: Academic Press Ltd Elsevier Science Ltd 2012
Subjects:
Biological Sciences
Microbiology
Microbiology not elsewhere classified
Atlantic salmon
Salmo salar
Online Access:https://doi.org/10.1016/j.fm.2012.07.009
http://www.ncbi.nlm.nih.gov/pubmed/22986211
http://ecite.utas.edu.au/74215
Description
Summary:The potential of a near infrared spectroscopy (NIR) method to detect as well as predict microbial spoilage on Atlantic salmon ( Salmo salar ) was investigated. Principal component analysis (PCA) of the NIR spectra showed clear separation between the fresh salmon fillets and those stored for nine days at 4°C indicating that NIR could detect spoilage. A partial least squares regression (PLS) prediction model for total aerobic plate counts after nine days was established using the NIR spectra collected when the fish was fresh to predict the number of bacteria that would be present nine days later. The calibration equation was good (R 2 =0.95 and RMSE=0.12logcfu/g) although the error of the validation curve was larger (R 2 =0.64 and RMSE=0.32logcfu/g). These results indicate that with further model development, it may be possible to use NIR to predict bacterial numbers, and hence shelf-life, in Atlantic salmon and other seafood.

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