Literature DB >> 329759

Rapid detection of microbial contamination in frozen vegetables by automated impedance measurements.

D Hardy, S J Kraeger, S W Dufour, P Cady.   

Abstract

Automated impedance measurements can be used to rapidly assess whether a sample of frozen vegetables contains greater or less than 10(5) organisms per g. Microorganisms growing pureed food samples cause a change in the impedance of the medium when the organisms reach a threshold concentration of between 10(6) and 10(7) organisms per ml. Estimates of the concentration of microorganisms initially present in the food sample can be made by recording the time required for the organisms in the sample to replicate to threshold levels. In this study, the detection times for 357 samples of frozen vegetables were compared with standard plate counts for each sample. The agreement between the two methods in distinguishing samples containing more than 10(5) organisms per g was 92.6% for 257 assorted frozen vegetables and somewhat higher (93 to 96%) when separate cutoff times were used for each type of vegetable. The time required for analysis was about 5 h, compared to the 48 to 72 h required for standard plate counts.

Mesh:

Year:  1977        PMID: 329759      PMCID: PMC242580          DOI: 10.1128/aem.34.1.14-17.1977

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  2 in total

1.  Quick counting method for estimating the number of viable microbes on food and food processing equipment.

Authors:  F H Winter; G K York; H el-Nakhal
Journal:  Appl Microbiol       Date:  1971-07

2.  Radiometric detection of some food-borne bacteria.

Authors:  J J Previte
Journal:  Appl Microbiol       Date:  1972-10
  2 in total
  10 in total

1.  Electrode system for the determination of microbial populations.

Authors:  T Matsunaga; I Karube; S Suzuki
Journal:  Appl Environ Microbiol       Date:  1979-01       Impact factor: 4.792

2.  Determination of microbial populations with piezoelectric membranes.

Authors:  Y Ishimori; I Karube; S Suzuki
Journal:  Appl Environ Microbiol       Date:  1981-10       Impact factor: 4.792

3.  Rapid, single-step most-probable-number method for enumerating fecal coliforms in effluents from sewage treatment plants.

Authors:  E F Munoz; M P Silverman
Journal:  Appl Environ Microbiol       Date:  1979-03       Impact factor: 4.792

4.  The impedance method for monitoring total coliforms in wastewaters. Part I. Background and methodology.

Authors:  W M Strauss; G W Malaney; R D Tanner
Journal:  Folia Microbiol (Praha)       Date:  1984       Impact factor: 2.099

5.  Enumeration of micro-organisms in food: a comparative study of five methods.

Authors:  J M Kramer; R J Gilbert
Journal:  J Hyg (Lond)       Date:  1978-08

6.  Evaluation of a rapid method for the quantitative estimation of coliforms in meat by impedimetric procedures.

Authors:  S B Martins; M J Selby
Journal:  Appl Environ Microbiol       Date:  1980-03       Impact factor: 4.792

7.  Electrode system for determination of microbial cell populations in polluted water.

Authors:  Y Maoyu; Y Zhang
Journal:  Appl Environ Microbiol       Date:  1989-08       Impact factor: 4.792

8.  Dye-coupled electrode system for the rapid determination of cell populations in polluted water.

Authors:  S Nishikawa; S Sakai; I Karube; T Matsunaga; S Suzuki
Journal:  Appl Environ Microbiol       Date:  1982-04       Impact factor: 4.792

9.  Automated detection of microbial growth in blood cultures by using stainless-steel electrodes.

Authors:  R L Holland; B H Cooper; N G Helgeson; A W McCracken
Journal:  J Clin Microbiol       Date:  1980-08       Impact factor: 5.948

10.  Computer Vision Approach for the Determination of Microbial Concentration and Growth Kinetics Using a Low Cost Sensor System.

Authors:  Marco Grossi; Carola Parolin; Beatrice Vitali; Bruno Riccò
Journal:  Sensors (Basel)       Date:  2019-12-05       Impact factor: 3.576

  10 in total

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