Literature DB >> 25650129

E-nose identification of Salmonella enterica in poultry manure.

Ü Kizil1, L Genç, T T Genç, S Rahman, M L Khaitsa.   

Abstract

A DiagNose II electronic nose (e-nose) system was tested to evaluate the performance of such systems in the detection of the Salmonella enterica pathogen in poultry manure. To build a database, poultry manure samples were collected from 7 broiler houses, samples were homogenised, and subdivided into 4 portions. One portion was left as is; the other three portions were artificially infected with S. enterica. An artificial neural network (ANN) model was developed and validated using the developed database. In order to test the performance of DiagNose II and the ANN model, 16 manure samples were collected from 6 different broiler houses and tested using these two systems. The results showed that DiagNose II was able to classify manure samples correctly as infected or non-infected based on the ANN model developed with a 94% level of accuracy.

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Year:  2015        PMID: 25650129     DOI: 10.1080/00071668.2015.1014467

Source DB:  PubMed          Journal:  Br Poult Sci        ISSN: 0007-1668            Impact factor:   2.095


  2 in total

Review 1.  Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review.

Authors:  Ernest Bonah; Xingyi Huang; Joshua Harrington Aheto; Richard Osae
Journal:  J Food Sci Technol       Date:  2019-11-05       Impact factor: 2.701

Review 2.  Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock.

Authors:  Pablo Rodríguez-Hernández; Vicente Rodríguez-Estévez; Lourdes Arce; Jaime Gómez-Laguna
Journal:  Front Vet Sci       Date:  2021-05-24
  2 in total

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