title: E-nose identification of Salmonella enterica in poultry manure.
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.
authors: a Department of Agricultural Structures and Irrigation, Agricultural Sensor and Remote Sensing Laboratory , Çanakkale Onsekiz Mart University , Çanakkale , Turkey.
authors: Ü
authors: Ü
authors: Kizil
authors: L
authors: L
authors: Genç
authors: T T
authors: TT
authors: Genç
authors: S
authors: S
authors: Rahman
authors: M L
authors: ML
authors: Khaitsa
mesh_terms: D000822:Animal Husbandry; D000818:Animals; D002645:Chickens; D062609:Electronic Nose / Q000662:veterinary*; D004784:Environmental Monitoring / Q000379:methods*; D008372:Manure / Q000382:microbiology*; D016571:Neural Networks, Computer; D011201:Poultry Diseases / Q000175:diagnosis* / Q000382:microbiology; D012481:Salmonella Infections, Animal / Q000175:diagnosis* / Q000382:microbiology; D019779:Salmonella enterica / Q000302:isolation & purification*; D014421:Turkey
chemical_list: D008372:Manure