Pokaż uproszczony rekord

Applied Sciences-Basel

dc.contributor.authorPakuła, A.
dc.contributor.authorPaśko, S.
dc.contributor.authorMarć, P.
dc.contributor.authorKursa, O.
dc.contributor.authorJaroszewicz, L.
dc.description.abstractRapid detection of Mycoplasma synoviae (MS) in a flock is crucial from the perspective of animals’ health and economic income. MS are highly contagious bacteria that can cause significantlosses in commercial poultry populations when its prevalence is not limited. MS infections cancause losses associated with a range of clinical symptoms related to the respiratory, mobility andreproductive systems. Lesions related to the reproductive system and changes in the eggshell result in losses associated with infection or embryo death or complete destruction of the eggs. The authors propose using spectral measurements backed up by an AI data processing algorithm to classify eggs’ origin: from healthy hens or MS-infected ones. The newest obtained classification factors are F-scores for white eggshells of 99% and scores for brown eggshells of 99%—all data used for classification were obtained using a portable multispectral fibre-optics reflectometer. The proposed method may be used directly on the farm by staff members with limited qualifications, as well as by veterinary doctors, assistants, or customs officers. Moreover, this method is scalable to mass production of eggs.Standard methods such as serological tests require either specialized staff or laboratory equipment.Implementation of a non-destructive optical measurement method, which is easily adapted for use on a production line, is economically reasonable
dc.subjectpathogen detection
dc.subjectMycoplasma synoviae
dc.subjectoptical measurements
dc.subjectspectral measurements
dc.subjectoptical spectroscop
dc.subjectmachine learning
dc.subjectartificial intelligence AI
dc.subjectorigin classification
dc.subjectfood safety
dc.subjectfood monitoring
dc.titleAI Classification of Eggs’ Origin from Mycoplasma synoviae-Infected or Non-Infected Poultry via Analysis of the Spectral Response
dcterms.bibliographicCitation2023 vol. 13 nr 22, 12360
dcterms.titleApplied Sciences-Basel

Pliki tej pozycji


Pozycja umieszczona jest w następujących kolekcjach

Pokaż uproszczony rekord