Preprint Article Version 1 This version is not peer-reviewed

Artificial Intelligence and Innovative Surveillance Methods—An Additional Value in Livestock Farming?

Matthias Eddicks
ORCID logo ,
Franziska Feicht
,
Jochen Beckjunker
,
Marika Genzow
,
Carmen Alonso
ORCID logo ,
Sven Reese
ORCID logo ,
Mathias Ritzmann
,
Julia Stadler
* ORCID logo
Version 1 : Received: 2 September 2024 / Approved: 3 September 2024 / Online: 3 September 2024 (09:41:16 CEST)

How to cite: Eddicks, M.; Feicht, F.; Beckjunker, J.; Genzow, M.; Alonso, C.; Reese, S.; Ritzmann, M.; Stadler, J. Artificial Intelligence and Innovative Surveillance Methods—An Additional Value in Livestock Farming?. Preprints 2024, 2024090222. https://doi.org/10.20944/preprints202409.0222.v1 Eddicks, M.; Feicht, F.; Beckjunker, J.; Genzow, M.; Alonso, C.; Reese, S.; Ritzmann, M.; Stadler, J. Artificial Intelligence and Innovative Surveillance Methods—An Additional Value in Livestock Farming?. Preprints 2024, 2024090222. https://doi.org/10.20944/preprints202409.0222.v1

Abstract

Artificial intelligence (A.I.) is the key to process big amounts of data to useful information for operators. In the present study the suitability of a 24/7 A.I. sound based coughing monitoring system for early detection of respiratory distress caused by porcine respiratory disease complex (PRDC) associated pathogens was assessed in the nursery of a conventional pig farm. Screening for PRDC associated pathogens was conducted by PCR examination of oral fluids (OFs) and bioaerosol samples (AS). A significant correlation between A.I. and human gained health data was observed in both batches. An increase in coughing episodes, either measured by A.I. or human, was significantly correlated with decreasing Ct-values of swIAV. The Odds to detect nucleic acids of PRRSV or Actinobacillus (A.) pleuropneumonia was significantly higher for OFs compared to AS. Moreover, PCR examinations of OFs revealed significantly lower Ct-values for swIAV and A. pleuropneumonia compared to AS. The quantity of swIAV RNA in OFs and AS was significantly associated with the A.I. calculated respiratory health score and thus, with clinical disease. Due to its reliable data A.I. based health monitoring is beneficial for early recognition of respiratory distress and thus can assist farmer’s daily work.

Keywords

surveillance; sample types; novel; diagnostics; respiratory disease; Influenza; oral fluids; bioaerosol samples

Subject

Medicine and Pharmacology, Veterinary Medicine

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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