Classification and correlation of coughing sounds and disease status in fattening pigs

There have been attempts to use technology to distinguish pig coughs from other sounds on farms. Machine learning is being used to classify pig coughs via python. Sound files have been converted to images that are composed of wave plots,spectrograms and log power spectrograms for identifica...

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Main Authors: Panuwat Yamsakul, Terdsak Yano, Kannika Na Lampang, Manad Khamkong, Lertrak Srikitjakarn
Format: Article
Language:English
Published: Faculty of Veterinary Medicine, Chiang Mai University 2023-02-01
Series:Veterinary Integrative Sciences
Online Access:https://he02.tci-thaijo.org/index.php/vis/article/view/260914
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author Panuwat Yamsakul
Terdsak Yano
Kannika Na Lampang
Manad Khamkong
Lertrak Srikitjakarn
author_facet Panuwat Yamsakul
Terdsak Yano
Kannika Na Lampang
Manad Khamkong
Lertrak Srikitjakarn
author_sort Panuwat Yamsakul
collection DOAJ
description There have been attempts to use technology to distinguish pig coughs from other sounds on farms. Machine learning is being used to classify pig coughs via python. Sound files have been converted to images that are composed of wave plots,spectrograms and log power spectrograms for identification of those sounds. A recorder was used with a total of 45 healthy three-bred weaned piglets, wherein three replications of each were used with 15 weaning pigs per pen during different months. This process was set up within the housing unit at a ratio as 1:1 (recorder per pen). Sounds, blood samples and tonsil swabs were collected every month. Pig cough sounds were then classified from other sounds and a coughing index (CI) was established. Blood samples and tonsil swabs were utilized to determine respiratory diseases via laboratory tests that included ELISA, PCR and bacterial cultures. According to our results, pig coughs sound distinctly different from other sounds as had been classified by python. Moreover, the laboratory results of the seroprofile of Mycoplasma hyopneumoniae (M.hyo), Porcine Reproductive and Respiratory Syndrome virus (PRRSv), and Porcine Circovirus type 2 (PCV2), as was established by ELISA test, were employed in disease detection during the fattening period. Spearman rank correlations and Kappa analysis were used to establish correlation values between coughing and the results of laboratory tests. CI revealed a high correlation coefficient and agreement with the ELISA results of M.hyo, as well as the PCR results of PRRSv and PCV2 (p<0.05), while CI also revealed low correlation coefficient and agreement with the results of the Streptococcus spp. and Pasteurella spp. cultures (p>0.05). Therefore, the monitoring of coughing can be suited to detect respiratory problems and any potential relationships with M.hyo, PRRSv and PCV2 infections
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spelling doaj.art-80c6f8af30484243b27c593925a84af22023-07-12T03:06:54ZengFaculty of Veterinary Medicine, Chiang Mai UniversityVeterinary Integrative Sciences2629-99682023-02-0121229130810.12982/VIS.2023.023Classification and correlation of coughing sounds and disease status in fattening pigsPanuwat YamsakulTerdsak YanoKannika Na LampangManad KhamkongLertrak Srikitjakarn There have been attempts to use technology to distinguish pig coughs from other sounds on farms. Machine learning is being used to classify pig coughs via python. Sound files have been converted to images that are composed of wave plots,spectrograms and log power spectrograms for identification of those sounds. A recorder was used with a total of 45 healthy three-bred weaned piglets, wherein three replications of each were used with 15 weaning pigs per pen during different months. This process was set up within the housing unit at a ratio as 1:1 (recorder per pen). Sounds, blood samples and tonsil swabs were collected every month. Pig cough sounds were then classified from other sounds and a coughing index (CI) was established. Blood samples and tonsil swabs were utilized to determine respiratory diseases via laboratory tests that included ELISA, PCR and bacterial cultures. According to our results, pig coughs sound distinctly different from other sounds as had been classified by python. Moreover, the laboratory results of the seroprofile of Mycoplasma hyopneumoniae (M.hyo), Porcine Reproductive and Respiratory Syndrome virus (PRRSv), and Porcine Circovirus type 2 (PCV2), as was established by ELISA test, were employed in disease detection during the fattening period. Spearman rank correlations and Kappa analysis were used to establish correlation values between coughing and the results of laboratory tests. CI revealed a high correlation coefficient and agreement with the ELISA results of M.hyo, as well as the PCR results of PRRSv and PCV2 (p<0.05), while CI also revealed low correlation coefficient and agreement with the results of the Streptococcus spp. and Pasteurella spp. cultures (p>0.05). Therefore, the monitoring of coughing can be suited to detect respiratory problems and any potential relationships with M.hyo, PRRSv and PCV2 infectionshttps://he02.tci-thaijo.org/index.php/vis/article/view/260914
spellingShingle Panuwat Yamsakul
Terdsak Yano
Kannika Na Lampang
Manad Khamkong
Lertrak Srikitjakarn
Classification and correlation of coughing sounds and disease status in fattening pigs
Veterinary Integrative Sciences
title Classification and correlation of coughing sounds and disease status in fattening pigs
title_full Classification and correlation of coughing sounds and disease status in fattening pigs
title_fullStr Classification and correlation of coughing sounds and disease status in fattening pigs
title_full_unstemmed Classification and correlation of coughing sounds and disease status in fattening pigs
title_short Classification and correlation of coughing sounds and disease status in fattening pigs
title_sort classification and correlation of coughing sounds and disease status in fattening pigs
url https://he02.tci-thaijo.org/index.php/vis/article/view/260914
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AT kannikanalampang classificationandcorrelationofcoughingsoundsanddiseasestatusinfatteningpigs
AT manadkhamkong classificationandcorrelationofcoughingsoundsanddiseasestatusinfatteningpigs
AT lertraksrikitjakarn classificationandcorrelationofcoughingsoundsanddiseasestatusinfatteningpigs