Bioacoustics features as a tool for early diagnosis of pneumonia in riverine buffalo (Bubalus bubalis) calves

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Indu Devi Kuldeep Dudi Yajuvendra Singh Surender Singh Lathwal


The present study was conducted to identify specific acoustic features which could be used as possible indicators for early diagnosis of pneumonia in buffalo calves. In pneumonia, change in elasticity and resonance of vocal sound producing organs occur which eventually affects the vocal signature of calves. Twenty Murrah buffalo calves’ voice was recorded during both healthy and pneumonia infected stage where pneumonia was confirmed by lung X-RAY radiography. From the recorded vocal sound, acoustic features viz. call duration (sec.), call interval (sec.), frequency (Hz), bandwidth (Hz) and peak amplitude (P) with their sub variants were extracted with the help of PRAAT 3.2.36 software. Out of these, call duration (sec.) (0.879± 0.29 v/s 0.689± 0.24), call interval (sec.) (0.288±0.059 v/s 0.107±0.047) and peak amplitude (P) (start (0.750 ± 0.118 v/s 0.435 ± 0.113), end (0.102 ± 0.045 v/s 0.508 ± 0.268) and maximum (0.938 ± 0.210 v/s 0.684 ± 0.480)) were found significantly (p<0.05) different between two groups. Rest acoustic features did not differ statistically between two groups. This study indicates that it is possible to discriminate pneumonia voice from normal/healthy voice by acoustic analysis and farmers can acquire an early warning of pneumonia infections in calves through this non-invasive method.

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DEVI, Indu et al. Bioacoustics features as a tool for early diagnosis of pneumonia in riverine buffalo (Bubalus bubalis) calves. Buffalo Bulletin, [S.l.], v. 40, n. 3, p. 399-407, sep. 2021. ISSN 2539-5696. Available at: <>. Date accessed: 21 oct. 2021.
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Aerts, J.M.P., D. Jans, Halloy and D. Berckmans. 2005. Labelling of cough data from pigs for on-line disease monitoring by sound analysis. Trans. ASAE., 48(1): 351-354. DOI: 10.13031/2013.17948

Andrews, A.H. 2000. Calf pneumonia costs. Cattle Practice., 8: 109-114.

Berckmans, D. 2006. Automatic on-line monitoring of animals by precision livestock farming. Catholic University Leuven, Laboratory for Agricultural Buildings Research, 30, B-3001, Leuven, Belgium.

Boersma, P., D, Weenink. 2010. PRAAT: doing phonetics by computer. University of Amsterdam: Phonetic Sciences, Spuistraat, 210. Netherland.

Bureau of Indian Standards. 2005. Indian standard recommendations for loose housing system for animals. BIS, 12237.

Exadaktylos, V., M., Silva, J.M. Aerts, C.J. Taylor and D. Berckmans. 2008a. Real-time recognition of sick pig cough sounds. Compt. Electron. Agr., 63(2): 207-214. DOI: 10.1016/j.compag.2008.02.010

Exadaktylos, V., M. Silva, S. Ferrari, M. Guarino, J.M. Aerts and D. Berckmans. 2008b. Time-series analysis for online recognition and localization of sick pig (Sus scrofa) cough sounds. J. Acoust. Soc. Am., 124(6): 3803-3809. DOI: 10.1121/1.2998780

Ferrari, S., R. Piccinini, M. Silva, V. Exadaktylos, D. Berkmans and M. Guarino. 2010. Cough sound description in relation to respiratory diseases in dairy calves. Prev. Vet. Med., 96(3-4): 276-280. DOI: 10.1016/j.prevetmed.2010.06.013

Ferrari, S., M. Silva, M. Guarino and D. Berckmans. 2008b. Cough analysis of cough sounds for diagnosis of respiratory infections in intensive pig farming. Trans. ASAE., 5: 1051-1055.

Ferrari, S., M. Silva, M. Guarino, J.M. Aerts and D. Berckmans. 2008a. Cough sound analysis to identify respiratory infection in pigs. Comput. Electron. Agr., 64(2): 318-325. DOI: 10.1016/j.compag.2008.07.003

Gerhard, D. 2003. Pitch Extraction and Fundamental Frequency: History and Current Techniques. Technical report TR-CS 2003-2006. University of Regina, Department of Computer Science. Canada.

Guarino, M., A. Costa, A. Van Hirtum, P. Jans, K. Ghesquiere, J.M. Aerts and D. Berckmans. 2004. Field tests of an algorithm to predict infected pig coughing. Ann. Anim. Sci., 1: 61-65.

Harvey, W.B. 1987. Users Guide for LSMLMW, mixed model least squares and maximum likelihood computer programme. PC-I Version, Mimeograph, Ohiostate University, Ohio, USA.

Jans, P., M. Guarino, A. Costa, J.M. Aerts and D. Berckmans. 2004. Field test of algorithm for cough detection in pig houses. Comput. Electron. Agr., 62(1): 22-28. DOI: 10.1016/j.compag.2007.08.016

Korpas, J., J. Sadlonva, D. Salat and E. Masarova. 1987. The origin of cough sounds. Bull. Eur. Physiopathol. Respir., 23(Suppl. 10): 47-50.

Korpas, J., J.G. Widdicombe and M. Vrabec. 1993. Influence of simulated mucus cough sounds in cats. Respir. Med., 87(1): 49-54. DOI: 10.1016/S0954-6111(05)80313-0

Moldoveanu, B., P. Otmishi, P. Jani, J. Walker, X. Sarmiento, J. Guardiola, M. Saad and Y. Jerry. 2009. Inflammatory mechanisms in the lung. J. Inflamm. Res., 2: 1-11.

NRC. 2001. Nutrient Requirements of Dairy Animals, 7th ed. National Research Council, 373: National Academy Press, Washington, DC, USA.

Peek, S.F. 2005. Respiratory emergencies in cattle. Veterinary Clinics of North America: Food Animal Practice., 21(3): 697-710. DOI: 10.1016/j.cvfa.2005.07.001

Reece, C.A., A.C. Cherry, A.T. Reece, T.B. Hatcher and A.M. Diehl. 1966. Tape recorder for evaluation of cough in children. Am. J. Dis. Child., 112(2): 124-128. DOI: 10.1001/archpedi.1966.02090110068005

Robertson, J.F. and J. Benzie. 1989. Assessment of a cough counter for pigs. Farm Build. Prog. 95: 25-28.

Russell, B.A., F.J. Cerny and E.T. Stathopoulos. 1998. Effects of varied vocal intensity on ventilation and energy expenditure in women and men. J. Speech Lang. Hear. Res., 41(2): 239-248. DOI: 10.1044/jslhr.4102.239

Sethi, R.K. 2003. Improving riverine and swamp buffaloes through breeding, p. 51-60. Proceedings of fourth Asian Buffalo Congress, New Delhi, India.

Sreedhar, S., M. Ranganadham and E. Madan Mohan. 2010. Calf mortality in indigenous buffaloes. Indian Vet. J., 87: 197-198.

Subburaj, S., L. Parvez and T.G. Rajagopalan. 1966. Methods of recording and analysing cough sounds. Pulm. Pharmacol., 9(5-6): 269-279. DOI: 10.1006/pulp.1996.0035

Taylor, A.M. and D. Reby. 2010. The contribution of source filter theory to mammal vocal communication research. J. Zool., 280(3): 221-236. DOI: 10.1111/j.1469-7998.2009.00661.x

Van Hirtum, A. and D. Berckmans. 2002b. Automated recognition of spontaneous versus voluntary cough. Med. Eng. Phys., 24(7-8): 541-545. DOI: 10.1016/s1350-4533(02)00056-5

Van Hirtum, A. and D. Berckmans. 2003a. Considering the influence of artificial environmental noise to study cough time-frequency features. J. Sound Vib., 266(3): 667-675. DOI: 10.1016/S0022-460X(03)00592-3

Van Hirtum, A. and D. Berckmans. 2003b. Fuzzy approach for improved recognition of citric acid induced piglet coughing from continuous registration. J. Sound Vib., 266(3): 677-686. DOI: 10.1016/S0022-460X(03)00593-5

Wang, X., Y. Zhang, L.Y. Zhao, G.L. Riskowski. 2000. Effect of ventilation rate on dust spatial distribution in a mechanically ventilated airspace. Trans. ASAE., 43(6): 1877-1884. DOI: 10.13031/2013.3092

Wudu, T., B. Kelay, H.M. Mekonnen and K. Tesfu. 2008. Calf morbidity and mortality in smallholder dairy farms in Ada’aLiben District of Oromia, Ethiopia. Trop. Anim. Health Pro., 40(5): 369-376. DOI: 10.1007/s11250-007-9104-3

Wymann, M.N., B. Bonfoh, E. Schelling, S. Bengaly, S. Tembely and M. Tanner. 2006. Calf mortality rate and causes of death under different herd management systems in peri-urban Bamako, Mali. Livest. Sci., 100(2-3): 169-178. DOI: 10.1016/j.livprodsci.2005.08.010

Zaman, T., A. Khan and M.Z. Akhtar. 2006. Some of the risk factors of Nili-Ravi buffalo (Bubalus bubalis) neonatal Calf mortality in Pakistan. Pak. Vet. J., 26: 121-125.