Literature DB >> 28994354

Monitoring and assessment of ingestive chewing sounds for prediction of herbage intake rate in grazing cattle.

J R Galli1, C A Cangiano2, M A Pece1, M J Larripa1, D H Milone3, S A Utsumi4, E A Laca5.   

Abstract

Accurate measurement of herbage intake rate is critical to advance knowledge of the ecology of grazing ruminants. This experiment tested the integration of behavioral and acoustic measurements of chewing and biting to estimate herbage dry matter intake (DMI) in dairy cows offered micro-swards of contrasting plant structure. Micro-swards constructed with plastic pots were offered to three lactating Holstein cows (608±24.9 kg of BW) in individual grazing sessions (n=48). Treatments were a factorial combination of two forage species (alfalfa and fescue) and two plant heights (tall=25±3.8 cm and short=12±1.9 cm) and were offered on a gradient of increasing herbage mass (10 to 30 pots) and number of bites (~10 to 40 bites). During each grazing session, sounds of biting and chewing were recorded with a wireless microphone placed on the cows' foreheads and a digital video camera to allow synchronized audio and video recordings. Dry matter intake rate was higher in tall alfalfa than in the other three treatments (32±1.6 v. 19±1.2 g/min). A high proportion of jaw movements in every grazing session (23 to 36%) were compound jaw movements (chew-bites) that appeared to be a key component of chewing and biting efficiency and of the ability of cows to regulate intake rate. Dry matter intake was accurately predicted based on easily observable behavioral and acoustic variables. Chewing sound energy measured as energy flux density (EFD) was linearly related to DMI, with 74% of EFD variation explained by DMI. Total chewing EFD, number of chew-bites and plant height (tall v. short) were the most important predictors of DMI. The best model explained 91% of the variation in DMI with a coefficient of variation of 17%. Ingestive sounds integrate valuable information to remotely monitor feeding behavior and predict DMI in grazing cows.

Entities:  

Keywords:  acoustic analysis; chew-bite; chewing; ingestive behavior; ruminants

Mesh:

Year:  2017        PMID: 28994354     DOI: 10.1017/S1751731117002415

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  5 in total

1.  Automated bioacoustics: methods in ecology and conservation and their potential for animal welfare monitoring.

Authors:  Michael P Mcloughlin; Rebecca Stewart; Alan G McElligott
Journal:  J R Soc Interface       Date:  2019-06-19       Impact factor: 4.118

Review 2.  Understanding intake on pastures: how, why, and a way forward.

Authors:  William B Smith; Michael L Galyean; Robert L Kallenbach; Paul L Greenwood; Eric J Scholljegerdes
Journal:  J Anim Sci       Date:  2021-06-01       Impact factor: 3.159

3.  Audio recordings dataset of grazing jaw movements in dairy cattle.

Authors:  Sebastián R Vanrell; José O Chelotti; Leandro A Bugnon; H Leonardo Rufiner; Diego H Milone; Emilio A Laca; Julio R Galli
Journal:  Data Brief       Date:  2020-04-30

4.  What, how, and how much do herbivores eat? The Continuous Bite Monitoring method for assessing forage intake of grazing animals.

Authors:  Anderson Michel Soares Bolzan; Leonardo S Szymczak; Laura Nadin; Olivier Jean F Bonnet; Marcelo O Wallau; Anibal de Moraes; Renata F Moraes; Alda L G Monteiro; Paulo C F Carvalho
Journal:  Ecol Evol       Date:  2021-06-25       Impact factor: 2.912

5.  Multi-dimensional Precision Livestock Farming: a potential toolbox for sustainable rangeland management.

Authors:  Agustina di Virgilio; Juan M Morales; Sergio A Lambertucci; Emily L C Shepard; Rory P Wilson
Journal:  PeerJ       Date:  2018-05-30       Impact factor: 2.984

  5 in total

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