Abstract

Vocal expression of emotions has been observed across species and could provide a non-invasive and reliable means to assess animal emotions. We investigated if pig vocal indicators of emotions revealed in previous studies are valid across call types and contexts, and could potentially be used to develop an automated emotion monitoring tool. We performed an analysis of an extensive and unique dataset of low (LF) and high frequency (HF) calls emitted by pigs across numerous commercial contexts from birth to slaughter (7414 calls from 411 pigs). Our results revealed that the valence attributed to the contexts of production (positive versus negative) affected all investigated parameters in both LF and HF. Similarly, the context category affected all parameters. We then tested two different automated methods for call classification; a neural network revealed much higher classification accuracy compared to a permuted discriminant function analysis (pDFA), both for the valence (neural network: 91.5%; pDFA analysis weighted average across LF and HF (cross-classified): 61.7% with a chance level at 50.5%) and context (neural network: 81.5%; pDFA analysis weighted average across LF and HF (cross-classified): 19.4% with a chance level at 14.3%). These results suggest that an automated recognition system can be developed to monitor pig welfare on-farm.

Details

Title
Classification of pig calls produced from birth to slaughter according to their emotional valence and context of production
Author
Briefer, Elodie F. 1 ; Sypherd, Ciara C.-R. 2 ; Linhart, Pavel 3 ; Leliveld, Lisette M. C. 4 ; Padilla de la Torre, Monica 5 ; Read, Eva R. 6 ; Guérin, Carole 6 ; Deiss, Véronique 7 ; Monestier, Chloé 8 ; Rasmussen, Jeppe H. 9 ; Špinka, Marek 10 ; Düpjan, Sandra 11 ; Boissy, Alain 12 ; Janczak, Andrew M. 5 ; Hillmann, Edna 13 ; Tallet, Céline 6 

 ETH Zurich, Institute of Agricultural Sciences, Zürich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780); University of Copenhagen, Behavioural Ecology Group, Section for Ecology and Evolution, Department of Biology, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X) 
 University of Copenhagen, Behavioural Ecology Group, Section for Ecology and Evolution, Department of Biology, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X); Harvard University, School of Engineering and Applied Sciences, Cambridge, USA (GRID:grid.38142.3c) (ISNI:0000 0004 1936 754X) 
 Institute of Animal Science, Department of Ethology, Prague, Czechia (GRID:grid.419125.a) (ISNI:0000 0001 1092 3026); University of South Bohemia, Department of Zoology, Faculty of Science, Č. Budějovice, Czechia (GRID:grid.14509.39) (ISNI:0000 0001 2166 4904) 
 Research Institute for Farm Animal Biology (FBN), Institute of Behavioural Physiology, Dummerstorf, Germany (GRID:grid.418188.c) (ISNI:0000 0000 9049 5051); Università Degli Studi Di Milano, Department of Agricultural and Environmental Sciences, Milano, Italy (GRID:grid.4708.b) (ISNI:0000 0004 1757 2822) 
 Norwegian University of Life Sciences, Faculty of Veterinary Medicine, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X) 
 Institut Agro, PEGASE, INRAE, Saint Gilles, France (GRID:grid.463756.5) (ISNI:0000 0004 0497 3491) 
 University of Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, Saint-Genès Champanelle, France (GRID:grid.463756.5) 
 Bureau ETRE, Bravant, France (GRID:grid.463756.5) 
 Research Institute for Farm Animal Biology (FBN), Institute of Behavioural Physiology, Dummerstorf, Germany (GRID:grid.418188.c) (ISNI:0000 0000 9049 5051); University of Agder, Center for Coastal Research, Kristiansand, Norway (GRID:grid.23048.3d) (ISNI:0000 0004 0417 6230); University of Agder, Center for Artificial Intelligence Research, Kristiansand, Norway (GRID:grid.23048.3d) (ISNI:0000 0004 0417 6230) 
10  Institute of Animal Science, Department of Ethology, Prague, Czechia (GRID:grid.419125.a) (ISNI:0000 0001 1092 3026); Czech University of Life Sciences, Faculty of Agrobiology, Food and Natural Resources, Prague, Czechia (GRID:grid.15866.3c) (ISNI:0000 0001 2238 631X) 
11  Research Institute for Farm Animal Biology (FBN), Institute of Behavioural Physiology, Dummerstorf, Germany (GRID:grid.418188.c) (ISNI:0000 0000 9049 5051) 
12  University of Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, Saint-Genès Champanelle, France (GRID:grid.418188.c) 
13  ETH Zurich, Institute of Agricultural Sciences, Zürich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780); Humboldt-Universität Zu Berlin, Animal Husbandry and Ethology, Albrecht Daniel Thaer-Institut, Faculty of Life Sciences, Berlin, Germany (GRID:grid.7468.d) (ISNI:0000 0001 2248 7639) 
Pages
3409
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2884935005
Copyright
© The Author(s) 2022. corrected publication 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.