Keyword : Precision breeding

IoT and ML approach for ornamental fish behaviour analysis

K. Suresh Kumar Patro, Vinod Kumar Yadav, Vidya S. Bharti, Arun Sharma, Arpita Sharma, T. Senthilkumar

Published in 2023

Article using machine and deep learning techniques to analyze changes in goldfish behavior following changes in environmental parameters (water temperature and dissolved oxygen).

Document Types: Scientific paper

Animal categories: Fish

Keywords:Animal adaptation to environment, Animal-based measurement, Precision farming, Enrichment, Living environment, Stress

Go to document

Editorial: Holistic prevention strategies for tail biting in pigs; from farm to slaughterhouse

Richard B. D'Eath, Keelin O'Driscoll, Emma Fàbrega

Published in 2023

Editorial summarizing the articles in a dossier on the prevention of tail biting in pigs. Topics include the identification of different types of tail biting, reducing  particular risk factors, the  settings that encourage biting, and the use of precision tools to spot the onset of biting episodes.

Document Types: Scientific paper

Animal categories: Porcines

Keywords:Aggression, Aggressivity, Pain, Precision breeding, Enrichment, Welfare indicators, Housing, Societal issues, Stress

Go to document

Measuring dairy cow welfare with real-time sensor-based data and farm records: a concept study

A.H. Stygar, L. Frondelius, G.V. Berteselli, Y. Gómez, E. Canali, J.K. Niemi, P. Llonch, M. Pastel

Published in 2023

Scientific article presenting an algorithm designed to assess the welfare of dairy cows based on sensor data (accelerometer and/or lactometer) and farm records. It concludes that the algorithm alone cannot not provide a sufficiently sensitive and specific assessment of cow welfare, but that there is merit in combining it with farm-based welfare measurement visits.

Document Types: Scientific paper

Animal categories: Bovines

Keywords: Animal-based measurements, Precision farming, Welfare indicators

Go to document

Animal board invited review: Quantification of resilience in farm animals

M. Taghipoor, M. Pastell, O. Martin, H. Nguyen Ba, J. van Milgen, A. Doeschl-Wilson, C. Loncke, N.C. Friggens, L. Puillet, R. Muñoz-Tamayo

Published in 2023

Scientific article on the detection and quantification of the responses of farm animals to changes in their environment as a means to classify them individually according to their level of resilience. To this purpose, the authors analyze the use of different modeling approaches to data generation from high-throughput recordings.

Document Types: Scientific paper

Category of animals: Bovines, Caprines, Ovines, Porcines

Keywords:Animal-based measurement, Precision farming, Welfare indicators, Modelling, Resilience, Stress

Go to document

Deciphering Avian Emotions: A Novel AI and Machine Learning Approach to Understanding Chicken Vocalizations

Adrian Cheok, Jun Cai, Ying Yan

Published in 2023

Scientific paper on the development of a system based on artificial intelligence and machine learning to identify different emotional states in chickens on the basis of their vocalizations, including hunger, fear, anger, contentment, excitement and distress, with a view to improving human-animal relationships.

Document Types: Scientific paper

Animal categories: Poultry

Keywords:Animal-based measurement, Precision farming, Welfare indicators, Human-animal relationship, Stress, Vocalizations

Go to document

Farmers' Perspectives of the Benefits and Risks in Precision Livestock Farming in the EU Pig and Poultry Sectors

Idan Kopler, Uri Marchaim, Ildikó E. Tikász, Sebastian Opaliński, Eugen Kokin, Kevin Mallinger, Thomas Neubauer, Stefan Gunnarsson, Claus Soerensen, Clive J. C. Phillips, Thomas Banhazi

Published in 2023

Scientific review of the acceptability to farmers of operational principles and technological solutions designed improve both animal and human welfare in the pork and poultry industries.

Document Types: Scientific review

Animal categories: Porcines, Poultry

Keywords:Animal-based measurement, Precision breeding, Welfare indicators, One Welfare

Go to document

Recognition of aggressive behavior of group-housed pigs based on CNN-GRU hybrid model with spatio-temporal attention mechanism

Yue Gao, Kai Yan, Baisheng Dai, Hongmin Sun, Yanling Yin, Runze Liu, Weizheng Shen

Published in 2023

Scientific article proposing a model for automatic video recognition of aggressive behavior in group-housed pigs, with an accuracy rate of 94.8%.

Document Types: Scientific paper

Animal categories:Pigs, Primates

Keywords:Aggression, Aggressiveness, Animal-based measurement, Precision breeding, Welfare indicators, Personality, Stress

Go to document

A two-stage recognition method based on deep learning for sheep behavior

Zishuo Gu, Haoyu Zhang, Zhiqiang He, Kai Niu

Published in 2023

Scientific article on a method to detect sheep behavior based on deep learning. It recognizes six types of sheep behavior, three corresponding to normal physiological activities (standing, feeding and lying down) and three behaviors considered to be disruptive (attacking, biting and climbing) that require immediate action from the farmer.

Document Types: Scientific paper

Animal categories: Ovines

Keywords:Animal-based measurement, Precision farming, Welfare indicator, Human-animal relationship

Go to document

Deviation of behavioural and productive parameters in dairy cows due to a lameness event: a synthesis of reviews

Luisa Magrin, Barbara Contiero, Giulio Cozzi, Flaviana Gottardo, Severino Segato

Published in 2023

Systematic literature review identifying the behavioral and yield parameters of cows that are the best indicators of lameness and calculating the changes in them during lameness episodes. They include time taken to feed, number of lying periods, time taken to lie down, time spent lying down,  and milk production. The values of all these parameters are significantly altered in the event of lameness, and could be used to detect lameness automatically.

Document Types: Scientific review

Animal categories: Bovines

Keywords: Animal-based measurements, Pain, Precision farming, Welfare indicators

Go to document

Analysis of Various Facial Expressions of Horses as a Welfare Indicator Using Deep Learning

Su Min Kim, Gil Jae Cho

Published in 2023

Article using deep learning to identify various facial expressions that can be used as indicators of welfare in horses. It proposes a model for the automatic recognition of facial expressions including the eyes, nose and ears, to identify horses in various situations: at rest, in pain, immediately after exercise and during shoeing.

Document Types: Scientific paper

Animal categories: Equines

Keywords:Animal-based measurements, Castration, Pain, Precision breeding, Welfare indicators, Sterilization

Go to document