General introduction to precision livestock farming
Open Access
- 1 January 2017
- journal article
- research article
- Published by Oxford University Press (OUP) in Animal Frontiers
- Vol. 7 (1), 6-11
- https://doi.org/10.2527/af.2017.0102
Abstract
Many people in several countries worldwide, particularly in Asia, India, and South America, are getting more financial possibilities to buy animal protein. This fact, combined with the changing diets of these people in those countries, will result in an increase of the worldwide demand for animal products (meat, eggs, and milk) of 70% by 2050. Consequently, the number of livestock is increasing, while at the same time, the number of farmers is decreasing. This results in much bigger herds per farmer. It has become impossible for farmers to follow all of their animals in a reliable way in such big groups. At the same time, several issues must be solved now in the livestock sector, such as monitoring animal health and welfare, reducing the environmental impact, and assuring the productivity of the process. Precision livestock farming (PLF) aims to offer a real-time monitoring and managing system for farmers. This is fundamentally different from other approaches that tried to monitor the animal welfare by human experts scoring animal-based indicators. These methods do not improve the life of the animal under consideration. It is nice to detect a problem after an animal has arrived at the slaughterhouse, but it is much better to detect a problem while the animal is being reared and to take immediate management action. The idea of PLF is to provide a real-time warning when something goes wrong so that immediate action can be taken by the farmer to solve the problem. To bring PLF technology further into field application, increased development and testing of PLF technologies is required in real farms to implement reliable solutions. To further develop and introduce such supporting management PLF systems, some basic principles must be respected. Copyright © 2017. . © 2017 BerckmansKeywords
This publication has 10 references indexed in Scilit:
- The Global One Health Paradigm: Challenges and Opportunities for Tackling Infectious Diseases at the Human, Animal, and Environment Interface in Low-Resource SettingsPLoS Neglected Tropical Diseases, 2014
- Development of an early warning system for a broiler house using computer visionBiosystems Engineering, 2013
- Cough sound description in relation to respiratory diseases in dairy calvesPreventive Veterinary Medicine, 2010
- Time-series analysis for online recognition and localization of sick pig (Sus scrofa) cough soundsThe Journal of the Acoustical Society of America, 2008
- Field test of algorithm for automatic cough detection in pig housesComputers and Electronics in Agriculture, 2008
- Individualized and time‐variant model for the functional link between thermoregulation and sleep onsetJournal of Sleep Research, 2006
- Assessing the sound of cough towards vocalityMedical Engineering & Physics, 2002
- Automated recognition of spontaneous versus voluntary coughMedical Engineering & Physics, 2002
- On-line cough recognizer systemThe Journal of the Acoustical Society of America, 1999
- Use of the receiver operating characteristic curve to evaluate sensitivity, specificity, and accuracy of methods for detection of peaks in hormone time seriesActa Endocrinologica, 1991