A review on the use of sensors to monitor cattle jaw movements and behavior when grazing

作者：Andriamandroso Andriamasinoro Lalaina Herinaina^*; Bindelle Jerome; Mercatoris Benoit; Lebeau Frederic

来源：Biotechnologie Agronomie Societe et Environnement, 2016, 20: 273-286.

DOI：10.25518/1780-4507.13058

• Precision agriculture
• livestock management
• cattle
• sensors
• movements
• forage

Introduction. Precision Livestock Farming (PLF) is spreading rapidly in intensive cattle farms. It is based on the monitoring of individuals using different kinds of sensors. Applied to grazing animals, PLF is mainly based on the recording of three parameters: the location, the posture and the movements of the animal. Until now, several techniques have been used to discriminate grazing and ruminating behaviors with accuracies over 90% on average, when compared to observations, providing valuable tools to improve the management of pasture and grazing animals. However, bites and jaw movements are still overlooked, even though they are of utmost importance to assess the animal grazing strategies for various pasture types and develop future techniques allowing better estimation of their intake.
Literature. The goal of this review is to explore the possibility of monitoring the individual jaw movements and the differentiation of bites in grazing animals. For this purpose, (1) the mechanisms of forage intake in cattle are explained briefly in order to understand the movements performed by the cow, especially during grazing, (2) the various sensors that have been proposed to monitor jaw movements of ruminants such as mechanical sensors (pressure sensors), acoustic sensors (microphone) and electromyography sensors are compared and (3) finally the relationship between jaw movements, biting behavior and forage intake is discussed.
Conclusions. The review clearly demonstrated the abilities of mechanical, acoustic and electromyography sensors to classify the difference types of jaw movements. However, it also indicated a wide range of accuracies and different observation windows required to reach these accuracies when compared to the observed movement. This classification purpose could lead to a better detection of more specific behavior, e.g. bite detection, and their exact location on pasture.

• 出版日期2016