How do we feed grazing livestock in the future? A case for knowledge‐driven grazing systems

Autoren: Juliane Horn, Johannes Isselstein

GreenGrass   |   08.2022    peer reviewed
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Grassland degradation has been observed worldwide and is often a result of overexploitation or abandonment. Knowledge‐driven and precise grazing management is required to use grasslands' potential in a sustainable way. Information gaps lead to inefficiencies in grazing land management and ecosystem service provision. Rapid advances in automated sensors and information technologies for information acquisition on herbage availability, controlling animal grazing behaviour and setting up data‐driven decision support tools have the potential to improve grazing management. Sensors and IT‐based methods allow spatiotemporal dynamics in herbage mass and quality and sward structure and botanical composition to be obtained automatically. These monitoring methods enable a spatially and temporally precise adjustment of the forage allowance and stocking density. Virtual fencing (VF) is an innovative digital tool for fine‐tuned spatiotemporal control of grazing animals. VF enables farmers to adjust grazing flexibly and dynamically by moving the virtual borders on a mobile user interface and sending new coordinates to the GPS receiver unit on each animal's VF collar. VF promises high efficiency with no obvious negative impacts on animal welfare. The potential of VF is enormous, but its economic viability still needs to be verified and its acceptance by authorities and the public needs to be supported. A decision support system that optimizes grazing management and agronomic and ecological outcomes by integrating and analysing multiple data at high spatial and temporal resolution can provide sufficient knowledge and confidence in grazing management decisions. Integration of key technologies into a holistic concept can take grazing management to the next level.

Publikationsdatum: 08.2022

Verlag: Wiley

Quelle: Grass and Forage Science | 3 | 153-166 | 77

Publikationstyp: Journal-Artikel