381 Smart Farming for Extensive Grazing Ruminant Production Systems

Autor: Igor Kardailsky, Warwick B Badgery, Paul L. Greenwood, G. J. Bishop-Hurley
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: J Anim Sci
Popis: Smart farming for extensive grazing systems includes applications linking environment and supply-chain, including metrics for climate, soils, pastures, animals and animal products to enhance management, optimization and predictions. Technological developments for remote monitoring in extensive systems have varied in their success and remain limited in uptake, and include: In-field, fixed-device monitoring of livestock numbers, water, photosynthesis and greenhouse gas emissions; body composition and physiology assessments using devices fixed to handling facilities; ground- or aerial-based livestock, water, pasture, invasive weeds and/or soil monitoring using photogrammetry or technologies including LiDAR; multi-channel, satellite-based spectrometry coupled with weather and soil grids to model and predict pasture biomass components; automated in-field liveweight measurement and drafting; virtual fencing; on- and in-animal devices to monitor location, activity, behaviors and physiology; GPS to monitor asset and personnel location. These technologies target productivity, efficiency, health and welfare of ruminants, including genetic improvement, and more efficient, sustainable resource use, including soils, pastures and water, to improve individual ruminants and grazing systems. We have developed and validated technologies for remote, in-field determination of animal behaviors, pasture characteristics including availability and disappearance mapping for calibration and validation of satellite images, and pasture intake under varying grazing conditions. Examples of our R&D include experimental on-animal sensor devices to classify and monitor behaviors in extensive systems, and development of a GrazingApp linking satellite imagery, weather and soil information to model and predict animal production. Development of these technologies has required analytical methods for big data, including machine learning and artificial intelligence. These and other applications that function in near to real-time are enhanced by management and aggregation of enormous amounts of data generated by sensors and other devices into useful metrics before transmission using wireless networks. These metrics are the basis for data-driven management decisions that reduce risk and enhance profit for grazing enterprises.
Databáze: OpenAIRE