Review: Precision Livestock Farming technologies in pasture-based livestock systems

Aquilani, Chiara; Confessore, Andrea; Bozzi, Rıccardo; Sirtori, Francesco; Pugliese, Carolina

doi:10.1016/j.animal.2021.100429

Cited by 119 publications

(91 citation statements)

References 123 publications

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“…AgTech research is strong in Australia and Australian innovators producing world-leading digital technologies (Hudson and Wood 2017;Nolet 2018). Some of the leading examples are direct from the research sector, like CSIRO (virtual fencing, Cerestag) and the University of Sydney (Australian Centre for Field Robotics), with products and services that have subsequently been commercialised (Campbell et al 2021;Aquilani et al 2022). Other examples come from the corporate and farming sectors (e.g.…”

Section: The Role Of Australian Agtech In Implementing Digital Techno...mentioning

confidence: 99%

Current status of and future opportunities for digital agriculture in Australia

Hansen

Leonard

Mitchell

et al. 2022

Crop & Pasture Science

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In Australia, digital agriculture is considered immature and its adoption ad hoc, despite a relatively advanced technology innovation sector. In this review, we focus on the technical, governance and social factors of digital adoption that have created a disconnect between technology development and the end user community (farmers and their advisors). Using examples that reflect both successes and barriers in Australian agriculture, we first explore the current enabling technologies and processes, and then we highlight some of the key socio-technical factors that explain why digital agriculture is immature and ad hoc. Pronounced issues include fragmentation of the innovation system (and digital tools), and a lack of enabling legislation and policy to support technology deployment. To overcome such issues and increase adoption, clear value propositions for change are necessary. These value propositions are influenced by the perceptions and aspirations of individuals, the delivery of digitally-enabled processes and the supporting legislative, policy and educational structures, better use/conversion of data generated through technology applications to knowledge for supporting decision making, and the suitability of the technology. Agronomists and early adopter farmers will play a significant role in closing the technology-end user gap, and will need support and training from technology service providers, government bodies and peer-networks. Ultimately, practice change will only be achieved through mutual understanding, ownership and trust. This will occur when farmers and their advisors are an integral part of the entire digital innovation system.

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Section: The Role Of Australian Agtech In Implementing Digital Techno...mentioning

confidence: 99%

Current status of and future opportunities for digital agriculture in Australia

Hansen

Leonard

Mitchell

et al. 2022

Crop & Pasture Science

View full text Add to dashboard Cite

show abstract

“…The possibility of monitoring animals in remote locations without human interference would improve animal management related to predator attacks, health, and welfare issues, consequently resulting in significant labor reduction to monitor the herd ( Aquilani et al, 2022 ). Efforts have been made in developing sensors with different suitability for grazing animals, for instance: using jaw activity to monitor feeding behavior ( Navon et al, 2013 ), measuring heart rate and body temperature to determine predator attacks ( Sendra et al, 2013 ), emitting auditory or electrical stimuli for virtual fencing ( Marini et al, 2019 ; Aquilani et al, 2022 ), among others. Virtual fencing is one of the most interesting precision farming technologies for pasture-based goat farms as it replaces physical fences with virtual boundaries ( Vaintrub et al, 2021 ).…”

Section: Confined Precision Operationsmentioning

confidence: 99%

ASAS–NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production

Menendez

Brennan

Gaillard

et al. 2022

Journal of Animal Science

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Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative five-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSM). This five-step process acts as a guide to realize anticipated benefits from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confined and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals, while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in, more challenging and harsh, extensive systems it is likely that confined operations will benefit from required advances in precision technology and PSM, ultimately strengthening the benefits from precision technology to achieve short-and long-term goals.

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“…Different sensors are employed to develop these tasks such as GPS, cameras, accelerometers or thermographic devices [ 20 , 21 ]. Generally, these sensors are classified in two groups: sensors worn by animals such as ear tags, collars, leg straps or implants [ 5 ], and sensors placed in the animal’s surroundings as in the case of cameras.…”

Section: Related Workmentioning

confidence: 99%

Vision-Based Module for Herding with a Sheepdog Robot

Castillo

Sánchez-González

Campazas-Vega

et al. 2022

Sensors

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Livestock farming is assisted more and more by technological solutions, such as robots. One of the main problems for shepherds is the control and care of livestock in areas difficult to access where grazing animals are attacked by predators such as the Iberian wolf in the northwest of the Iberian Peninsula. In this paper, we propose a system to automatically generate benchmarks of animal images of different species from iNaturalist API, which is coupled with a vision-based module that allows us to automatically detect predators and distinguish them from other animals. We tested multiple existing object detection models to determine the best one in terms of efficiency and speed, as it is conceived for real-time environments. YOLOv5m achieves the best performance as it can process 64 FPS, achieving an mAP (with IoU of 50%) of 99.49% for a dataset where wolves (predator) or dogs (prey) have to be detected and distinguished. This result meets the requirements of pasture-based livestock farms.

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Review: Precision Livestock Farming technologies in pasture-based livestock systems

Cited by 119 publications

References 123 publications

Current status of and future opportunities for digital agriculture in Australia

Current status of and future opportunities for digital agriculture in Australia

ASAS–NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production

Vision-Based Module for Herding with a Sheepdog Robot

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