Abstract
Among the most straining trends that farmers have to face there are: on one side, to guarantee welfare and adequate life conditions for animals and to reduce the environmental footprint, on the other side, to develop new strategies to improve farm management reducing costs. The current conditions and the expected developments of the dairy sector highlight a strong need for more efficient and sustainable farming systems. Studying heat stress, herd management and housing and animals’ productive and reproductive performances is fundamental for the economic and environmental sustainability of the dairy chain. New and effective tools to cope with these challenges have been provided by Precision Livestock Farming (PLF), which is nowadays increasingly applied and makes possible to control quali-quantitative parameters related to production, health, behaviour, and real-time locomotion per animal. The research key challenge is to turn these data into knowledge to provide real-time support in farming optimisation. This research focuses specifically on different systems to collect, process and derive useful information from data on animal welfare and productivity. A multi-disciplinary approach has been adopted to generate a decision support system for farmers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arcidiacono, C., Porto, S. M. C., Mancino, M., & Cascone, G. (2017a). Development of a threshold-based classifier for real-time recognition of cow feeding and standing behavioural activities from accelerometer data. Computers and Electronics in Agriculture, 134, 124–134.
Arcidiacono, C., Porto, S. M. C., Mancino, M., & Cascone, G. (2017b). A software tool for the automatic and real-time analysis of cow velocity data in free-stall barns: The case study of oestrus detection from Ultra-Wide-Band data. Biosystems Engineering, 173, 157–165.
Bargo, F., Muller, L. D., Delahoy, J. E., & Cassidy, T. W. (2002). Performance of high producing dairy cows with three different feeding systems combining pasture and total mixed rations. Journal of Dairy Science, 85, 2948–2963.
Charlton, G. L., & Rutter, S. M. (2017). The behaviour of housed dairy cattle with and without pasture access: A review. Applied Animal Behaviour Science, 192, 2–9.
Gernand, E., König, S., & Kipp, C. (2019). Influence of on-farm measurements for heat stress indicators on dairy cow productivity, female fertility, and health. Journal of Dairy Science, 102, 6660–6671.
Legrand, A. L., von Keyserlingk, M. A. G., & Weary, D. M. (2009). Preference and usage of pasture versus free-stall housing by lactating dairy cattle. Journal of Dairy Science, 92, 3651–3658.
Mayo, L. M., Silvia, W. J., Ray, D. L., Jones, B. W., Stone, A. E., Tsai, I. C., et al. (2019). Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows. Journal of Dairy Science, 102, 2645–2656.
Porto, S. M. C., Arcidiacono, C., Anguzza, U., & Cascone, G. (2015). The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system. Biosystems Engineering, 133, 46–55.
Trnovszky, T., Kamencay, P., Orjesek, R., Benco, M., & Sykora, P. (2017). Animal recognition system based on convolutional neural network. Digital Image Processing and Computer Graphics, 15(3), 517–525.
Acknowledgements
The activity presented in the paper is part of the research grant Progetti di Ricerca di rilevante Interesse Nazionale—Bando 2017 Prot. 20178AN8NC.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Arcidiacono, C. et al. (2020). Smart Dairy Farming: Innovative Solutions to Improve Herd Productivity. In: Coppola, A., Di Renzo, G., Altieri, G., D'Antonio, P. (eds) Innovative Biosystems Engineering for Sustainable Agriculture, Forestry and Food Production. MID-TERM AIIA 2019. Lecture Notes in Civil Engineering, vol 67. Springer, Cham. https://doi.org/10.1007/978-3-030-39299-4_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-39299-4_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-39298-7
Online ISBN: 978-3-030-39299-4
eBook Packages: EngineeringEngineering (R0)