DIGITAL TOOLS FOR INCREASING THE COMPETITIVENESS OF LIVESTOCK PRODUCTS

Keywords: competitiveness, livestock products, blockchain, Big Data, transparency

Abstract

The purpose of this article is to critically review the current state of digital livestock technology using Precision Livestock (PLF) technologies, including big data and blockchain technology. With PLF technologies, livestock has the potential to address the above pressing issues by becoming more transparent and building consumer confidence. However, new PLF technologies are still developing, and core component technologies (such as blockchain) are still in their infancy and not yet proven at scale. Next-generation PLF technologies require preemptive and predictive analytics platforms that can sort through vast amounts of data accurately and affordably by accounting for specific variables. Data privacy, security and integration issues need to be addressed before the deployment of shared PLF solutions across multiple agribusinesses (farms) becomes commercially feasible. Advanced digitization technologies can help modern farms optimize economic input per animal, reduce the burden of repetitive farming tasks and overcome less efficient individual solutions. There is now a strong cultural emphasis on reducing animal experimentation and physical contact with animals to improve animal welfare and avoid disease outbreaks. This trend may spur more research into the use of new biometric sensors, big data, and blockchain technology for the mutual benefit of livestock farmers, consumers, and farm animals themselves. Farmer autonomy and data-driven approaches to farming versus experience-based animal management practices are just some of the many hurdles digitalization must overcome before it can be widely adopted. In modern animal husbandry systems, animals are mostly kept indoors or in small enclosures. Rangeland production systems are declining as the demand for high profitability increases. However, pasture systems generally provide better hygiene than indoor systems, provide the animals with a softer surface than the concrete commonly used in buildings, and allow them to perform natural behaviors without severely restricting their movements. Such conditions have many positive consequences for animal welfare that meet the general expectations of consumers. In addition, grazing can be beneficial for biodiversity, soil conservation and carbon sequestration. It is good agricultural practice to regularly inspect the health and welfare of animals on pasture, which is also regulated by legislation in some countries.

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Jorquera-Chavez, M., Fuentes, S., Dunshea, F.R., Jongman, E.C., Warner, R.D. Computer vision and remote sensing to assess physiological responses of cattle to pre-slaughter stress, and its impact on beef quality: A review Meat. Sci., 156 (2019), pp. 11-22, 10.1016/j.meatsci.2019.05.007.

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Lin, J., Shen, Z., Zhang, A., Chai, Y. Blockchain and IoT based food traceability for smart agriculture Proceedings of the 3rd Int. Con. on Crowd Sci. and Eng (2018), pp. 1-6.

Morota, G., Ventura, R.V., Silva, F.F., Koyama, M., Fernando, S.C. Big data analytics and precision animal agriculture symposium: machine learning and data mining advance predictive big data analysis in precision animal agriculture.

Motta, G.A., Tekinerdogan, B., Athanasiadis, I.N. Blockchain Applications in the Agri-Food Domain: The First Wave Front. Blockchain., 3 (2020), p. 6.

Neethirajan, S. Recent advances in wearable sensors for animal health management Sens Biosensing Res., 12 (2017), pp. 15-29, 10.1016/j.sbsr.2016.11.004.

Ochs, D.S., Wolf, C.A., Widmar, N.J. Bir Consumer perceptions of egg-laying hen housing systems Poult. Sci., 97 (10) (2018), pp. 3390-3396, 10.3382/ps/pey205.

Piñeiro, C., Morales, J., Rodríguez, M., Aparicio, M., Manzanilla, E.G., Koketsu, Y. Big (pig) data and the internet of the swine things: a new paradigm in the industry Anim. Front., 9 (2) (2019), pp. 6-15.

Thornton, P.K. Livestock production: recent trends, future prospects Philos. Trans. R. Soc. B., 365 (1554) (2010), pp. 2853-2867, 10.1098/rstb.2010.0134.

UN (United Nations) Department of Economic and Social Affairs, Population Division, World population prospects. https://www.un.org/development/desa/publications/world-population-prospects-2019-highlights.html, 2019.

Wolfert, S., Ge, L., Verdouw, C., Bogaardt, M.J. Big data in smart farming–a review Agric. Syst., 153 (2017), pp. 69-80, 10.1016/j.agsy.2017.01.023.

Published
2022-12-27
How to Cite
Perehuda, Y. (2022). DIGITAL TOOLS FOR INCREASING THE COMPETITIVENESS OF LIVESTOCK PRODUCTS. Bulletin of Sumy National Agrarian University, (2 (92), 38-46. https://doi.org/10.32782/bsnau.2022.2.5