Sensitive Livestock and Information Communication Technology Applications to Prevent the Spread of Covid-19

Year 2023, , 104 - 107, 01.01.2023

Hatice Nur Kılıç , Mustafa Boğa , Demet Çanga

https://doi.org/10.47115/bsagriculture.1194817

Abstract

The epidemic disease called COVID-19 (SARS-CoV-2) has affected the whole world. With the spread of the epidemic, various measures such as distance education, home-office, and especially movement restrictions, have been tried to be taken. These measures have increased people's demand for healthy food. The formation of food safety awareness among in consumers has revealed the necessity of control of the controlling food chain (production, storage, transportation of products, etc.). In this process, animal products gained importance, especially as people paid more attention to their nutrition compared to previous years. Especially in this process, animal production should be systematically sustainable in order to meet the increasing animal protein needs of people. In this review, it aims to compile sensitive livestock systems in order to ensure the sustainability of animal production, the production of healthier animals and the production of the obtained products within the framework of food safety rules, with the cessation of mobility due to the measures taken under quarantine and social distance in the COVID-19 epidemic. Thus, in addition to reducing the human workforce during the epidemic process, the data collected with modern animal husbandry will prevent diseases, and facilitate the diagnosis and treatment processes in the event of a disease. With the use of information and communication technologies (ICT), which have an important place in this system, the data obtained through the modern livestock system can be easily processed, managed, and shared, thus reducing the possibility of disease transmission during the pandemic process.

Keywords

Covid-19, Animal production, Data, Artificial intelligence, Sensitive livestock, Information communication technologies

References

• Bewley J. 2008. Precision dairy farming: What is it and when does it pay. In Proceedings of the Kentucky Dairy Partners Meeting, April 15, Cave City, USA, pp. 14-18.
• Canga D, Boğa M, Kılıç HN, Bulut M. 2022. Information and communication technologies (ICT) and precision livestock (PLF) applications in farm conditions. Livre de Lyon, 1-39.
• Düzgün D, Or M. 2009.Application of thermal camera on the medicine and veterinary. Tubaw Sci J, 2(4): 468-475.
• Hoque M, Mondal S, Adusumilli S. 2022. Sustainable livestock production and food security. Biol Tools Technique, 71-90.
• Nunes L, Ampatzidisa Y, Costaa L Wallaub M. 2021. Horse foraging behavior detection using sound recognition techniques and artificial intelligence. Comput Electron Agric, 183:106080.
• Nääs IA. Carvalho VC. Moura DJ. Mollo M. 2006. Precision livestock production. Agric Eng Int CIGR J, 313-315.
• Tarhan S, Özgüven MM, Ertuğrul M. 2015.Applications of information technologies on dairy cattle enterprises. In Proceedings of the GAP VII. Agriculture Congress, 28 April-1 May 2015, Şanlıurfa, Türkiye, pp. 510-513.
• Tömek B. 2007.An evaluation of modern technology applications used by herd management in dairy cattle husbandrysüt. MSc thesis, Ege University, Graduate School of Natural and Applied Sciences, İzmir, Türkiye, ss. 58.
• Türker U, Akdemir B, Topakcı M, Tekin B, Aydın İÜA, Özoğul G, Evrenosoğlu M. 2015. Advances in precision farming technologies. In Proceedings of Agricultural Engineering VIII. Technical Congress, 16 February, Ankara, Türkiye, pp. 1: 295.
• Walter A, Finger R, Huber R, Buchmann N. 2017. Opinion: smart farming is key to developing sustainable agriculture. Proc Natl Acad Sci, 114: 6148–6150.
• Wolfert S, Ge L, Verdouw C, Bogaardt MJ. 2017. Big data in smart farming–a review. Agric Syst, 153: 69-80.
• Yaman H, Sungur O, Dulupçu MA. 2021. Transformation of agriculture and livestock in the world: technology-based applications and revolutions. TJAE, 27(2): 123-133.
• Yaylak E. 2008.Lameness in dairy cattle and its effects on some characters. J Anim Prod, 49:1.
• Yıldız AK, Özgüven MM. 2018. Precision animal production practices and applicability in Yozgat livestock. 3. International Bozok Symposium, May 3-5, Yozgat, Türkiye, pp. 59-72.