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Decision-Making Strategies on Smart Dairy Farms: A Review

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh


Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Keywords: Big data, evolutionary computing, cloud, precision technologies

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[1] T. Garnett, M. C. Appleby, A. Balmford, I. J. Bateman, T. G. Benton, P. Bloomer, et al.,” Sustainable intensification in agriculture: Premises and policies”, Science, vol. 341, no.6141., pp. 33-34, Jul 2013.
[2] C. S. Cardoso, M. Jose Hotzel, D. M. Weary, J. A. Robbins, and M. A. G. von Keyserlingk,” Imagining the ideal dairy farm”, J. Dairy Sci., vol. 99, no.2., pp. 1663–1671, Jan 2016.
[3] A. Corallo, M. E. Latino, and M. Menegoli, “From Industry 4.0 to Agriculture 4.0: A Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability World Academy of Science, WASET, Int. J. of Nutrition and Food Engineering, vol. 12, no. 5., pp. 146–150, Apr 2018.
[4] B. R. McFadden and S. Stefanou, ‘Another Perspective on Understanding Food Democracy,’ Choices, vol. 31, no. 1, pp. 1–6, 2016.
[5] M. C. Ferris, A. Christensen, and S. R. Wangen, “Symposium review: Dairy Brain—Informing decisions on dairy farms using data analytics, J. Dairy Sci., vol. 103, no. 4., pp. 3874–3881, Apr 2020.
[6] S. Wolfert, L. Ge, C. Verdouw, and M. Bogaardt, “Big data in Smart Farming – A review”, Agricultural Systems., vol.153, pp. 69–80, May 2017.
[7] J. Wolfert, C. G. Sørensen, and D. Goense, “A Future Internet Collaboration Platform for Safe and Healthy Food from Farm to Fork”, Global Conference (SRII), 2014 Annual SRII. IEEE, San Jose, CA, USA, pp. 266–273.
[8] A. T. Balafoutis, B. Beck, S. Fountas, Z. Tsiropolous, J. Vangeyte, T. van der Wal, I. Soto et al., “Smart Farming Technologies – Description, Taxonomy and Economic Impact” In: Pedersen S., Lind K. (eds) Precision Agriculture: Technology and Economic Perspectives. Progress in Precision Agriculture. Springer, Cham, 2017.
[9] E. Kebreab, K. F. Reed, V. E. Cabrera, P. A. Vadas, G. Thoma, and J. M. Tricarico,” A new modeling environment for integrated dairy system management ”, Animal Frontiers, vol. 9, pp. 25-35, Dec 2019.
[10] D.G Mayer, “Evolutionary Algorithms and Agricultural Systems” Kluwer Academic Publishers: Dordrecht, 2001, ISBN 0792375750.
[11] A. De Mauro, M. Greco, and M. Grimaldi, ” A formal definition of big data based on its essential features”, Libr. Rev. vol. 65, no3., pp. 122 - 135, Apr 2016.
[12] N. O’ Mahony, S. Campbell, A. Carvalho, L. Krpalkova, D. Riordan, and J. Walsh, “3D Vision for Precision Dairy Farming”, IFAC-Papers OnLine, vol. 52, no. 30., pp. 312 – 317, 2019.
[13] M. Bohlouli, S.Alijani, S.Naderi, T.Yin, and S.König, “Prediction accuracies and genetic parameters for test-day traits from genomic and pedigree-based random regression models with or without heat stress interactions” J. Dairy Sci., vol. 102, no.1., pp. 488–502, Jan 2019.
[14] L. N. Grinter, M. R. Campler, and J. H. C. Costa, “Technical note: Validation of a behavior-monitoring collar’s precision and accuracy to measure rumination, feeding, and resting time of lactating dairy cows”, J. Dairy Sci., vol. 102, no. 4., pp. 3487–3494, Feb 2019.
[15] A. Carvalho, N. O’Mahony, L. Krpalkova, S. Campbell, J. Walsh and P. Doody, "Farming on the edge: Architectural Goals," 2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Istanbul, Turkey, 2019, pp. 1-6, doi: 10.1109/Agro-Geoinformatics.2019.8820424.
[16] M. A. Zamora-Izquierdoa , J. Santaa,∗ , J. A. Martınezb, V. Martınezc , A. F. Skarmetaa, “Smart farming IoT platform based on edge and cloud computing”, Biosystems Engineering, vol. 177, pp. 4-17, Jan 2019.
[17] V. E. Cabrera, J. A.Barrientos-Blanco, H. Delgado, and L. Fadul-Pacheco, “Symposium review: Real-time continuous decision making using big data on dairy farms” , J. Dairy Sci., vol. 103, no. 4., pp. 3856-3866, Apr 2020.
[18] K. Græsbøll, C. Kirkeby, S. S. Nielsen, T. Halasa, N. Toft, and L. E. Christiansen, “ Models to Estimate Lactation Curves of Milk Yield and Somatic Cell Count in Dairy Cows at the Herd Level for the Use in Simulations and Predictive Models”, Frontiers in Vet. Sci., vol.3, pp. 115, Dec 2016.
[19] S.B. Mat Sah, V. Ciesielski, D. D’Souza, M. Berry, ”Comparison between Genetic Algorithm and Genetic Programming Performance for Photomosaic Generation” In: Li X. et al. (eds) Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg
[20] J. S. Vuppalapati, S. Kedari, A. Ilapakurthy, A. Ilapakurti, and C. Vuppalapati, "Smart Dairies — Enablement of Smart City at Gross Root Level," 2017 IEEE Third International Conference on big data Computing Service and Applications (BigDataService), San Francisco, CA, pp. 118-123, 2017.
[21] J. Koltes, J. B. Cole, R. Clemmens, R. N. Dilger, L. M. Kramer, and J. K. Lunney, “A Vision for Development and Utilization of High-Throughput Phenotyping and big data Analytics in Livestock” Front Genet., vol. 10, pp. 1-14, Dec 2019.
[22] C. Kulatunga, L. Shalloo, W. Donnelly, E. Robson, and S. Ivanov, "Opportunistic Wireless Networking for smart dairy farming," in IT Professional, vol. 19, no. 2, pp. 16-23, Mar-Apr 2017.
[23] R. Chudasama, S. Dobariya, K. Patel, and H. Lopes, "DAPS: Dairy analysis and prediction system using technical indicators," 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS), Chennai, 2017, pp. 176-180.
[24] C. Hudson, J. Kaler, and P. Down, “Using big data in cattle practice,” In Practice, vol. 40, no. 9., pp. 396 - 408, Oct 2018.
[25] R. S. Alonsoa, I. Sittón-Candanedoa, Ó. Garcíaa, J. Prietoab, and S. Rodríguez-Gonzáleza, “An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario” Ad Hoc Net., vol. 98, Mar 2020.
[26] E. Mieras, A. Gaasbeek, and D. Kan, “How to Seize the Opportunities of New Technologies in Life Cycle Analysis Data Collection: A Case Study of the Dutch Dairy Farming Sector” Challenges, vol. 10, no. 1., pp. 8, Jun 2019.
[27] W. J. Yan, X. Chen, O. Akcan, J. Lim, and D. Yang, "Big data analytics for empowering milk yield prediction in dairy supply chains," 2015 IEEE International Conference on big data (big data), Santa Clara, CA, pp. 2132-2137, 2015.
[28] J. Horvath, B. Banhelyi, T. Csendes, and E. Miko,” Professional and economic reasons for adoption of precision dairy farming” Lucrari Stiintifice Seria I, Management Agricol. vol. 21, no. 2., pp. 39-43, 2019.
[29] E. A. Eckelkamp and J. M. Bewley, “On-farm use of disease alerts generated by precision dairy technology”, J. Dairy Sci., vol. 103, no. 2., pp. 1566-1582, Feb 2020.
[30] L. M. Mayo, W. J. Silvia, D. L. Ray, B. W. Jones, A. E. Stone, I. C. Tsai, J. D. Clark, J. M. Bewley, and G. Heersche, “Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows”, J. Dairy Sci., vol. 102, no. 3., pp. 2645-2656, Feb 2020.
[31] M. C. Cantor, C. H. Pertuisel, and J. H. C. Costa, “Technical note: Estimating body weight of dairy calves with a partial-weight scale attached to an automated milk feeder2”, J. Dairy Sci., vol. 103, no. 2., pp. 1914-1919, Feb 2020.
[32] S. F. Wamba and A. Wicks, "RFID deployment and use in the dairy value chain: Applications, current issues and future research directions," 2010 IEEE International Symposium on Technology and Society, Wollongong, NSW, 2010, pp. 172-179.
[33] S. Sonka, “big data and the Ag Sector: More than Lots of Numbers”, Int. Food & Agri. Management Rev., vol. 17, no. 1., pp. 1-19, 2014.
[34] J. B. Cole, S. Newman, F. Foertter, I. Aguilar, and M. Coffey, “Breeding and Genetics Symposium: really big data: processing and analysis of very large data sets”, J. Anim. Sci., vol. 90, no. 3., pp 723–733, Mar 2012.
[35] J. Werner, C. Umstatter, L. Leso, E. Kennedy, A. Geoghegan, and L. Shalloo, M. Schick, B. O'Brien, “Evaluation and application potential of an accelerometer-based collar device for measuring grazing behavior of dairy cows,” Animal, vol. 13, no. 9., pp. 2070–2079, Feb 2019.
[36] L. Krpalkova, A. Murphy, L. Zavadilova, N. O’ Mahony, A. Carvalho, S. Campbell, and J. Walsh, “Detection, prevention and impact of lameness in dairy cattle management”, Int. J. of Advances in Sci. Eng. and Tech., vol. 8, no. 1., pp. 2321 –9009, Jan 2020.
[37] M. O. Akbar, M. S. Shahbaz khan, M. J. Ali, A. Hussain, G. Qaiser, Maruf Pasha, U. Pasha, M. Saad Missen, N. Akhtar, “IoT for Development of Smart Dairy Farming”, J. of Food Quality, vol. 2020, pp. 1-8, Mar 2020.
[38] C. Lokhorst, R. M. de Mol, C. Kamphuis, “Invited review: Big Data in precision dairy farming”, Animal, vol. 13, no. 7, pp. 1519-1528, 2019 Jul.
[39] M. Taneja, N. Jalodia, J. Byabazaire, A. Davy, C. Olariu, “SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy farming”, Softw Pract Exp, vol. 49, no. 7, pp. 1055-1078, Jul 2019.
[40] L. Krpálková, N. O' Mahony, A. Carvalho, S. Campbell, J. Walsh, “Evaluating the economic profit of reproductive performance through the integration of a dynamic programming model on a specific dairy farm”, Czech J. of Animal Science, vol. 65, pp. 124-134, Apr 2020.