DIGITAL AGRICULTURE PRACTICES IN THE CONTEXT OF AGRICULTURE 4.0

Yıl 2017, Cilt: 4 Sayı: 2, 186 - 193, 30.06.2017

Burak Ozdogan Anil Gacar Huseyin Aktas

https://doi.org/10.17261/Pressacademia.2017.448

Öz

Purpose- Agricultural production is under heavy pressure based upon increasing
world population and significant changes in the climate. In this study, the
concept of digital agriculture practices and their effects on agricultural
productivity is discussed. An evaluation of current circumstance is made
through the cases of Doktar Inc. and Tarla.io which are digital agriculture
companies located in Turkey.

Methodology- This study has utilized case method to evaluate the current circumstance
of digital agriculture applications in Turkey. Since digital agriculture is an
area that is still in early development stage in Turkey, case method is one of
the most suitable methods. 11 open-ended questions and subsequent interviews
sent to Doktor Inc and Tarla.io General Managers via e-mail and answers are
evaluated with other collected data.

Findings- Digital agriculture applications are in the early development stage in
Turkey. The companies that are discussed in the paper have made meaningful
progress regarding raising awareness of farmers and other involved parts of
agriculture sector in Turkey. While the penetration of the two companies is
currently not enough both as volume and quantity, the applications used for
digital agriculture by them are parallel with the applications in developed
countries.

Conclusion- Digital
agriculture practices in Turkey have yet to be implemented in very limited, but
there are steps to be taken to acceleration. To develop digital farming in
Turkey, supports of government have strategic priorities. In this context, the
development of a digital agriculture action plan and supporting of this
strategy with related policies and implementations, like in the EU countries and
USA, will enable the expansion of agricultural production vision in Turkey.
Technopolis and incubation centers of universities will be able to transform
the accumulated scientific knowledge into initiatives and create a digital
agriculture-focused ecosystem.

Anahtar Kelimeler

Digital agriculture, big data, innovation, IoT, cloud computing

Kaynakça

• Andrade-Sanchez, P., & Heun, J. T. (2010), Understanding Technical Terms and Acronyms Used in Precision Agriculture, The University of Arizona, Arizona Cooperative Extension Bulletin AZ1534.
• Ault, A., Krogmeier, J., & Buckmaster, D. (2013, July), Mobile, Cloud-Based Farm Management: A Case Study with Trello on My Farm, In 2013 ASABE Annual International Meeting, https://elibrary.asabe.org/abstract.asp?aid=43733&t=2&redir=&redirType=, Accessed: 11.02.2017.
• Avşar, D. & Avşar, G. (2014), Yeni Tarım Düzeninin Tarımsal Üretim Üzerindeki Etkileri ve Türkiye’deki Uygulamalar, Akademik Platform, 379-385.
• Balamurugan S., Divyabharathi, N., Jayashruthi, K., Bowiya, M., Shermy, R. P. &Shanker, R., (2016), Internet of Agriculture: Applying IoT to Improve Food and Farming Technology, International Research Journal of Engineering and Technology (IRJET), 3(10), 713-719.
• Byerlee, D., de Janvry, A. ve Sadoulet, E. (2009), Agriculture for Development: Toward a New Paradigm, Annual Review of Resource Economics, 1, 15-31.
• Chavali, L. N. (2014), Cloud Computing in Agriculture. In Agricultural Bioinformatics, 189-213, Springer India.
• Deichmann, U., Goyal, A., & Mishra, D. (2016), Will Digital Technologies Transform Agriculture in Developing Countries?, Agricultural Economics, 47(S1), 21-33.
• Devlin, B. (2013), Business UnIntelligence: Insight and Innovation Beyond Analytics and Big Data, Technics Publications, New Jersey, p.151.
• Doğan, Z., Arslan, S. ve Berkman, A.N. (2015), Türkiye’de Tarım Sektörünün İktisadi Gelişimi ve Sorunları: Tarihsel Bir Bakış, Niğde Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Ocak, 8(1). 29-4.
• Dong, X., Vuran, M. C., & Irmak, S. (2013), Autonomous Precision Agriculture Through İntegration of Wireless Underground Sensor Networks with Center Pivot Irrigation Systems, Ad Hoc Networks, 11(7), 1975-1987.
• Doyle, M., How the Internet of Things Helps Grow our Food, Product Lifecycle Report, http://www.ptc.com/product-lifecycle-report/how-the-internet-of-things-helps-grow-our-food, Accessed: 11.02.2017.
• Faulkner, A., Cebul, K., (2014), Agriculture Gets Smart: The Rise of Data and Robotics, Cleantech Agriculture Report, http://info.cleantech.com/Ag-Get-Smart-Report-Submit.html, Accessed: 09.02.2017.
• GIFS, Global Institute for Food Security (2015), Digital and Computational Agriculture, 2014-2015 Annual Report, http://gifs.ca/wp-content/uploads/2015/08/GIFS-2014-15-Annual-Report-final.pdf, Accessed: 11.02.2017.
• Goraya, M. S., Kaur, H., (2015), Cloud Computing in Agriculture, HCTL Open International Journal of Technology Innovations and Research (IJTIR), 16, 1-5.
• Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015), The Rise of “Big Data” on Cloud Computing: Review and Open Research Issues, Information Systems, 47, 98-115.
• IDEAGRO (2015), The Era of Digital Agriculture, http://www.ideagro.es/index.php/noticias/89-the-era-of-digital-agriculture, Accessed: 11.02.2017.
• IRMA, Information Resources Management Association (2016), Big Data: Concepts, Methodologies, Tools, and Applications, IGI Global Publishing, Hershey, p.279.
• Juma, C. (2015), The New Harvest: Agricultural Innovation in Africa. Oxford University Press.
• Kaloxylos, A., Eigenmann, R., Teye, F., Politopoulou, Z., Wolfert, S., Shrank, C., Dilinger, M., Lampropoulou, I., Antoniou E., Pesonen, L. & Nicole, H. (2012), Farm Management Systems and The Future Internet Era, Computers and Electronics in Agriculture, 89, 130-144.
• Lakshmisudha, K., Hegde, S., Kale, N., Iyer, S., (2016), Smart Precision Based Agriculture Using Sensors, International Journal of Computer Applications, 146(11), 36-38.
• Liang, Y., Lu, X. S., Zhang, D. G., & Liang, F. (2002). The Main Content, Technical Support and Enforcement Strategy of Digital Agriculture, Geo-Spatial Information Science, 5(1), 68-73.
• López-Riquelme, J. A., Pavón-Pulido, N., Navarro-Hellín, H., Soto-Valles, F., & Torres-Sánchez, R. (2016), A Software Architecture Based on FIWARE Cloud for Precision Agriculture, Agricultural Water Management, http://dx.doi.org/10.1016/j.agwat.2016.10.020
• Malveaux, C., Hall, S. G., & Price, R. (2014), Using Drones in Agriculture: Unmanned Aerial Systems for Agricultural Remote Sensing Applications, In 2014 Montreal, Quebec Canada July 13–July 16, 2014, American Society of Agricultural and Biological Engineers.
• O’Halloran, D., & Kvochko, E. (2015), Industrial Internet of Things: Unleashing the Potential of Connected Products and Services, In World Economic Forum (p. 40).
• OECD (2012), OECD Environmental Outlook to 2050, OECD Publishing, http://dx.doi.org/ 10.1787/9789264122246-en
• Patel, R., Patel, M. (2013), Application of Cloud Computing in Agricultural Development of Rural India, International Journal of Computer Science and Information Technologies, 4(6), 922-926.
• Porter, M. E., & Heppelmann, J. E. (2014), How Smart, Connected Products are Transforming Competition. Harvard Business Review, 92(11), 64-88.
• Savale, O., Managave, A., Ambekar, D., & Sathe, S., (2015), Internet of Things in Precision Agriculture using Wireless Sensor Networks, International Journal of Advanced Engineering & Innovative Technology, 2(3), 1-5.
• Shen, S., Basist, A., & Howard, A. (2010), Structure of a Digital Agriculture System and Agricultural Risks Due to Climate Changes, Agriculture and Agricultural Science Procedia, 1, 42-51.
• Sørensen, C. G., Fountas, S., Nash, E., Pesonen, L., Bochtis, D., Pedersen, S. M., Basso, B. & Blackmore, S. B. (2010), Conceptual Model of a Future Farm Management Information System, Computers and Electronics in Agriculture, 72(1), 37-47.
• Sönmez, V. ve Alacapınar, F.G (2014). Örneklendirilmiş Bilimsel Araştırma Yöntemleri. Genişletilmiş 3. Baskı. Ankara
• Sun, Z. F., Du, K. M., & Zhang, F. X. (2013), Perspectives of Research and Application of Big Data on Smart Agriculture. J. Agric. Sci. Technol, 15(6), 63-71.
• Tan, L. (2016), Cloud-based Decision Support and Automation for Precision Agriculture in Orchards, IFAC-PapersOnLine, 49(16), 330-335.
• TOBB (2013), Türkiye Tarım Sektörü Raporu 2013, TOBB Yayınları, https://www.tobb.org.tr/Documents/yayinlar/2014/turkiye_tarim_meclisi_sektor_raporu_2013_int.pdf, Acceessed: 12.02.2017.
• Tripicchio, P., Satler, M., Dabisias, G., Ruffaldi, E. & Avizzano, C. A. (2015), Towards Smart Farming and Sustainable Agriculture with Drones, In 2015 International Conference on Intelligent Environements, 140-143. IEEE.
• Tüylüoğlu, Ş. & Saraç, Ş. (2012), Gelişmiş ve Gelişmekte Olan Ülkelerde İnovasyonun Belirleyicileri: Ampirik Bir Analiz, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 7(1), 39-74.
• UNECE, (2013), Classification of Types of Big Data, Big Data in Official Statistics, http://www1.unece.org/stat/platform/display/bigdata/Classification+of+Types+of+Big+Data, Accessed: 10.02.2017.
• van der Wal, T., Kooistra, L., & Poppe, K. J. (2015), The Role of New Data Sources in Greening Growth: The Case of Drones, In 2015 OECD Green Growth and Sustainable Development Forum, Paris, 14.12.2015.
• van Es, H.M., J.D. Woodard, M. Glos, L.V. Chiu, T. Dutta, and A. Ristow. 2016. Digital Agriculture in New York State: Report and Recommendations. Cornell University, Ithaca, NY.
• WBCSD (2008), Agricultural Ecosystems: Facts and Trends, WBCSD Publishing, http://www.wbcsd.org/Projects/Climate-Smart-Agriculture/Resources/Agricultural-Ecosystems-Facts-and-trends ,Accessed: 12.02.2017
• WBCSD (2009), Water Facts and Trends, WBCSD Publishing, http://www.unwater.org/downloads/Water_facts_and_trends.pdf, Accessed: 12.02.2017
• Weltzien C., (2016), Digital Agriculture or Why Agriculture 4.0 Still Offers Only Modest Returns, Landtechnik, 71(2), 66–68.
• Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017), Big Data in Smart Farming–A Review, Agricultural Systems, 153, 69-80.
• Yane, D. (2010, October), Research and Analysis about System of Digital Agriculture Based on a Network Platform, In International Conference on Computer and Computing Technologies in Agriculture (pp. 274-282). Springer Berlin Heidelberg.
• Yin, R. K. (1994). Case Study Research. Design and Methods, Applied Social Research Methods Series, 5, (ed. Sage Publications).
• Zhang, Y. (2011, February), Design of The Node System of Wireless Sensor Network and Its Application in Digital Agriculture, Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2011 International Conference on (pp. 29-35). IEEE.
• Zhu, Y., Wu, D., & Li, S. (2013), Cloud Computing and Agricultural Development of China: Theory and Practice, International Journal of Computer Science Issues, 10(1), 7-12.