Main Article Content
Abstract
The consistent advancement of innovation has implied information and data being created at a rate, not at all like ever previously, and it's just on the ascent. The world makes an extra 2.5 quintillion bytes of information every year. The demand for individuals talented in investigating, deciphering, and utilising this information is now high and is set to become exponential over the coming years. The total populace is relied upon to arrive at 9.7 billion by 2050 from the current population of 7.8 billion. The Food and Agriculture Organization (FAO) has predicted that the development of farming must be expanded by 70% to provide for the extended interest. Data-driven agriculture choices can be a potent technology to manage the needs of this much high population, as this technology gives higher efficiency, rehearses support-ability, and even assists with giving straightforwardness to purchasers and consumers needing to find out about their food as reported in the studies. The current and future interests will require more data researchers, data engineers, data specialists, and chief data Officers. This paper tries to examine the need, use, role, and issues faced by data science and data analytics to improve the quality as well as quantity of Agricultural produce thereby leading to an increase in production, a decrease in costs, and overall sustainability.
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References
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References
Anonymous, 2005. Long-lived digital data collections enabling research and education in the 21st century. Retrieved from https://www.nsf.gov/pubs/2005/nsb0540/
Anonymous, 2016. The future of agriculture. Retrieved from https://www.economist.com/technology-quarterly/2016-06-09/factory-fresh
Anonymous, 2020. University of Illinois College of Agricultural, Consumer and Environmental Sciences. Predicting US end-of-season corn yield. Retrieved from
https://www.sciencedaily.com/releases/2018/09/180927145320.htm
Anonymous, 2018. Taiwan’s rice farmers use big data to cope with climate change. Retrieved from https://www.ft.com/content/9f5438fa-ee2d-11e8-89c8-d36339d835c0
Anonymous, 2019. Animal nutrition solutions. Retrieved from https://www.kemin.com/na/en-us/markets/animal/nutrition
Anonymous, 2018. Startup uses AI to identify crop diseases with superb accuracy – NVIDIA developer news center.
Retrieved from https://news.developer.nvidia.com/startup-uses-ai-to-identify-crop-diseases-with-superb-accuracy/
Barbieri, L. 2018. Grow more food and mitigate climate change? Agricultural soil data could help. Retrieved from https://bigdata.cgiar.org/grow-more-food-and-mitigate-climate-change-agricultural-soil-data-could-help/
Bell, G., Hey, T. and Szalay, A. 2009. Computer science: Beyond the data deluge. Science, 323(5919), 1297-1298. doi:10.1126/science.1170411
Bhutiani, R. and Ahamad, F. 2019. A case study on changing pattern of agriculture and related factors at Najibabad region of Bijnor, India. In: Contaminants in Agriculture and Environment: Health Risks and Remediation. Edited by Vinod Kumar, Rohitashw Kumar, Jogendra Singh and Pankaj Kumar. pp 237-247 DOI: 10.26832/AESA-2019-CAE-0158-018,.
Brown, M. 2017. Agriculture Software Deep Dive — Agriculture Software Interview With Lance Donny. Retrieved https://bowerycap.com/blog/insights/agriculture-software-interview/
Clark, J. 2016. What is the Internet of Things?. Retrieved from https://www.ibm.com/blogs/internet-of-things/what-is-the-iot/
Davenport, T. H. and Patil, D. J. 2012. Data scientist: The sexiest job of the 21st century. Retrieved from https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century
Dhar, V. 2013 Data science and prediction. Retrieved from https://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/fulltext
Es, H. V. and Woodard, J. 2017. Innovation in Agriculture and Food Systems in the Digital Age. Retrieved from https://www.wipo.int/edocs/pubdocs/en/wipo_pub_gii_2017-chapter4.pdf
FAPESP, 2018. AI in pest control increases its efficiency and environmental impact. Retrieved from https://phys.org/news/2018-02-ai-pest-efficiency-environmental-impact.html
Fauvel, K., Masson, V., Faverdin, P. and Termier, A. 2018. Data science techniques for sustainable dairy management. Retrieved from https://ercim-news.ercim.eu/en113/special/ data-science-techniques-for-sustainable-dairy-management
Gupta, S. 2015. William S. Cleveland. Retrieved from https://www.stat.purdue.edu/~wsc/
Hayashi, C., Yajima, K., Bock, H., Ohsumi, N., Tanaka, Y. and Baba, Y. 1998. What is data science ? Fundamental concepts and a heuristic example. Studies in Classification, Data Analysis, and Knowledge Organization, 40-51. https://doi.org/10.1007/978-4-431-65950-1_3
Hey, T. 2009. The fourth paradigm: Data-intensive scientific discovery. Microsoft Press.
Kshetri, N. 2016. Big Data’s Big Potential in Developing Economies. Retrieved from https://books.google.com.au/ books?id=4fl-DQAAQBAJ.
Leek, J. 2013. The key word in "Data science" is not data, it is science • Simply statistics. Retrieved from https://simplystatistics.org/2013/12/12/the-key-word-in-data-science-is-not-data-it-is-science/
Lohr, S. 2015. The Internet of Things and the Future of Farming. Retrieved October 21, 2020, from https://bits.blogs.nytimes.com/2015/08/03/the-internet-of-things-and-the-future-of-farming/
Maru, A., Berne, D., Beer, J. D., Ballantyne, P., Pesce, V., Kalyesubula, S. and Chaves, J. 2018. Digital and Data-Driven Agriculture: Harnessing the power of Data for Smallholders.Retrieved from https://cgspace.cgiar.org/ bitstream/handle/10568/92477/GFAR-GODAN-CTA-white-paper-final.pdf
Matthews, K. 2019. 6 Ways the Agricultural Industry Is Benefiting From Data Scientists. Retrieved from https://towardsdatascience.com/6-ways-the-agricultural-industry-is-benefiting-from-data-scientists-b778d83f61db
Mello, U. and Raghavan, S. 2019 Smarter farms: Watson decision platform for agriculture. Retrieved from https://www.ibm.com/blogs/research/2018/09/smarter-farms-agriculture/
Mittal, R. 2013. Impact of population explosion on environment. WeSchool "Knowledge Builder" - The National Journal vol.1(01)
Press, G. 2013. Data science: What's the half-life of a buzzword? Retrieved from https://www.forbes.com/sites/gilpress/2013/08/19/data-science-whats-the-half-life-of-a-buzzword/
Press, G. 2014. A very short history of data science. Retrieved from https://www.forbes.com/sites/gilpress/2013/05/28/a-very-short-history-of-data-science/
Sain, M., Singh, R. and Kaur, A. 2020. Robotic Automation in Dairy and Meat Processing Sector for Hygienic Processing and Enhanced Production. Journal of Community Mobilization and Sustainable Development, 15(3), 543-550.
Singh, R., Sain, M., Singh, B., Nagi, H. S. and Bala, N. 2020. Development of a Cost Effective Beverage and Food-Serving Robot for Hygienically Outcomes and Human Comfort. International Journal of Current Microbiology and Applied Science 9(5), 247-257. doi: https://doi.org/10.20546/ijcmas.2020.905.028
Roser, M. 2014. Future population growth. Retrieved from https://ourworldindata.org/future-population-growth
Talley, J. 2016. ASA Expands Scope, Outreach to Foster Growth, Collaboration in Data Science. Amstat News. American Statistical Association.
Tollefson, J. 2018. Big-data project aims to transform farming in world’s poorest countries. Retrieved from https://doi.org/10.1038/d41586-018-06800-8
Trendov, N. M., Varas, S. and Zeng, M. 2019. Digital Technologies in Agriculture and Rural Areas. Retrieved from http://www.fao.org/3/ca4887en/ca4887en.pdf