Opportunities and Challenges for Big Data in Agricultural and Environmental Analysis

Agriculture stands on the cusp of a digital revolution, and the same technologies that created the Internet and are transforming medicine are now being applied in our farms and on our fields. Overall, this digital agricultural revolution is being driven by the low cost of collecting data on everything from soil conditions to animal health and crop development along with weather station data and data collected by drones and satellites. The promise of these technologies is more food, produced on less land, with fewer inputs and a smaller environmental footprint. At present, however, barriers to realizing this potential include a lack of ability to aggregate and interpret data in such a way that it results in useful decision support tools for farmers and the need to train farmers in how to use new tools. This article reviews the state of the literature on the promise and barriers to realizing the potential for Big Data to revolutionize agriculture.

[1]  Kelly Bronson,et al.  Big Data in food and agriculture , 2016 .

[2]  John McLean Bennett.  Agricultural big data: utilisation to discover the unknown and instigate practice change , 2015 .

[3]  S. Swinton,et al.  Using conservation auctions informed by environmental performance models to reduce agricultural nutrient flows into Lake Erie , 2016 .

[4]  Viktor Mayer-Schönberger,et al.  The Rise of Big Data: How It’s Changing the Way We Think about the World , 2014 .

[5]  Advancing U.S. Agricultural Competitiveness with Big Data and Agricultural Economic Market Information, Analysis, and Research , 2016 .

[6]  Jay T. Akridge,et al.  2008 PRECISION AGRICULTURAL SERVICES DEALERSHIP SURVEY RESULTS , 2008 .

[7]  Nir Kshetri,et al.  Big Data's Big Potential in Developing Economies: Impact on Agriculture, Health and Environmental Security , 2016 .

[8]  John M. Antle,et al.  Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology , 2017, Agricultural systems.

[9]  Index Insurance: Using Public Data to Benefit Small-Scale Agriculture , 2016 .

[10]  Yamine Bouzembrak,et al.  Big data in food safety: An overview , 2017, Critical reviews in food science and nutrition.

[11]  Alfons Weersink,et al.  Do farmers waste fertilizer? A comparison of ex post optimal nitrogen rates and ex ante recommendations by model, site and year , 2008 .

[12]  A. Good,et al.  Future Prospects for Cereals That Fix Nitrogen , 2011, Science.

[13]  S. Wolfert,et al.  Big Data in Smart Farming – A review , 2017 .

[14]  W. Parton,et al.  Agricultural intensification and ecosystem properties. , 1997, Science.

[15]  Giacomo Carli,et al.  6 th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013) Drivers of Precision Agriculture Technologies Adoption: A Literature Review , 2013 .

[16]  M. Carolan.  Publicising Food: Big Data, Precision Agriculture, and Co-Experimental Techniques of Addition , 2017 .

[17]  Andrew Schmitz,et al.  Agricultural Policy, Agribusiness, and Rent-Seeking Behaviour , 2002 .

[18]  Spyros Fountas,et al.  Big Data for weed control and crop protection , 2017 .

[19]  B. Whelan,et al.  Flat earth economics and site-specific crop management: how flat is flat? , 2016, Precision Agriculture.

[20]  A. Weersink,et al.  Actual versus environmentally recommended fertilizer application rates: Implications for water quality and policy , 2017 .

[21]  David Tilman,et al.  The greening of the green revolution , 1998, Nature.

[22]  A. Weersink,et al.  Growing Forward with Agricultural Policy: Strengths and Weaknesses of Canada's Agricultural Data Sets , 2014 .

[23]  Estelle Biénabe,et al.  Making transition towards ecological intensification of agriculture a reality: The gaps in and the role of scientific knowledge , 2014 .

[24]  Chandra Krintz,et al.  SmartFarm : Improving Agriculture Sustainability Using Modern Information Technology , 2016 .

[25]  Michael Duffy,et al.  Economies of Size in Production Agriculture , 2009, Journal of hunger & environmental nutrition.

[26]  David C. Rose,et al.  Decision support tools for agriculture: Towards effective design and delivery , 2016 .

[27]  David Besanko,et al.  Economics of Strategy , 1995 .

[28]  R. Sexton.  Market Power, Misconceptions, and Modern Agricultural Markets , 2013 .

[29]  Lee Rainie,et al.  The Future of Jobs and Jobs Training. , 2017 .

[30]  S. Fountas,et al.  Precision Agriculture Technologies positively contributing to GHG emissions mitigation, farm productivity and economics , 2017 .

[31]  M. Goddard.  Uses of genomics in livestock agriculture , 2012 .

[32]  David J. Pannell,et al.  Flat Earth Economics: The Far-reaching Consequences of Flat Payoff Functions in Economic Decision Making , 2006 .

[33]  S. Sonka.  Big Data: Fueling the Next Evolution of Agricultural Innovation , 2016 .

[34]  David Osimo,et al.  Policy-Making 2.0: Unleashing the Power of Big Data for Public Governance , 2014 .

[35]  Bruce Erickson,et al.  Adoption of precision agriculture technologies in Ontario crop production , 2018, Canadian Journal of Plant Science.

[36]  Andrea De Mauro,et al.  A formal definition of Big Data based on its essential features , 2016 .

[37]  Do Landlord-Tenant Relationships Influence Rental Contracts for Farmland or the Cash Rental Rate? , 2015, Land Economics.

[38]  Terry W. Griffin,et al.  Farm’s Sequence of Adoption of Information-intensive Precision Agricultural Technology , 2017 .

[39]  M. Costanigro,et al.  Labeling Food Processes: The Good, the Bad and the Ugly , 2017 .

[40]  Yeong Sheng Tey,et al.  Factors influencing the adoption of precision agricultural technologies: a review for policy implications , 2012, Precision Agriculture.

[41]  J. Woodard.  Data Science and Management for Large Scale Empirical Applications in Agricultural and Applied Economics Research , 2016 .

[42]  J. Shogren,et al.  Economic Instruments and Environmental Policy in Agriculture , 1998 .

[43]  L. Prokopy,et al.  Why farmers adopt best management practice in the United States: a meta-analysis of the adoption literature. , 2012, Journal of environmental management.

[44]  Bernardo B. N. Strassburg,et al.  How can higher-yield farming help to spare nature? , 2016, Science.

[45]  R. Hanner,et al.  DNA barcoding detects market substitution in North American seafood , 2008 .

[46]  Christian Bauckhage,et al.  Feeding the World with Big Data: Uncovering Spectral Characteristics and Dynamics of Stressed Plants , 2016, Computational Sustainability.

[47]  S. Polasky,et al.  Agricultural sustainability and intensive production practices , 2002, Nature.

[48]  L. Pant,et al.  Broadband for a sustainable digital future of rural communities: A reflexive interactive assessment , 2017 .

[49]  G. Griffith,et al.  30 and Daisy: Where’s the Economics in Beef Cattle DNA Testing? , 2016 .

[50]  David Schimmelpfennig,et al.  Farm Profits and Adoption of Precision Agriculture , 2016 .

[51]  B. Gardner.  Changing Economic Perspectives on the Farm Problem , 1992 .

[52]  Uwe Deichmann,et al.  A Tale of Two Surplus Countries: China and Germany , 2016 .

[53]  J. Lusk.  Consumer Research with Big Data: Applications from the Food Demand Survey (FooDS) , 2017 .

[54]  Sergio Terzi,et al.  State of the art of technology in the food sector value chain towards the IoT , 2016, 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI).

[55]  D. Edwards.  The Impact of Genomics Technology on Adapting Plants to Climate Change , 2016 .

[56]  Lian Duan,et al.  Big data analytics and business analytics , 2015 .

[57]  L. Port.  Tony Weis: The ecological hoofprint: the global burden of industrial livestock , 2015 .

[58]  Dong-Hee Shin,et al.  Ecological views of big data: Perspectives and issues , 2015, Telematics Informatics.

[59]  J. McCluskey,et al.  Media Coverage, Public Perceptions, and Consumer Behavior: Insights from New Food Technologies , 2016 .

[60]  B. Barnett,et al.  Canadian Business Risk Management: Private Firms, Crown Corporations, and Public Institutions , 2017 .

[61]  Stephen R. Koontz,et al.  The Economics of Livestock Disease Insurance: Concepts, Issues and International Case Studies , 2006 .

[62]  J. Nørskov,et al.  Farming and the Fate of Wild Nature , 2009 .

[63]  Beverley J. Oda.  Canadian Radio-television and Telecommunications Commission , 2020, The SAGE International Encyclopedia of Mass Media and Society.

[64]  Sabina Leonelli,et al.  Big Data in Environment and Human Health , 2017 .

[65]  Wolfgang Bokelmann,et al.  Analysis of animal monitoring technologies in Germany from an innovation system perspective , 2015 .

[66]  S. Sonka,et al.  Big Data and the Ag Sector: More than Lots of Numbers , 2014 .

[67]  M. Anusha,et al.  Big Data-Survey , 2016 .

[68]  I. Bateman,et al.  Sustainable Intensification in Agriculture: Premises and Policies , 2013, Science.

[69]  Alfons Weersink,et al.  The Growing Heterogeneity in the Farm Sector and Its Implications , 2018 .

[70]  Robin Gebbers,et al.  Precision Agriculture and Food Security , 2010, Science.

[71]  Michael J A Walker,et al.  Horse Meat in Beef Products- Species Substitution 2013 , 2013 .

[72]  Jessica Lindblom,et al.  Promoting sustainable intensification in precision agriculture: review of decision support systems development and strategies , 2016, Precision Agriculture.

[73]  Linus U. Opara,et al.  Traceability in agriculture and food supply chain: A review of basic concepts, technological implications, and future prospects , 2002 .

[74]  A. Good,et al.  “Genes, Meet Gases”: The Role of Plant Nutrition and Genomics in Addressing Greenhouse Gas Emissions , 2016 .