INFORMS 2017Agricultural AnalyticsChallenges and opportunities of establishing data-driven agronomic services to small-scale

farmers across the world (MD54)

362A. Monday Oct 23, 2017 4:30 PM - 6:00 PM

Session SummaryA wide range of services, mostly in developed coun-tries, offer farmers the possibility of making better data-driven decisions including what to plant the next season, what is the most profitable crop, the right amount of fertilizers, etc., Large producers have often been able to capitalize on these services, smaller producers often find themselves on wrong side of the technology divide. In this session, we seek to explore answers on how data-driven approaches can support farmers to increase pro-ductivity, provide farmers with climate services and predict the occurrence of fungal diseases.

Agronomic Modeling Scientist. Drew graduated with honors from Yale University having studied Economics with focus on the applied use of econometrics. During his Master’s (Duke University) and PhD work (North Carolina State University), Drew applied his skills to a number of diverse areas of study. These topics include but are not limited to the optimization of crop rotations in the Eastern Coastal Plain of North Caro-lina in support of transitioning farmland to Organic usage, the develop-ment of complex Bayesian based variable selection algorithms to better understand the drivers of farmland loss in North Carolina, and economic analyses of burgeoning specialty crop markets in the state with particu-lar attention paid to the issue of rural development. Drew now leads aWhere’s efforts to develop statistics based models to provide actiona-

ble and insightful information across the agricultural value chain. Drew’s work makes extensive use of hierarchical regression analysis, data mining, machine learning, copula modeling, and spatio-temporal analyses all implemented through a nuanced understan-ding of agriculture, soil science, and ecology.

Drew Marticorena

P a n e l i s t s

Currently Strategy Lead for Sustainable Intensification in Latin America at the International Maize and Wheat Improvement Center (CIMMYT). He is dedicated to turning subsistence agriculture and failed farming systems into productive and sustainable production units that make it possible for farmers to escape hunger and poverty in the developing world. At CIMMYT, Govaerts leads the centers’ research on conservation agriculture, applying science to the development of sustainable farming practices and methods that are specifically designed to meet the challenges confronting the rural poor. Since 2007, Govaerts has led the Mexico based conservation agriculture program in CIMMYT. From

2003-2007 he was Research Associate with the Katholieke Universiteit Leuven conducting research for the Ph D dissertation. Bram Govaerts holds a Master and Bachelor of Science in Bioscience Engineering, specialization Soil Conservation in combination with Tropical Agriculture at the Katholieke Universiteit Leuven, Belgium. Bram Govaerts has authored >58 peer reviewed journal articles, >19 book chapters and numerous papers in internatio-nal conferences. Govaerts received the Development Cooperation Prize 2003 of the Bel-gian Federal Government and was appointed Belgian O�cial Representative of the Inter-national Youth Forum for the Food and Agriculture Organization of the United Nations in 1997. Bram Govaerts received the 2014 Norman Borlaug Award for Field Research and Application, endowed by the Rockefeller Foundation on October 2014, in Des Moines, Iowa.

Bram Govaerts

Julian Ramírez

Associate Professor and Extension Specialist, Crop, Soil, and Environ-mental Sciences Department. Dr. Brenda Ortiz is an Associate Professor at Auburn University. She has an extension and research appointment in the area of Precision Agriculture. Her Ph.D. is in Biological and Agri-cultural Engineering from The University of Georgia. Her main research and extension interests include evaluate different management practi-ces to reduce aflatoxin contamination in corn, the study the impact of weather and climate on agriculture especially corn and wheat crops, identification of adaptation strategies to reduce climate-related risk in agriculture, the use of field studies and crop growth modeling to eva-

luate different management strategies for improving grain production, evaluation of irri-gation scheduling strategies (sensor-based) for corn production, variable rate irrigation, and the use of remote sensing technologies for variable rate application of nitrogen. In 2015, she was the leader of the Precision Agricultural Systems Community of the Ameri-can Society of Agronomy. Because of her expertise in Precision Agriculture, she has been invited by several Universities in Europe and South America (Brazil in particular) to mentor their graduate student and to work on collaborative projects.

Brenda Ortiz

Holds a PhD in Environmental Science at University of Leeds. His work is on climate, crop modelling as well as biodiversity conservation espe-cially in the context of climate change, making use of statistics, crop and species distributions models and geographic information systems (GIS). Currently he focused mainly in spatial analysis of relationships between environmental factors on both crop production systems and biodiversity, including crop wild relatives and leads research on clima-te services and climate change adaptation. He has published more than 40 papers, iIncluding high impact journals such as Nature Clima-te Change, Nature Plants, PNAS, amongst others.

Colombian agronomist Daniel Jiménez is a scientist at the International Center for Tropical Agriculture (CIAT). He holds a PhD in Applied Biologi-cal Sciences (Agriculture) from Ghent University, and is the coordinator of the Data-Driven Agronomy Community of Practice of the CGIAR Plat-form for Big Data in Agriculture. Daniel’s data-mining approach to agro-nomy allows decision makers in agriculture to accelerate and enhance the impact of agricultural research in the face of pressing challenges such as yield gaps and climate change. In recognition of this work, the United Nations selected Daniel as one of two winners of its Big Data Climate Challenge in 2014. He was also selected by the World Bank as

one of the winners of the first World Bank Group Big Data Innovation Challenge in 2015; and in 2017 he led one of the three teams whose work was selected by the United Nations Climate Change secretariat as one of the winners of the Momentum for Change award. Before joining CIAT, Daniel worked at Bioversity International and the University Of Applied Sciences Of Western Switzerland (HEIG-VD), and was also a consultant for the French Agricultural Research Centre for International Development (CIRAD).

Daniel Jiménez

Session Chair

Simulation Based Fungal Disease Modeling In Agriculture Using Big Data (Drew Marticorena): The FAO estimates that over 1B MT of food are lost due to the fungal diseases yearly. In addition, associated toxins because harmful health effects to both animals and people that consume the contaminated food. These issues are especially prevalent amongst smallholder producers. The ability to predict where and when fungal diseases are likely to occur would be of great value across the agricultural value chain and would improve the lives of smallholder producers. Using field datasets and modern parameter optimization.

Increasing agricultural production and resilience through data services and decision support sys-tems (Brenda Ortiz): The farming community is currently being challenged to build resilience to climate change and to increase crop productivity through the adoption of practices and technology. Our extension efforts have showed that low adoption of decision support systems is due to the lack of engagement with farmers during the conceptualization and development process. A success farmer’s engagement story is the Tri-state Climate Learning Network for Row Crop Agriculture. Through bi-annual meetings, we learned that awareness on the limitations of the data, the applicability of climate information to crop management, and the co-development of usable decision support tools are key elements of farmers’ adoption.

Data-driven agro-climatic services improve farmer responses to climate variability (Julian Ramírez): Climate is one of the most important factors influencing the performance farming systems. In Colombia, climate variability explains between 30-60 % of rice yield. Farmers, however, make decisions in their farms including issues related to planting date, what variety to plant, or whether to plant, at best, on the basis of no information. We develop data-driven seasonal crop-climate prediction analyses that feed into the deve-lopment of a climate services platform. The analyses demonstrate that the combination of skillful seasonal climate forecasts, calibrated crop models, and a forecast platform tailored to users’ needs can prove suc-cessful in establishing a climate service for agriculture.

Crowed Sourced data for decision making and taking in resilient agrifood systems: (Bram Govaerts): Managing the hugely complex risks that are associated with the food system of the 21st century is a major challenge for decision makers in government, civil society and the private sector alike, and one that has been neglected for the past 30 years. Therefore complex agriculture innovation systems (AIS) that can support agrifood systems for nutrition, nature conservation and national and international security are required. While Knowledge Management (KM) is an important component of AIS. Previous KM frameworks did not account for the fact that agricultural systems are complex systems and did not integrate innovation with KM. The results presented will show a real case of an AIS that was implemented in Mexico including crowd sourcing of on plot data to develop complex decision support systems. The case presented shows that these approached can boost performance and steer complex systems in ways that benefit all stakehol-ders.

Abstracts

Robin Lougee is the IBM Research Lead for Consumer Products & Agri-culture. Robin chairs the 2017 Syngenta Crop Challenge Award in Analytics Prize Committee and serves on the Advisory Committee for the World Agritech Investment Summit. She is an industrial research scientist with a strong track record of delivering innovation to IBM and its customers. Robin pioneered the creation of COIN-OR, an open-sour-ce foundry for computational operations research, and led its growth to an independent non-profit that has served the scientific and business community for over 15 years. She was elected to the Board of INFORMS, the largest society in the world for professionals in the field of opera-tions research, management science and analytics, Chair of the INFOR-

MS Computing Society, and President of the Fora of Women in ORMS. She is an Associate Editor of Surveys in Operations Research. Robin earned a Ph.D. in Mathematical Sciences from Clemson University in 1993.

Robin Lougee

Track Chair