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Using Data Analytics to Avoid World Hunger

January 30, 2016

Using Data Analytics to Avoid World Hunger

An Emerging Crisis

It could be an episode right out of Mission Impossible. Within the next 35 years, the world community needs to find a way to produce an estimated 60% more food to feed nearly 10 billion people – more than 2.3 billion more than today.  If that is not challenging enough, food safety issues caused by such naturally occurring contaminants as mycotoxins and human-induced fraud and adulteration are becoming more widespread and serious in nature. 1 Add to that the effects of global climate change, scarce natural resources, and a troubling tendency among the world’s developed nations to simply throw out or waste more than a third of all food produced for human consumption and you will have a better idea as to the scope of the massive task that lays ahead. 2

Why should all of this be of concern to you? According to McKinsey & Company, a global research and consulting firm, agribusiness is a $5 trillion industry that accounts for 20% of global spending, 40% of worldwide employment, and 30% of greenhouse gases produced each year. If current trends continue, difficult choices need to be made that will require some disruptive solutions. 3

Data as a Solution

Part of virtually every solution for meeting world food needs is to leverage Big Data. When it comes to agronomics, better data leads to better policies. 4 It enables world food organizations to more easily measure the effect of those policies and “to hold governments accountable for the pledges they make,” according to the Food and Agricultural Organization of the United Nations. 5

Agribusiness firms and farmers in developing nations are increasing their use of technology and data to   better understand crop yields, soil conditions, weather patterns, pest infestation, and more. The goal is to spread the technology and best practices to developing countries. Monsanto -traditionally a chemicals, seeds, and genetic traits company - has announced it is transitioning to a greater emphasis on data science and services. Chief Technology Officer Robert T. Fraley told Reuters the company would offer services and solutions that use data to help farmers boost crop yields. 6

The Right Data Tools for the Job

A major, multinational agricultural company has been applying data solutions to improve its productivity, innovation, collaboration, transparency, and intellectual property protection for over a decade. The company has been expanding its use of PerkinElmer’s exclusive offering of the TIBCO Spotfire® analysis and visualization software across its R&D, QA/QC, and commercial operations.

As an enterprise solution, TIBCO Spotfire® is helping the company improve farming practices, protect crops from pests and diseases, and make more efficient use of farming resources, including water. Why TIBCO Spotfire® software? The company cites four primary reasons:

1. Enables company leaders to build and visualize analytical pipelines.
2. Easily handled the large volumes and variety of data.
3. Integrates with the enterprise’s data ecosystem.
4. Demonstrates a commitment to the R&D market.

Dow AgroSciences, an agribusiness company, meanwhile, uses a different PerkinElmer solution, the E-Notebook, an electronic laboratory notebook which provides templates for the physical science sector. For more than eight years, Dow’s R&D scientists working on insecticides, herbicides, fungicides, and more have tracked all individual and group experiments using E-Notebook. The data is date- and time-stamped, easily searchable, and secure. E-Notebook also serves as a long-term data archive and central repository for Dow’s R&D scientists to search, retrieve, and find the right information quickly for analyses that can drive innovation.

Dow AgroSciences has found that data quality improved with E-Notebook, first by eliminating the risk of manual transcription errors, but also because users are far more likely to directly upload Excel spreadsheets and other supporting files to their experiments. This level of detail enriches the record, compared to summary notes in a paper notebook. Scientist productivity has increased 10-15 percent as well - no small accomplishment when the challenge to improve the food supply is so great.

Learning From Others

From finance to pharmaceuticals, other industries leverage big data to drive innovations from deeper insights - and agribusiness is no different. PerkinElmer’s informatics solutions have been helping agribusiness clients for years to achieve better insights from data in order to do the important work of improving crop yields, reducing disease and infestation, and finding solutions for constrained resources.

The planet is counting on farmers and agribusiness to feed the growing population. To meet this challenge, agribusiness must leverage data – and have the best tools available to collect, manage, store, retrieve, analyze, and visualize that data for maximum effect.


  1. Silvia W. Gratz, Neil Havis, Fiona Burnett, “Fusarium Mycotoxin Contamination In The Human Food Chain,” New Food, Vol. 18, Issue 4, pp. 56 – 58.
  2. Food and Agricultural Organization of the United Nations, “Feeding Nine Billion in 2050,” Food and Agricultural Organization of the United Nations News Release, April 12, 2013. See also, "Food losses and waste in the context of sustainable food systems", a report by The High Level Panel of Experts on Food Security and Nutrition, June 2014.
  3. Lutz Goedde, Maya Horii, and Sunil Sanghvi, “Pursuing The Global Opportunity In Food And Agribusiness, McKinsey&Company, Insights & Publications, July 2015.
  4. “Big Data I: Leveraging Big Data in Agriculture Production,” International Food and Agribusiness Management Association, World Conference, Minneapolis-Saint Paul, 2015.
  5. Food and Agricultural Organization of the United Nations, Statistical Pocketbook, World Food and Agriculture, 2015 (Rome: Food and Agricultural Organization of the United Nations, 2015), p. 1.
  6. P.J. Huffstutter, Carey Gillam, “Pivoting After Failed Syngenta Bid, Monsanto To Build Big Data Business,” Reuters, September 24, 2015.

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