Big data poised to transform the global food chain

To achieve food and nutritional security, for present and future generations, an agricultural transformation is not only required. It is vital.

Photo by A. Lane / Bioversity International


We are under no illusion that the world population is exponentially expanding and is expected to hit 9 billion by 2050.

It is only natural then that this projected populace will place more and more stress on the already strained food and nutritional resources available to the globe, relegating some regions of the world to perpetual susceptibility to hunger and malnutrition.

The effects of climate change that result in unpredictable seasons and increased frequency of extreme weather events – mostly because we are already hitting the ecological limits of our universe – only make it more difficult to sustain agricultural production.

The situation is further aggravated by the diminishing of arable land suitable for agricultural production as a result of the exchange of farmlands for high rising buildings and cities through rapid urbanization.

To achieve food and nutritional security, for present and future generations, an agricultural transformation is not only required. It is vital.

The use of big data can birth unconventional and innovative solutions leading to a significant and sustainable increase in agricultural production while minimizing the environmental footprint of farming. possible to feed the world quantitatively and qualitatively with high quality and nutritious food. Big data is poised to transform the global food chain.

Big Data Solutions

Crop yield

Transformation of the agricultural landscape has a long list of needed metrics. But one of the most important aspects is the increase in crop yields. The synthesis of data from a wide variety of sources can inform scientific crop improvement.

Similarly, actionable information from the growing pile of data can lead to crafting better seeds that can then increase crop yields. It is imperative that big data solutions in this area be emphasized since half of the increase in global food production, so far, can be attributed to genetic improvement.

Precision farming for resource conservation

Of equal importance to agricultural transformation are the increased levels of precision in farm inputs application.

In this regard, real-time sampling of soil that is run through spatial data sets can be used to predict the current fertilizer requirements for a farmer’s crops.

These insights can be helpful to tame runaway input costs experienced in a myriad of farms. Also, information from sensors and monitors that are complemented by soil moisture data can be used to optimize the utilization of water resources, hence minimizing wastage of this ever-important resource.

New capabilities in the collection of weather data additionally help farmers schedule irrigation programs for their crops. This enables them to limit the use of water only to seasons when it is needed and informs them when to employ water harvesting techniques, increasing water conservation.

While mechanization is central to ensuring improved yield, proper capacity utilization of tools and overall equipment effectiveness are critical factors that need to be considered.

Sensors and trackers are becoming more common in farm equipment and the data transmitted to the farmer can provide insights on operational efficiency on matters that border on equipment leasing, sharing, timely scheduled maintenance and in the minimization of the equipment energy usage.

Combatting pests and disease

In regards to crop pests and diseases, the twin data-driven services of plant monitors and real-time leaf and stem imaging give early signs of infirmity through predictive analytics. They can even provide insights on the measures to combat them.

This will help manage the spread of pathogens that create catastrophic losses to the farmer, hopefully relegating this threat to a thing of the past.

Finance tools to influence food value chain

Big data application is not only limited to primary production but can go further to influence the entire food value chain.

Take agricultural lending for instance. Through historical lending data analytics, financial models that provide alternative credit scoring can be used to rate agricultural enterprises.

It is true that the financial sector views the agricultural sector through the skeptic’s lens of high risk. However, big data is already playing a huge role to structure incentive and risk sharing algorithms, as well as models for the development and private sector, to unlock the financing needed for smallholder family farms.


There are more benefits. Post-harvest losses represent 1/3 of all food produced, amounting to almost $ 1 trillion, which could be substantially reduced by applying big data strategies.

Drones can patrol fields and provide useful data on crop maturity.Traceability systems also can provide useful information on farm products moving through the supply chain.

In addition, the proliferation of technology powered by big data makes it possible to improve the packaging and labeling of food products while also detecting spoilage through monitoring the gases emitted by canned food products.


In essence, all these predictive and forecasting insights, combined with the real-time solutions based on data, can improve a farmer’s decision-making capabilities. As a consequence, integrated and enhanced strategies and systems for agricultural production can come to fruition.

Big data is poised to catalyze agricultural transformation, making it possible for plants to thrive in changing climatic conditions, enabling an increase in productivity and the achievement of food and nutritional security and, in addition, deliver high quality and safe food for the global populace.

Data analytics will drive farmers’ decisions on what to plant, when to plant it and even how to plant these crops, affecting both profitability and sustainability.

Big data technology can, therefore, help engineer agricultural transformation characterized by a steady rise in yields, similar to the one experienced in the 1960’s.

Smallholder farmers from around the planet, at the very least, are desperate for this kind of transformation.

Apr 11, 2018

Victor Mugo

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