If you want to see the power of big data, look no further than one of the world’s oldest industries. Data science and data analytics are the technology drivers leading a revolution in the agricultural sector. These large data sets are not only helping to improve the productivity of individual farms – it’s also helping to ease the global food crisis.

Digital transformation to help global food supplies

Global food demand continues to grow. A report from the World Government Summit shows that  by 2050 we will need to produce 70% more food. About 800 million people around the world suffer from hunger – yet ag’s share of the global GDP fell to one-third of its contribution just decades ago.

Ag must embrace a digital, connectivity-fueled transformation to overcome increasing demand and several disruptive forces. It’s happening – the adoption of data analytics in ag has been increasing consistently, and  its market size is predicted to grow at a compound annual growth rate of more than 12%.

As supply and demand side pressure intensifies, policymakers and industry leaders must seek assistance from technological innovations, including big data, AI, analytics, and cloud computing. The COVID-19 pandemic led to increased demand and other issues such as labor shortages. As  McKinsey pointed out, other factors impacting global food supply chains include supply side challenges such as constraints in land and farming inputs, along with the lack of a solid connectivity infrastructure.

farm shipping truck-reduced (1)

Fewer resources to produce stronger results

Big data and AI now play a pivotal role in farm resource efficiency and will be crucial to producing more food with less resources in the coming decades. Big data and AI help farmers quickly derive actionable insights about the operations of their farms.

A great example is the recent surge in the use of imagery-based analytics in agriculture. Imagery has been available to farmers for decades. In the 1970s free satellite imagery became available to farmers through NASA’s Landsat program. However, imagery had a minimal impact on resource use efficiency at the farm level until the last decade, when advances in computing power and the use of AI made it possible to distill insights from imagery data.

Now farmers are using imagery to reduce water use and apply fertilizer only where it is needed. For example, technology from Ceres Imaging combines imagery with AI to evaluate crop health on a per plant basis to help farmers in California reduce their water use by 10% on average.

With increasing pressure to grow more with less, farmers are turning to big data to help make decisions about where and how to be more sustainable.

 The balance of risks and rewards

In addition to helping reduce resource use on farms, increasingly AI is being used to mitigate some of the risks and uncertainties pervasive in farming as well. When a disease outbreak rages through the Midwest due to unseasonably wet conditions, for example, AI can be used to predict the location and mitigate the impact of such diseases helping farmers take actions to protect yields before disease strikes.

While protecting yields by predicting disease outbreaks benefits farmers, the benefits of using AI amplifies as it ripples down the supply chain, from agriculture insurers and lenders to food distributors and retailers and eventually all the way to the consumer. As climate change and political instability, coupled with growing demand, put more pressure on our food system, AI and big data play a pivotal role in reducing risks and ensuring a sustainable food supply chain.

As such, one roadblock to overcome is the balance of costs and benefits in deploying AI solutions within the agriculture sector. Since the whole supply chain benefits when the farmer uses AI and big data to drive decisions that reduce risk and increase yields at the farm level, the costs of deploying such solutions shouldn’t sit only with the farmer and must be shared by the whole supply chain. As downstream players like agriculture insurers and major food brands continue to see the benefits of big data and AI in their upstream supply chain, it is likely they will invest in the deployment of such technologies down to the farm level.

Supply chain innovation

The agriculture supply chain is going to look completely different in the near future. Nearly every step of the chain is going to be more data intensive. This will lead to mass improvements in resource-use efficiency on the farm level. In addition, the benefits of big data and AI will help reduce disruptions in the food supply chain and better inform financing and insurance risk models in ways that were previously unimaginable.

Risk Solutions from Ceres Imaging offers insurers and lenders the advantage of finely tuned data models—refined by more than 11 billion individual plant-level measurements, captured over ten years and more than 40 crop types—to help you adapt to change.

Risk Solutions

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The difference between Ceres Imaging and other technologies I've used is the help I get from their expert team.
Jake Samuel, Partner
Samuel Farms
With Ceres Imaging we can take a more targeted approach to applying fertilizer and nutrients.
Brian Fiscalini, Owner
Fiscalini Cheese Company
These flights can cover way more ground and provide more insight than a dozen soil moisture probes — and it's cheaper to implement.
Patrick Pinkard, Assistant Manager
Terranova Ranch
The average Ceres Imaging conductance measurement from its imagery over the season has provided the best correlation with applied water.
Blake Sanden
University of California Cooperative Extension