From Singapore to the USA and all around Europe, Edible Innovations profiles food makers that engage in improving the global food system at every stage, from production to distribution to eating and shopping. Join us as we explore the main trends in the industry from a maker perspective. Chiara Cecchini of Future Food Institute — an ecosystem with a strong educational core that promotes food innovation as a key tool to tackle the great challenges of the future — introduces you to the faces, stories, and experiences of food makers around the globe. Check back on Tuesdays and Thursdays for new installments.


Today we meet Leo Bottrill, an expert in mapping technologies. He is the founder and director of Moabi, a nonprofit organization dedicated to developing the technology to map and monitor logging, mining, palm oil, and other resource-related infrastructure. A man passionate about chocolate, he is also working on a new project that’s focused on cocoa farming.

The Overall Problem

While all of us enjoy a tasty bar of chocolate, cocoa is directly and indirectly responsible for an enormous of amount of deforestation across the cocoa belt of West Africa. Cocoa beans meander through a complex web of actors from farm to factory, which currently makes linking deforestation to a particular farm nearly impossible. Cocoa has millions of farmers with small cocoa plots. It’s there that Leo sees the opportunity to spot the deforestation-free beans (separating them from the dirty ones), and the potential to sing praises of the technology working to improve the cocoa system.

Leo, what is the main takeaway from this overall problem?

Well, I think the main problem is that we don’t know from which farm our beans come from. We don’t know whether the cocoa supply chain is deforestation-free. I believe technology has reached a level where we can actually hack this problem and bring more clarity. That’s what I’ve been working on for a while!

Can you tell us a bit more about the technology you have been working on?

In the last few years I’ve been focusing on mapping technologies that will allow people to securely upload and edit spatial data (e.g. shp, geojson kml, csv., etc), create new data, and manage who can access and edit information. Together with other makers, I’ve created an open source tool that allows everybody to make a map and share it. This is a tool for every maker, both working in food and not, who is interesting in adding a mapping land piece to his or her project. You can already take a look at the beta!

Can you show us how you are using this technology and how other makers could do the same?

Sure!

What we are trying to do is simply make it easier for other makers to make and manage maps. The tool we have been using keeps everything in the same place, and assembles multiple map layers to interpret the scale and causes of deforestation in different locations.

Using that platform, I am now developing a tracking system for cocoa farmers and distributors.

Our idea was to use cocoa trucker drivers, who typically have smartphone phones, to collect geo-referenced photographs of cocoa depots – locations where farmers drop off their crop for pick up. We have a first prototype of a smartphone application that doesn’t require network access to function. At each depot, the driver just snaps a photo with the GPS turned on, records the weight of the beans, and optionally asks the farmers the distance they travelled from their farm.

When the truck driver arrives at the coop or processing facility, they transfer the data from their phone to the Coop app by scanning a QR code. Coops and processors are typically located in towns and cities where there is 3G coverage and internet. The Facility Coordinator can then run a deforestation report on all the depot points, setting a custom buffer around them (e.g., 1km), or using information collected from farmers. In a matter of seconds, the facility coordinator receives statistics on total deforestation annually from 2000-2016 and the remaining 80% canopy of cover forest. These statistics area weighted mean for the truckload of the cocoa based on weight and distance information collected. The depot areas can then be monitoring weekly using University of Maryland GLAD forest alerts. The Coop app can then rank depots with the most remaining forest cover and the highest rates of deforestation.

This is an example of how we can build on the open tracking platform and create incremental value.