AI for IA: Artificial Intelligence for Innovative Agriculture

By ESG Analyst Louise-Marie Sur

Optimization, efficiency, precision, analytics, impact: they were once industry-specific nomenclature, but have now become colloquial thanks to AI integration. This cutting-edge technology has allowed companies to automate processes, maximize capabilities, minimize costs, sharpen know-how and widen margins, but the power of vertical AI—an application that is uniquely specialized to support a specific sector—has increasingly been leveraged by agricultural companies of all sizes to tackle imminent social and environmental concerns. Seeing this gap in the market as an opportunity, various AgTech startups have been propping up aiming to provide tailored support at all levels of the food value chain: input use, crop production, disease resistance, livestock management, biodiversity, soil maintenance, supply chain and farmer livelihoods. 

Staple commodity producers have leveraged precision agriculture technologies – such as US-based Taranis and Australian equivalent, The Yield – which capture leaf-level images using satellites and drones to pinpoint potential issues on the field. Their app’s AI software powered by millions of data points from farms nationwide can give individual farmers feedback on their crop health and soil characteristics, and generate personalized strategies that would make their enterprises more efficient. Similarly, agronomic analytic and machine learning tools provided by Sentera and Grointelligence have been implemented by producers to better manage their input use and lessen the ecological impact of supply chains. As of now, the capabilities of these technologies have yet to be maximized by specialty crop producers due to investment and scaling difficulties.

            I had the pleasure of speaking with Xavier Sagnieres, an executive of 12Tree and CEO of Andean Cacao, whose efforts are focused climate-smart approach to large-scale cacao production. Based in Colombia, the company has successfully converted over 2000 hectares of degraded pasture lands to regenerative agroforestry systems delivering carbon-neutral cacao and supporting over 600 employments. Due to the vulnerable nature of tropical crops, the industry standard for over 90% of the world’s cacao production comes from farms of less than 2 acres in size. Bearing testament to Andean Cacao’s scalability through environmentally responsible and socially ethical means is its recent partnership with Mars Wrigley and Cacao for Generations, an initiative highly committed to leveraging technologies that bolster efficient production systems that generate positive externalities for the soil and the participating smallholder farmers. 

This interview has been edited to ensure conciseness and cohesion. 

What does AI for IA mean for Andean Cacao and how are these technologies leveraged at various levels of the organization?

Xavier: To produce cacao at scale on lands with compromised fertility, the company crosses past satellite imagery with soil samples taken from the field to guide its decision-making in plots to purchase and then optimizing the design of the farm in those areas. These images grant the company insight into the physical and chemical composition of the soil, topography, and knowledge of previous uses of the farm, which then facilitates management decisions like knowing where best to place drainage and irrigation systems and infrastructure, generating demand for certain machines, and ultimately deciding where to place the cacao plants to not only maximize production but to limit the footprint created as a result.

Where do you see a void in the productive system that integration of AI could support

Xavier: The company is really looking towards expanding its use of precision agriculture to support an “agroeconomic management unit.” By being able to garner all vital information on soil characteristics using a sample, tailored micro adaptations can be implemented on a lot basis to ensure efficient input use and farming practices. Currently, these practices cover 30 hectares and are done by non-AI software, but the hope is to expand enough to generate enough data points where the process could become automated and forecast future conditions. 

The environmental and economic benefits of technology-driven production optimization are evident. What are potentially some social benefits that you have witnessed at the producer and community level?

Xavier: Direct impact on the smallholders is limited as they do not have iPhones themselves. However, indirectly, technology enables us to validate their compliance with sustainability standards (EUDR), thereby granting farmers access to European markets to sell their products. Additionally, technology allows for better traceability, increasing international buyers’ willingness to pay for our cacao. 

With sustainability being a core focus for stakeholders at all levels of the value chain, Public-Private Partnerships (PPPs) have increasingly become a medium through which investing companies and producers can mutually benefit. Historically these investments have been used to generate know-how and implement optimizing strategies in rural areas. In your experience, what role have you witnessed precision agriculture and/or machine learning technologies play in these initiatives? If not, in which ways do you think these future private investments should be tailored to capitalizing on these technologies in the future? 

Xavier: Specialty crops are smallholder-dominated, so there is less investment in R&D and less data collection as a result. Additionally, these tropical crops are often very difficult to manage; cacao as its productivity is greatly at the discretion of climate and pruning techniques. Industry groups are not currently focused on technology, but it would help to give more permanency to what is taught to smallholders. For example, when farmers go to a pruning conference, they watch a couple of slides and leave. Technology can create a way to keep up with trials and measure their actual effects. As for AI, I would be excited to see augmented reality goggles that are commonly used in manufacturing applications on our farms. They could give farmers immediate information on the architecture of individual trees and insight on which pods to harvest, or which leaves to prune while leaving them with both of their hands free to work. This sort of technology exists to some extent on iPhones and 360 scans, but AI integration would be much more efficient. 

The integration of artificial intelligence has become the linchpin to innovation in most industries, and sustainable agriculture is proving to be no different. Although these advancements have been undoubtedly easier to integrate in large-scale staple crop production, the potential payoff for specialty crops and positive externalities on producers and the environment alike are evident. 


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