In an interesting interview for Veggies From México on technology and innovation and the application of these in the farming sector, German Alfaro Ibarra shares with us a little bit of his expertise as an AI researcher & developer, the use of data, AI, predictive analysis and their areas of opportunity in the sector.
German is both an Agronomist and a Mechatronics engineer; he worked at the Scripps Institution of Oceanography in San Diego, California, USA as a researcher, developing sensors to measure the chemistry of the sea (pH, temperature, salinity) where he had his first approach to data analysis, along with the opportunity to study a Master’s degree in computer science at University of California, San Diego (UCSD), where he became more specialized in Artificial Intelligence (AI) subjects. The last 5 years, he has been devoted to AI development focused on companies in the US, Mexico and Canada.
The agri-food sector in Mexico has turned out to be one of the most dynamic in recent years, as population growth has increase the need for more and better food products. In my opinion, the sector is facing trade restrictions in the export sector, as well as an increase in production costs and difficulties in accessing capital at competitive cost, which puts pressures on food producers and forces them to be more efficient and innovative.
Innovation in companies is an area which has been talked about a lot, but not enough has been done in Mexico. With digitalization (internet), trade barriers between countries have been worn out, causing the development of proprietary technology in our country to be one of our weaknesses.
I see a great need for digitalization of companies in Mexico, in order to become better competitors globally.
The use of AI caused a boom during the last decade. Most of the digital services we use have AI content (Google, Netflix and Facebook). In the financial sector it is used to award credits, combat fraud, as well as investment models; in both manufacture and logistics, its use is increasing as it helps optimizing processes and reducing costs.
In the trade sector, there are systems of product recommendation to customers, and inventory forecasts using AI.
AI finds patterns in information, and farming is one of the most data-generating human activities and perhaps the one with the most uncertainty. I believe that AI has one of the greatest areas of opportunity in farming by reducing risks and costs, as well as increasing production by means of recommendations for so many choices the farmer deals with every day.
Companies generate a great deal of data: sales, production, finance, HR, which has made decision-making increasingly difficult. AI helps finding the interrelation that exists between the date we cannot see at first sight. By identifying these relations, the systems are able to make predictive models and scenarios of what may happen, and in this manner to make suggestions; that is, we are able to create a system that simulates the behavior of business processes, which helps us in making better decisions.
Grow-Mind comes from the need of a group engaged in vegetable production, to make more accurate forecasts about their production that would let them make better choices in the market, as well as choices of production and logistics of shipping the product.
Grow-Mind is a system that streamlines the collection and use of data in vegetable production, data such as: weather, pests, varieties and management. These are entered into the system, which analyzes and simulates the relations between these, giving accurate forecasts in production, as well as recommendations to grow more with less, reducing this way the risk in farming operations.
The pressure from foreign markets can be frequent in the years to come, but above all I see signs of the impact of climate change in farming during the last seasons, which may increase in the coming years and farmers must be prepared, having more information and be better informed on their crops, varieties, climate, etc.
We are using AI in “El Porvenir” field, to make yield forecasts, as well as agronomic and management variables that impact in it, in order to make better choices both as market-logistics and crops; always looking for the higher productivity at a lower cost.
Certifications are essential for the sector, as consumers are more aware of the food they consume. AI could help them find risks in the production stages, that could help ensuring food safety.
I would like to invite farmers to organize their production data (yields, management, fertilization, pesticides, etc.), with good data management, more digitalization and AI, these would help them become more efficient and comply with food safety standards.