Eugenia Saini is currently FONTAGRO’s Executive Secretary. FONTAGRO is the Regional Fund for Agricultural Technology. She leads the investment fund and a portfolio of 70 international operations related to science, technology, and innovation for the Latin America and the Caribbean region. She is from Argentina and is an agronomist by training. She holds a doctorate in agricultural sciences, specializing in total factor productivity analysis. One of her seminal works in this field was the estimation of 120 years of TFP for the agricultural sector in Argentina. She is also a National Public Accountant and holds an MS in Food and Agribusiness and an MS in Applied Economics, both from Universidad de Buenos Aires. She has worked in the private and public sectors, both nationally and internationally, especially in multilateral banks. She was awarded a Fulbright Scholarship at Cornell University and, more recently, with the Abshire-Inamori Leadership Academy (AILA) Scholarship at the Center for Strategic & International Studies (CSIS) in Washington, D.C.
Artificial Intelligence: A More Precise Green Revolution
The next revolution in precision agriculture has arrived. New technology is customizing the already efficient gains in modern agriculture to move to individual plant and animal precision management. In crop production, this exciting development is being made possible by applying the advanced technology of artificial intelligence to farming equipment by industry leaders such as John Deere.
John Deere Labs opened its office in San Francisco in the spring of 2017 to focus on high technology ventures and product development. Shortly thereafter it acquired Blue River Technology, a startup with computer vision and machine learning technology that can identify weeds, making it possible to spray herbicides only where needed.
By using computer vision and machine learning technologies, machinery can be “trained” to recognize harmful weeds that require a precise dose of herbicide, while allowing other crops around the weed to avoid spraying. This “see and spray” technology has the potential to reduce herbicide applications by up to 95 percent, avoiding the need to spray an entire field and reducing costs and environmental impact.
Similar machine learning can be programmed for targeted applications of fertilizers and irrigation and to detect disease, yield, and quality of crops and soils. The technology will be especially helpful to inform irrigation decisions and water management in water-scarce regions. New applications are also being test to assist with customized livestock management, improving animal health and well-being. A comprehensive review of machine learning and artificial intelligence in agriculture outlines the benefits this emerging technology brings to farmers, the environment and the agri-food system.