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AI in Agriculture: Solutions to Global Challenges

· Ai,Robotics,Robots,Agriculture,Agrarian Economy

AI in Agriculture: Solutions to Global Challenges

May 2019 concluded the third AI for Good Global Summit, a United Nations platform that aims to connect AI innovators with problem owners, in view of developing practical applications of AI to achieve UN Sustainable Development Goals. This interdisciplinary, multi-stake-holder approach to sustainable development brings together UN agencies, governments, industries, international organizations, and members of civil society and academia from 200 countries to solve the world’s most pressing issues.

The United Nations estimates that globally, 1 in 9 (or 815 million) people in the world today are undernourished. Moreover, we are faced with the looming challenge of feeding an additional 2 billion people by 2050. If the UN, and the world, is to even attempt to achieve its “Zero Hunger” Sustainable Development Goal by 2030, it will need to employ all possible strategies to increase efficiency in agriculture worldwide.

Through its continuous analysis of big data relating to climate, lands, crop growing, pests, and other additional agricultural factors, artificial intelligence can help to provide farmers with the information necessary to efficiently allocate their resources. It can also predict natural disasters or meteorological phenomena, in order to respond to these ever-growing global nutritional challenges.

At the 2019 AI for Good Global Summit, the Chinese company XAG presented their approach to these problems using AI and drone technology to efficiently time and allocate uses of such chemicals as defoliant. In the past, due to lack of professional knowledge and reliable data, cotton-producing farmers would douse cotton crops multiple times with defoliant in order to remove all cotton leaves. XAG’s four years of field experiments in deep learning, image segmentation, and convolutional neural network has enabled them to significantly reduce the use of these chemicals. Using this technology to predict cotton opening time and optimal times to conduct spraying, XAG’s coupling of AI and drone technologies can decrease farmers’ expenses on defoliants, help to decrease the use of chemicals on the final products, and minimize the impact of such farming on the soil, all through precision spraying.

Yet the advantages of AI technologies are not limited to simply reducing the use of chemicals. By comparing new satellite images with images of the same parcel of land over the past 5 years, an AI algorithm helped a Texas farmer to predict an oncoming swarm of grasshoppers, and effectively protect his field of corn. In so doing, the farmer avoided the huge costs associated with such pests. Companies like NatureFresh Farms also use AI algorithms and sensors to continuously monitor their tomatoes throughout their growth processes, allowing them to produce perfectly ripened tomatoes. Through adjustments to the amount of light the tomatoes are exposed to, every tomato is brought to perfect maturation. Greenhouses like those used to grow these tomatoes are just a glimpse into the potential future of food production.

Through technology, specifically AI, farmers are more appropriately equipped to tackle the huge challenges of a growing global population and world hunger. Not only can AI benefit virtually everyone from farmers and agrochemical producers to consumers, it is constantly evolving and learning, increasing its precision and efficiency over time. Simply put, AI, along with all its potential uses, must become one of our most viable tools if we are to confront our world’s most pressing and crucial agricultural and nutritional challenges.

Written by Paul Luu Van Lang, Edited by Matthew Durborow & Alexander Fleiss

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