Precision agriculture could offer a practical solution for the challenge against threatening global food security, reveals a new study. By definition, precision agriculture involves nanotechnology and artificial intelligence, wherein farmers respond to changes in crop growth in real-time. In fact, climate change, increasing populations, and competing burden on land for declining soil quality and production of biofuels imply it is becoming increasingly difficult to meet the food demand of the populations of the world.
Meanwhile, according to UN estimates, by 2030, 840 million people will be affected by hunger. However, researchers have developed a roadmap that combines smart and nano-enabled agriculture with machine learning and AI capabilities that could help to reduce the number.
The study carried out by an international team of researchers at the University of Birmingham puts forth a number of steps needed to use AI to harness the power of nanomaterials sustainably, safely, and responsibly.
In the first step, the technique involves understanding the long-term impact of nanomaterials in agricultural environments – the way nanomaterials can interact with leaves, roots, and soil. The second step is to evaluate how nanomaterials cyclically impact in the agricultural ecosystem in the long-term, and the way in which the repeated application of nanomaterials will affect soils. In the next step, it involves taking a system level approach for nano-enabled agriculture based on existing data on soil quality, crop production and nutrient-use efficiency, this is to predict the behavior of nanomaterials in the environment; lastly, employ machine learning and AI to detect key properties that will control the behavior of nanomaterials in agricultural settings.