'Precision agriculture' where farmers respond in real time to changes in crop growth using nanotechnology and artificial intelligence (AI) could offer a practical solution to the challenges threatening global food security, a new study reveals.
Climate change, increasing populations, competing demands on land for production of biofuels and declining soil quality mean it is becoming increasingly difficult to feed the world's populations.
The United Nations (UN) estimates that 840 million people will be affected by hunger by 2030, but researchers have developed a roadmap combining smart and nano-enabled agriculture with AI and machine learning capabilities that could help to reduce this number.
Publishing their findings today in Nature Plants, an international team of researchers led by the University of Birmingham sets out the following steps needed to use AI to harness the power of nanomaterials safely, sustainably and responsibly:
- Understand the long-term fate of nanomaterials in agricultural environments—how nanomaterials can interact with roots, leaves and soil;
- Assess the long-term life cycle impact of nanomaterials in the agricultural ecosystem such as how how repeated application of nanomaterials will affect soils;
- Take a systems-level approach to nano-enabled agriculture—use existing data on soil quality, crop yield and nutrient-use efficiency (NUE) to predict how nanomaterials will behave in the environment; and
- Use AI and machine learning to identify key properties that will control the behavior of nanomaterials in agricultural settings.
Study co-author Iseult Lynch, Professor of Environmental Nanosciences at the University of Birmingham, commented: "Current estimates show nearly 690 million people are hungry—almost nine percent of the planet's population. Finding sustainable agricultural solutions to this problem requires us to take bold new approaches and integrate knowledge from diverse fields, such as materials science and informatics.
"Precision agriculture, using nanotechnology and artificial intelligence, offers exciting opportunities for sustainable food production. We can link existing models for nutrient cycling and crop productivity with nanoinformatics approaches to help both crops and soil perform better—safely, sustainably and responsibly."
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