Bluster or Lustre: Can AI Improve Crops and Plant Health?

In a changing climate where future food security is a growing concern, researchers are exploring new methods and technologies in the effort to meet ambitious crop yield targets. The application of Artificial Intelligence (AI) including Machine Learning (ML) methods in this area has been proposed as...

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Bibliographic Details
Published in:	Plants (Basel) 2021-12, Vol.10 (12), p.2707
Main Authors:	Gardiner, Laura-Jayne, Krishna, Ritesh
Format:	Article
Language:	eng
Subjects:	Agricultural production Algorithms Artificial intelligence Automation Climate change Corn Crop diseases Crop yield Crops Datasets Deep learning disruptive technologies Drought Food security Genotype & phenotype Learning algorithms Machine learning Neural networks omics plant HEALTH Plant sciences Review Unmanned aerial vehicles
Online Access:	Get full text
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Summary:	In a changing climate where future food security is a growing concern, researchers are exploring new methods and technologies in the effort to meet ambitious crop yield targets. The application of Artificial Intelligence (AI) including Machine Learning (ML) methods in this area has been proposed as a potential mechanism to support this. This review explores current research in the area to convey the state-of-the-art as to how AI/ML have been used to advance research, gain insights, and generally enable progress in this area. We address the question-Can AI improve crops and plant health? We further discriminate the bluster from the lustre by identifying the key challenges that AI has been shown to address, balanced with the potential issues with its usage, and the key requisites for its success. Overall, we hope to raise awareness and, as a result, promote usage, of AI related approaches where they can have appropriate impact to improve practices in agricultural and plant sciences.
ISSN:	2223-7747 2223-7747