A primer on artificial intelligence in plant digital phenomics: embarking on the data to insights journey
Author(s)
Date Issued
2023
Type
article
Volume
28
Issue
2
Start Page
154
End Page
184
Journal
Abstract
Artificial intelligence (AI) has emerged as a fundamental component of global agricultural research that is poised to impact on many aspects of plant science. In digital phenomics, AI is capable of learning intricate structure and patterns in large datasets. We provide a perspective and primer on AI applications to phenome research. We propose a novel human-centric explainable AI (X-AI) system architecture consisting of data architecture, technology infrastructure, and AI architecture design. We clarify the difference between post hoc models and 'interpretable by design' models. We include guidance for effectively using an interpretable by design model in phenomic analysis. We also provide directions to sources of tools and resources for making data analytics increasingly accessible. This primer is accompanied by an interactive online tutorial.
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Name
Trends_Plant_Science_2022_Harfouche.pdf
Size
4.9 MB
Format
Adobe PDF
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