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Review: Application of Artificial Intelligence in Phenomics
납뷔래쇼나 ( Shona Nabwire ),조병관 ( Byoung-kwan Cho ) 한국농업기계학회 2021 한국농업기계학회 학술발표논문집 Vol.26 No.1
Plant phenomics has been rapidly advancing over the past few years. This is attributed to the increased innovation and availability of new technologies to enable high-throughput phenotyping of complex plant traits. The application of artificial intelligence in various domains of science has grown exponentially in recent years. Traditionally-used techniques for non-destructive plant phenotyping are now integrating artificial intelligence methods into their data management pipelines. This is gradually improving the efficiency of data analysis and has fostered further research into the development and utilization of these methods. Large volumes of plant data are now being collected in real-time at different research facilities depending on the desired research goals. The integration of a range of artificial intelligence approaches like computer vision, machine learning and deep learning at various stages in the entire phenotypic data management pipeline has become increasingly important to seamlessly consolidate plant data. This review provides an overview of current phenotyping technologies and the ongoing integration of artificial intelligence in plant phenotyping.
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