文章基本信息

标题：Machine learning in plant science and plant breeding
本地全文：下载
作者：Aalt Dirk Jan van Dijk ; Gert Kootstra ; Willem Kruijer 等
期刊名称：iScience
印刷版ISSN：2589-0042
出版年度：2021
卷号：24
期号：1
页码：1-12
DOI：10.1016/j.isci.2020.101890
语种：English
出版社：Elsevier
摘要：SummaryTechnological developments have revolutionized measurements on plant genotypes and phenotypes, leading to routine production of large, complex data sets. This has led to increased efforts to extract meaning from these measurements and to integrate various data sets. Concurrently, machine learning has rapidly evolved and is now widely applied in science in general and in plant genotyping and phenotyping in particular. Here, we review the application of machine learning in the context of plant science and plant breeding. We focus on analyses at different phenotype levels, from biochemical to yield, and in connecting genotypes to these. In this way, we illustrate how machine learning offers a suite of methods that enable researchers to find meaningful patterns in relevant plant data.Plant Biotechnology; Plant Bioinformatics; Artificial Intelligence