数字农科院2.0

Satellite-enabled enviromics to enhance crop improvement

文献类型： 外文期刊

作者： Rafael T. Resende;Lee Hickey;Cibele H. Amaral;Lucas L. Peixoto;Gustavo E. Marcatti;Yunbi Xu

作者机构：

关键词： enviromic information;envirotyping;genotype–environment interactions;precision breeding;predictive models;remote sensing

期刊名称： Molecular Plant

ISSN： 1674-2052

年卷期： 2024 年 17 卷 6 期

页码：

收录情况： SCIE（2024版） ; ; CSCD（2023-2024年度） ; ; 科技核心（2024版）

摘要： Enviromics refers to the characterization of micro- and macroenvironments based on large-scale environmental datasets. By providing genotypic recommendations with predictive extrapolation at a site-specific level, enviromics could inform plant breeding decisions across varying conditions and anticipate productivity in a changing climate. Enviromics-based integration of statistics, envirotyping (i.e., determining environmental factors), and remote sensing could help unravel the complex interplay of genetics, environment, and management. To support this goal, exhaustive envirotyping to generate precise environmental profiles would significantly improve predictions of genotype performance and genetic gain in crops. Already, informatics management platforms aggregate diverse environmental datasets obtained using optical, thermal, radar, and light detection and ranging (LiDAR)sensors that capture detailed information about vegetation, surface structure, and terrain. This wealth of information, coupled with freely available climate data, fuels innovative enviromics research. While enviromics holds immense potential for breeding, a few obstacles remain, such as the need for (1) integrative methodologies to systematically collect field data to scale and expand observations across the landscape with satellite data; (2) state-of-the-art AI models for data integration, simulation, and prediction; (3) cyberinfrastructure for processing big data across scales and providing seamless interfaces to deliver forecasts to stakeholders; and (4) collaboration and data sharing among farmers, breeders, physiologists, geoinformatics experts, and programmers across research institutions. Overcoming these challenges is essential for leveraging the full potential of big data captured by satellites to transform 21st century agriculture and crop improvement through enviromics.

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