物候学
适应性
基因组学
生物技术
计算机科学
粮食安全
数据科学
生化工程
人工智能
生物
工程类
生态学
农业
基因组
生物化学
基因
作者
Antoine Harfouche,Daniel Jacobson,David Kainer,Jonathon Romero,Antoine Harfouche,Giuseppe Scarascia Mugnozza,Menachem Moshelion,Gerald A. Tuskan,Joost J. B. Keurentjes,Arie Altman
标识
DOI:10.1016/j.tibtech.2019.05.007
摘要
Breeding crops for high yield and superior adaptability to new and variable climates is imperative to ensure continued food security, biomass production, and ecosystem services. Advances in genomics and phenomics are delivering insights into the complex biological mechanisms that underlie plant functions in response to environmental perturbations. However, linking genotype to phenotype remains a huge challenge and is hampering the optimal application of high-throughput genomics and phenomics to advanced breeding. Critical to success is the need to assimilate large amounts of data into biologically meaningful interpretations. Here, we present the current state of genomics and field phenomics, explore emerging approaches and challenges for multiomics big data integration by means of next-generation (Next-Gen) artificial intelligence (AI), and propose a workable path to improvement.
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