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.

为了确保持续的粮食安全，生物量生产和生态系统服务，必须培育高产和对新的多变气候具有出色适应性的农作物。基因组学和表型组学的研究进展为深入了解构成植物功能以应对环境扰动的复杂生物学机制提供了见识。然而，将基因型与表型联系起来仍然是一个巨大的挑战，并且阻碍了高通量基因组学和表型组学在先进育种中的最佳应用。成功的关键是需要将大量数据同化为具有生物学意义的解释。在这里，我们介绍了基因组学和现场组学的当前状态，探讨了通过下一代（Next-Gen）人工智能（AI）进行多组学大数据集成的新兴方法和挑战，