Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1217-1235 |
| Number of pages | 19 |
| Journal | Trends in Biotechnology |
| Volume | 37 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- augmented breeding
- explainable AI
- field phenomics
- genomics
- next-generation artificial intelligence
- smart farming
All Science Journal Classification (ASJC) codes
- Biotechnology
- Bioengineering
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