Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
Copyright © 2019 Elsevier Ltd. All rights reserved..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:37 |
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| Enthalten in: |
Trends in biotechnology - 37(2019), 11 vom: 20. Nov., Seite 1217-1235 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Harfouche, Antoine L [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 02.07.2020 Date Revised 02.07.2020 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.tibtech.2019.05.007 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a 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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| 700 | 1 | |a Scarascia Mugnozza, Giuseppe |e verfasserin |4 aut | |
| 700 | 1 | |a Moshelion, Menachem |e verfasserin |4 aut | |
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| 700 | 1 | |a Keurentjes, Joost J B |e verfasserin |4 aut | |
| 700 | 1 | |a Altman, Arie |e verfasserin |4 aut | |
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