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Article . 2019
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Trends in Biotechnology
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Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence

Authors: Antoine H. Harfouche; Antoine H. Harfouche; Jonathon Romero; Gerald A. Tuskan; Menachem Moshelion; Antoine Harfouche; Joost J. B. Keurentjes; +5 Authors

Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence

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.

Keywords

Crops, Agricultural, Genotype, Climate, Climate Change, Genomics, field phenomics, explainable AI, augmented breeding, smart farming, Plant Breeding, Phenotype, Artificial Intelligence, genomics, Humans, Biomass, Phenomics, next-generation artificial intelligence, Ecosystem

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visibility
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
213
Top 0.1%
Top 10%
Top 1%
2
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