Accelerating climate resilient plant breeding by applying next-generation artificial intelligence

Autor: Joost J. B. Keurentjes, Menachem Moshelion, Arie Altman, Gerald A. Tuskan, Antoine Harfouche, Jonathon Romero, Antoine H. Harfouche, Daniel Jacobson, David Kainer, Giuseppe Scarascia Mugnozza
Jazyk: angličtina
Rok vydání: 2019
Předmět:
0301 basic medicine
Crops
Agricultural
Genotype
Computer science
media_common.quotation_subject
Climate
Climate Change
Big data
Bioengineering
Genomics
02 engineering and technology
Laboratorium voor Erfelijkheidsleer
Adaptability
Ecosystem services
explainable AI
Smart farming
03 medical and health sciences
smart farming
Phenomics
Artificial Intelligence
genomics
Humans
Field phenomics
Plant breeding
Biomass
Augmented breeding
Ecosystem
media_common
Food security
business.industry
field phenomics
021001 nanoscience & nanotechnology
Plant Breeding
augmented breeding
030104 developmental biology
Phenotype
Explainable AI
Laboratory of Genetics
Artificial intelligence
Next-generation artificial intelligence
Genotype to phenotype
EPS
0210 nano-technology
business
next-generation artificial intelligence
Biotechnology
Zdroj: Trends in Biotechnology 37 (2019) 11
Trends in Biotechnology, 37(11), 1217-1235
ISSN: 0167-7799
Popis: This is the accepted manuscript of the paper "Accelerating climate resilient plant breeding by applying next-generation artificial intelligence", published as final paper in "Trends in Biotechnology Volume 37, Issue 11, 01 November 2019, Pages 1217–1235 https://doi.org/10.1016/j.tibtech.2019.05.007”. 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.
Databáze: OpenAIRE
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