TY - JOUR
T1 - Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
AU - Harfouche, Antoine L.
AU - Jacobson, Daniel A.
AU - Kainer, David
AU - Romero, Jonathon C.
AU - Harfouche, Antoine H.
AU - Scarascia Mugnozza, Giuseppe
AU - Moshelion, Menachem
AU - Tuskan, Gerald A.
AU - Keurentjes, Joost J.B.
AU - Altman, Arie
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
KW - augmented breeding
KW - explainable AI
KW - field phenomics
KW - genomics
KW - next-generation artificial intelligence
KW - smart farming
UR - http://www.scopus.com/inward/record.url?scp=85067510759&partnerID=8YFLogxK
U2 - 10.1016/j.tibtech.2019.05.007
DO - 10.1016/j.tibtech.2019.05.007
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C2 - 31235329
AN - SCOPUS:85067510759
SN - 0167-7799
VL - 37
SP - 1217
EP - 1235
JO - Trends in Biotechnology
JF - Trends in Biotechnology
IS - 11
ER -
