Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/48284
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dc.contributor.authorStreich, Jaredit
dc.contributor.authorRomero, Jonathonit
dc.contributor.authorGazolla, João Gabriel Felipe Machadoit
dc.contributor.authorKainer, Davidit
dc.contributor.authorCliff, Ashleyit
dc.contributor.authorPrates, Erica Teixeirait
dc.contributor.authorBrown, James Bit
dc.contributor.authorKhoury, Sachait
dc.contributor.authorTuskan, Gerald Ait
dc.contributor.authorGarvin, Michaelit
dc.contributor.authorJacobson, Danielit
dc.contributor.authorHarfouche, Antoineit
dc.date.accessioned2022-07-04T21:01:41Z-
dc.date.available2022-07-04T21:01:41Z-
dc.date.issued2020it
dc.identifier.issn0958-1669it
dc.identifier.urihttp://hdl.handle.net/2067/48284-
dc.description.abstractHuman population growth and accelerated climate change necessitate agricultural improvements using designer crop ideotypes (idealized plants that can grow in niche environments). Diverse and highly skilled research groups must integrate efforts to bridge the gaps needed to achieve international goals toward sustainable agriculture. Given the scale of global agricultural needs and the breadth of multiple types of omics data needed to optimize these efforts, explainable artificial intelligence (AI with a decipherable decision making process that provides a meaningful explanation to humans) and exascale computing (computers that can perform 1018 floating-point operations per second, or exaflops) are crucial. Accurate phenotyping and daily-resolution climatype associations are equally important for refining ideotype production to specific environments at various levels of granularity. We review advances toward tackling technological hurdles to solve multiple United Nations Sustainable Development Goals and discuss a vision to overcome gaps between research and policy.it
dc.titleCan exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?it
dc.typearticle*
dc.identifier.doi10.1016/j.copbio.2020.01.010it
dc.identifier.pmid32086132it
dc.identifier.scopus2-s2.0-85079546842it
dc.identifier.urlhttps://dspace.unitus.it/handle/2067/44015it
dc.relation.journalCURRENT OPINION IN BIOTECHNOLOGYit
dc.relation.firstpage217-225it
dc.relation.lastpage225it
dc.relation.volume61it
dc.type.miur262*
item.openairetypearticle-
item.grantfulltextrestricted-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.journal.journalissn0958-1669-
crisitem.journal.anceE046620-
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