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PredictiveCharacterizationof ICARDA
GenebankBarleyAccessions singFIGS
andMachineLearning
ZainabAZOUGHa,b,ZakariaKEHELb,AzizaBENOMARa,MostafaBELLAFKIHa
andAhmedAMRIb
aINPT,Rabat,Morocco
bICARDA,Rabat,Morocco
Abstract. The International Center for Agricultural Research in the Dry Areas
(ICARDA)has auniquegermplasmcollectionof barley, amongmanyother crops
that it holds in its genebank. This collection contains landraces and barley wild
relatives andmost of themare georeferenced.Distribution of genetic resources is
a core genebank activity aiming at responding to requests from various users in-
cluding breeders, researchers, farmers, etc. ICARDAhas developed over the last
decade an efficient approach for better targeting adaptive traits called theFocused
Identification ofGermplasmStrategy (FIGS). FIGSapproach links adaptive traits
toenvironments (andassociatedselectionpressures) throughfilteringandmachine
learning and it focuses on accessions that aremost likely to possess trait specific
geneticvariation. In thispaper,wepresentaworkofpredictivecharacterizationon
ICARDAbarleycollectionusing theFIGSapproachand its algorithmscombining
severalmachine learningmethods, and using several characterization traits.Most
of the studied traits have shownahighpredictability.Outcomes from this analysis
are then used tomake a predictive characterization of the entire ICARDAbarley
collectionbyassigningprobabilitiesof each trait to thenon-evaluatedaccessions.
Keywords.barley, characterization,FIGS,machine learning
1. Introduction
Genebanksworldwidehold collections of plant genetic resources for long-termconser-
vation andmaintain crop diversity for current and future use by crop improvement re-
search,directuseand training.Mostofgenebanksare facingmajorproblemsofsizeand
organization. Some collections have grown so largemaking theirmain activitieswhich
aretheconservationandtheuseofthegeneticdiversitychallenging.Anotherchallenging
aspectofplantgeneticresourcesconservationis the lackof informationaboutaccessions
specificallyapreciseevaluation information.This ismainlydue to thechallengeofeval-
uationtheentirecollectionofagenebank.However, severalgenebankshavedoneagreat
jobonmaintainingandcuratingpassport information.Butpassport datadoesnothelpa
user of the genebank to discernwhich accession in a database is potentially containing
the trait of interest. The concept of core andmini-core collections have been proposed
as a strategy that allows theuseof small portionof agermplasmcollection to represent
U
Intelligent Environments 2019
A. Muñoz et al. (Eds.)
© 2019 The authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms
of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
doi:10.3233/AISE190031 121
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Title
- Intelligent Environments 2019
- Subtitle
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Authors
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-Cía
- Publisher
- IOS Press BV
- Date
- 2019
- Language
- German
- License
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Size
- 16.0 x 24.0 cm
- Pages
- 416
- Category
- Tagungsbände