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A comparison of classical and machine learning-based phenot..:
Maura John
;
Florian Haselbeck
;
Rupashree Dass
...
https://www.frontiersin.org/articles/10.3389/fpls.2022.932512/full. , 2022
Link:
https://doi.org/10.3389/fpls.2022.932512
RT Journal T1 <Title>A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:1989c900845642afbd2043b4c21e4580&Exemplar=1&LAN=DE A1 Maura John A1 Florian Haselbeck A1 Rupashree Dass A1 Christoph Malisi A1 Patrizia Ricca A1 Christian Dreischer A1 Sebastian J. Schultheiss A1 Dominik G. Grimm PB Frontiers Media S.A. YR 2022 K1 phenotype prediction K1 genomic selection K1 plant phenotyping K1 machine learning K1 Arabidopsis thaliana K1 Plant culture K1 SB1-1110 JF https://www.frontiersin.org/articles/10.3389/fpls.2022.932512/full LK http://dx.doi.org/https://doi.org/10.3389/fpls.2022.932512 DO https://doi.org/10.3389/fpls.2022.932512 SF ELIB - SuUB Bremen
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