Principal variable selection to explain grain yield variation in winter wheat from features extracte...
Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery
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Publisher
England: BioMed Central Ltd
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Language
English
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Publisher
England: BioMed Central Ltd
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Contents
Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phen...
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Full title
Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery
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TN_cdi_doaj_primary_oai_doaj_org_article_cf3d94e3cb8c4a678fd39f0ded70b30f
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cf3d94e3cb8c4a678fd39f0ded70b30f
Other Identifiers
ISSN
1746-4811
E-ISSN
1746-4811
DOI
10.1186/s13007-019-0508-7
