Classification approaches for sorting maize (Zea mays subsp. mays) haploids using single‐kernel near‐infrared spectroscopy

dc.contributor.author Gustin, Jeffery
dc.contributor.author Frei, Ursula
dc.contributor.author Lubberstedt, Thomas
dc.contributor.author Baier, John
dc.contributor.author Armstrong, Paul
dc.contributor.author Lubberstedt, Thomas
dc.contributor.author Settles, A. Mark
dc.contributor.department Agronomy
dc.date 2020-09-03T14:00:03.000
dc.date.accessioned 2021-02-24T19:25:17Z
dc.date.available 2021-02-24T19:25:17Z
dc.date.issued 2020-01-01
dc.description.abstract <p>Doubled haploids (DHs) are an important breeding tool for creating maize inbred lines. One bottleneck in the DH process is the manual separation of haploids from among the much larger pool of hybrid siblings in a haploid induction cross. Here, we demonstrate the ability of single‐kernel near‐infrared reflectance spectroscopy (skNIR) to identify haploid kernels. The skNIR is a high‐throughput device that acquires an NIR spectrum to predict individual kernel traits. We collected skNIR data from haploid and hybrid kernels in 15 haploid induction crosses and found significant differences in multiple traits such as percent oil, seed weight, or volume, within each cross. The two kernel classes were separated by their NIR profile using Partial Least Squares Linear Discriminant Analysis (PLS‐LDA). A general classification model, in which all induction crosses were used in the discrimination model, and a specific model, in which only kernels within a specific induction cross, were compared. Specific models outperformed the general model and were able to enrich a haploid selection pool to above 50% haploids. Applications for the instrument are discussed.</p>
dc.description.comments <p>This article is published as Gustin, Jeffery L., Ursula K. Frei, John Baier, Paul Armstrong, Thomas Lübberstedt, and A. Mark Settles. "Classification approaches for sorting maize (Zea mays subsp. mays) haploids using single‐kernel near‐infrared spectroscopy." <em>Plant Breeding </em>(2020). doi: <a href="https://doi.org/10.1111/pbr.12857">10.1111/pbr.12857</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/agron_pubs/673/
dc.identifier.articleid 1722
dc.identifier.contextkey 19232004
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath agron_pubs/673
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/93072
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/agron_pubs/673/2020_Lubberstedt_ClassificationApproaches.pdf|||Sat Jan 15 01:27:43 UTC 2022
dc.source.uri 10.1111/pbr.12857
dc.subject.disciplines Agricultural Science
dc.subject.disciplines Agriculture
dc.subject.disciplines Plant Breeding and Genetics
dc.subject.keywords doubled haploid
dc.subject.keywords germplasm enhancement of maize
dc.subject.keywords haploid classification
dc.subject.keywords partial least squares regression
dc.subject.keywords R1-nj
dc.subject.keywords single-kernel near-infrared spectroscopy
dc.title Classification approaches for sorting maize (Zea mays subsp. mays) haploids using single‐kernel near‐infrared spectroscopy
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 4e4330cd-db15-4ac5-8924-41119139cf32
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
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