Campus Units

Agronomy

Document Type

Article

Publication Version

Published Version

Publication Date

2020

Journal or Book Title

Plant Breeding

DOI

10.1111/pbr.12857

Abstract

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.

Comments

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." Plant Breeding (2020). doi: 10.1111/pbr.12857.

Rights

Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.

Language

en

File Format

application/pdf

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