Diversity of Maize Kernels from a Breeding Program for Protein Quality: I. Physical, Biochemical, Nutrient, and Color Traits

It is a challenge to breed maize (Zea mays L.) varieties with enhanced levels of protein, oil, starch, and essential amino acid contents while maintaining competitive agronomic capability. We used multivariate statistical procedures to quantify total diversity and its components for 31 physical, biochemical, nutrient, and color traits of 1348 accessions from 13 maize populations. The germplasm belonged to stiff and non-stiff stalk heterotic groups at different stages of inbreeding and with opaque or translucent kernel endosperm. Cluster, principal components, and variance components analyses resulted in separating populations and traits into statistically different groups and helped to identify physical and color traits that may be useful for selecting accessions with high protein, amino acid, oil, and nutrient contents. We identified correlative relationships between groups of biochemical and nutrient traits linked to certain populations or physical or kernel color traits. Diversity analysis revealed variable relationships between and within total diversity and its components depending on kernel physical, biochemical, nutrient, and color traits. Sources of variation in and amount of variation attributed to total diversity for each of these traits were identified and quantified. populations and genotypes within populations were identified as sources of variation for multiple kernel quality traits that can be used in developing high-quality maize varieties. A.A. Jaradat, USDA-Agricultural Research Service, 803 Iowa Ave., Morris MN 56267; W. Goldstein, Mandaamin Institute, W2331 Kniep Road, Elkhorn WI 53121. Received 21 July 2012.*Corresponding author ([email protected]; [email protected]). Abbreviations: a*, redness–greenness; ANN, artificial neural network; b*, yellowness–blueness; BSSS, Iowa Stiff Stalk Synthetic; GEM, Germplasm Enhancement of Maize; Gst, population differentiation; Hs, diversity within populations; Ht, total diversity; ISU, Iowa State University; L*, darkness–lightness; MFAI, Michael Fields Agricultural Institute, NG, Nokomis Gold; NIRS, near-infrared spectroscopy; PC, principal component; PCA, principal components analysis; PLS, partial least squares, Q2, validation coefficient of determination; UPGMA, unweighted pair group method with arithmetic average. Published in Crop Sci. 53:956–976 (2013). doi: 10.2135/cropsci2012.07.0437 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.