Ionomic Characterization of Maize Kernels in the Intermated B73 × Mo17 Population

Abstract

Dietary mineral deficiencies affect nearly half of the people on our planet, largely due to poverty. Enhancing nutritional quality—or biofortification—represents an efficient and sustainable potential solution to this massive public health problem. To create biofortified crops, one must understand the genetic and environmental factors that influence the ionome, or collection of mineral nutrients, in the target organism and tissue. We describe the use of quantitative trait loci (QTL) mapping to characterize the maize (Zea mays L.) grain ionome illustrated by the intermated B73 × Mo17 (IBM) recombinant inbred population. Ionomic profiling was applied to field grown materials from Florida, North Carolina, and New York. Twenty‐seven QTL were detected for 10 traits derived from the North Carolina and New York grown maize explaining between 4 and 46% of the variance observed. For biofortification to succeed, QTL effective in multiple environments need to be the targets for improvement efforts. Florida grown maize were sampled shallowly to provide a low cost dataset to evaluate the models based on the combined North Carolina and New York traits. Twenty‐five QTL were detected as significant in two or more locations using ANOVA on the original single location and/or site data; 12 QTL were found to be significant in Florida. While this strategy may have not detected every potential QTL from our data, we suggest these QTL effective in multiple environments represent a starting position for the biofortification of maize grain.