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Updated: Jun 16, 2026

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (Zea mays L.)
Published on: June 16, 2018
Impact of genetics and environment on the metabolite composition of maize grain
Kirsten Skogerson1, George G Harrigan, Tracey L Reynolds
1Product Safety Center, St. Louis, Missouri 63167, USA.
Abstract:
This study sought to assess genetic and environmental impacts on the metabolite composition of maize grain. Gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) measured 119 identified metabolites including free amino acids, free fatty acids, sugars, organic acids, and other small molecules in a range of hybrids derived from 48 inbred lines crossed against two different tester lines (from the C103 and Iodent heterotic groups) and grown at three locations in Iowa. It was reasoned that expanded metabolite coverage would contribute to a comprehensive evaluation of the grain metabolome, its degree of variability, and, in principle, its relationship to other compositional and agronomic features. The metabolic profiling results established that the small molecule metabolite pool is highly dependent on genotypic variation and that levels of certain metabolite classes may have an inverse genotypic relationship to each other. Different metabolic phenotypes were clearly associated with the two distinct tester populations. Overall, grain from the C103 lines contained higher levels of free fatty acids and organic acids, whereas grain from the Iodent lines were associated with higher levels of amino acids and carbohydrates. In addition, the fold-range of genotype mean values [composed of six samples each (two tester crosses per inbred x three field sites)] for identified metabolites ranged from approximately 1.5- to 93-fold. Interestingly, some grain metabolites showed a non-normal distribution over the entire corn population, which could, at least in part, be attributed to large differences in metabolite values within specific inbred crosses relative to other inbred sets. This study suggests a potential role for metabolic profiling in assisting the process of selecting elite germplasm in biotechnology development, or marker-assisted breeding.
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