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ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #337557

Title: Diversity of maize kernels from a breeding program for protein quality III: Ionome profiling

item Jaradat, Abdullah
item GOLDSTEIN, WALTER - Mandaamin Institute

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/14/2018
Publication Date: 1/23/2018
Publication URL:
Citation: Jaradat, A.A., Goldstein, W. 2018. Diversity of maize kernels from a breeding program for protein quality III: Ionome profiling. Agronomy.

Interpretive Summary: Consumers are generating more demand for grain crops with better nutritional quality. We surveyed a large corn collection and selected those with larger essential nutrients than what is normally found in commercial corn. A selection procedure was developed to identify corn with larger quality and was based on differences in seed color. We provided a method, data and interpretation of factors affecting individual nutrients and groups of nutrients and their relationships to seed composition. This method provides a practical and inexpensive initial selection step for nutrients and can be used to develop high quality corn with balanced nutritional value. The selected varieties can be part of a durable solution for nutrient deficiency in corn. Analytical methods used in the study are of value to students and instructors; the new varieties are a valuable source for farmers who are interested in growing corn with better quality.

Technical Abstract: Densities of single and multiple macro- and micronutrients have been estimated in mature kernels of 1,348 accessions in 13 maize genotypes. The germplasm belonged to stiff stalk (SS) and non-stiff stalk (NS) heterotic groups (HG) with one (S1) to four (S4) years of inbreeding (IB), or open pollination (OP); and with opaque (O) or translucent (T) endosperm (E). Indices were calculated for macronutrients (M-Index), micronutrients (m-Index) and an index based on combined Fe and Zn densities (FeZn-Index). The objectives were to (1) build predictive models and quantify multivariate relationships between single and multiple nutrients with physical and biochemical constituents of the maize kernel; (2) quantify the effects of IB stages and E textures, in relation to carbon and nitrogen allocation, on nutrients and their indices, and (3) develop and test the utility of hierarchical multi-way classification of nutrients with kernel color space coordinates. Differences among genotypes and among IB stages accounted for the largest amount of variation in most nutrients and in all Indices; while genotypic response to IB within HGs explained 52.4, 55.9 and 76.0% of variation in M-Index, m-Index, and FeZn-Index, respectively. Differences in C and N allocation among HGs explained more variation in all indices than respective differences in allocation among E textures; while variation decreased with sequential inbreeding compared to OP germplasm. Specific color space coordinates of color space coordinates indicated either large macronutrient densities and M-Index; or large micronutrient densities, m-Index and FeZn-Index. These results demonstrated the importance of genotypes and C:N ratio in nutrient allocation, and bivariate and multiple interrelationships.