Skip to main content
ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #302940

Title: Statistical modeling of correlatively expressed functional amino acids in maize

item Jaradat, Abdullah
item GOLDSTEIN, WALTER - Mandaamin Institute

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/5/2014
Publication Date: 11/5/2014
Citation: Jaradat, A.A., Goldstein, W. 2014. Statistical modeling of correlatively expressed functional amino acids in maize [abstract]. ASA-CSSA-SSSA Annual Meeting Abstracts. ASA-CSSA-SSSA Annual Meeting. Nov. 2-5, 2014, Long Beach, CA.

Interpretive Summary:

Technical Abstract: Modern maize breeding and selection for large starchy kernels may have contributed to reduced contents of essential amino acids which represents a serious nutritional problem for humans and animals. A large number (1,348) of germplasm accessions belonging to 13 populations and classified into four heterotic groups of stiff stalk and non-stiff stalk, each with opaque or translucent endosperm was produced in a breeding program for maize protein quality. We developed calibration and validation statistical models and discerned the effects of a causal network of simultaneously operating physical, biochemical, nutrient and color components of the maize kernel on the three correlatively expressed essential amino acids lysine, methionine and cysteine. In addition, we identified opaque and translucent families within the 13 maize populations having acceptable kernel hardness, and high and stable contents of all three essential amino acids. The nutritional quality of maize kernels, as measured by contents and relative contents of the three essential amino acids, is influenced by the genetic background of endosperm texture, number of inbreeding generations, phytochemical composition, and their interactions. The exceptionally large amount of variation in amino acid contents and relative contents found between accessions within selfing stages suggested that selection for nutritional quality can be accelerated through inbreeding and recurrent selection. It was possible to discriminate between opaque and translucent endosperms at the population and heterotic group levels on the basis of amino acid contents and it was possible to reduce the loss of lysine during the conversion from opaque to translucent endosperm. The comprehensive structural equation modeling provided new insights into the relative importance of biochemical, physical and kernel color factors determining amino acid contents and will help prioritize future breeding studies of maize nutritional quality.