Compositional Analyses Reveal Relationships among Components of Blue Maize Grains

dc.contributor.author Nankar, Amol
dc.contributor.author Scott, M. Paul
dc.contributor.author Scott, Marvin
dc.contributor.author Pratt, Richard
dc.contributor.department Agronomy
dc.date 2021-01-04T17:10:03.000
dc.date.accessioned 2021-02-24T19:25:40Z
dc.date.available 2021-02-24T19:25:40Z
dc.date.issued 2020-12-14
dc.description.abstract <p>One aim of this experiment was to develop NIR calibrations for 20-grain components in 143 pigmented maize samples evaluated in four locations across New Mexico during 2013 and 2014. Based on reference analysis, prediction models were developed using principal component regression (PCR) and partial least squares (PLS). The predictive ability of calibrations was generally low, with the calibrations for methionine and glycine performing best by PCR and PLS. The second aim was to explore the relationships among grain constituents. In PCA, the first three PCs explained 49.62, 22.20, and 6.92% of the total variance and tend to align with nitrogen-containing compounds (amino acids), carbon-rich compounds (starch, anthocyanin, fiber, and fat), and sulfur-containing compounds (cysteine and methionine), respectively. Correlations among traits were identified, and these relationships were illustrated by a correlation network. Some relationships among components were driven by common synthetic origins, for example, among amino acids derived from pyruvate. Similarly, anthocyanins, crude fat, and fatty acids all share malonyl CoA in their biosynthetic pathways and were correlated. In contrast, crude fiber and starch have similar biosynthetic origins but were negatively correlated, and this may have been due to their different functional roles in structure and energy storage, respectively.</p>
dc.description.comments <p>This article is published as Nankar, Amol N., M. Paul Scott, and Richard C. Pratt. "Compositional Analyses Reveal Relationships among Components of Blue Maize Grains." <em>Plants</em> 9, no. 12 (2020): 1775. doi: <a href="https://doi.org/10.3390/plants9121775">10.3390/plants9121775</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/agron_pubs/692/
dc.identifier.articleid 1740
dc.identifier.contextkey 20926804
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath agron_pubs/692
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/93091
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/agron_pubs/692/2020_Scott_CompositionalAnalyses.pdf|||Sat Jan 15 01:30:56 UTC 2022
dc.source.uri 10.3390/plants9121775
dc.subject.disciplines Agriculture
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Plant Breeding and Genetics
dc.subject.keywords blue maize
dc.subject.keywords NIR calibration
dc.subject.keywords NIR predictions
dc.subject.keywords heirloom pigmented maize
dc.subject.keywords grain compositional traits
dc.subject.keywords chemometric models
dc.subject.keywords reference analysis
dc.title Compositional Analyses Reveal Relationships among Components of Blue Maize Grains
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 97acee5f-1291-4c27-8929-a8e1617c411d
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
File
Original bundle
Now showing 1 - 1 of 1
Name:
2020_Scott_CompositionalAnalyses.pdf
Size:
2.22 MB
Format:
Adobe Portable Document Format
Description:
Collections