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Article

Compositional Analyses Reveal Relationships among Components of Blue Maize Grains

1
Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM 88003-8003, USA
2
Center of Plant Systems Biology and Biotechnology (CPSBB), 4000 Plovdiv, Bulgaria
3
USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
*
Author to whom correspondence should be addressed.
Plants 2020, 9(12), 1775; https://doi.org/10.3390/plants9121775
Received: 6 November 2020 / Revised: 9 December 2020 / Accepted: 11 December 2020 / Published: 14 December 2020
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. View Full-Text
Keywords: blue maize; NIR calibration; NIR predictions; heirloom pigmented maize; grain compositional traits; chemometric models; reference analysis blue maize; NIR calibration; NIR predictions; heirloom pigmented maize; grain compositional traits; chemometric models; reference analysis
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MDPI and ACS Style

Nankar, A.N.; Scott, M.P.; Pratt, R.C. Compositional Analyses Reveal Relationships among Components of Blue Maize Grains. Plants 2020, 9, 1775. https://doi.org/10.3390/plants9121775

AMA Style

Nankar AN, Scott MP, Pratt RC. Compositional Analyses Reveal Relationships among Components of Blue Maize Grains. Plants. 2020; 9(12):1775. https://doi.org/10.3390/plants9121775

Chicago/Turabian Style

Nankar, Amol N., M P. Scott, and Richard C. Pratt. 2020. "Compositional Analyses Reveal Relationships among Components of Blue Maize Grains" Plants 9, no. 12: 1775. https://doi.org/10.3390/plants9121775

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