Genetic and agronomic assessment of cob traits in corn under low and normal nitrogen management conditions

Date
2015-01-01
Authors
Jansen, Constantin
Zhang, Youngzhong
Lubberstedt, Thomas
Liu, Hongjun
Gonzalez-Portilla, Pedro
Lauter, Nick
Kumar, Bharath
Trucillo-Silva, Ignacio
San Martin, Juan Pablo
Lee, Michael
Simcox, Kevin
Schussler, Jeff
Dhugga, Kanwarpal
Lubberstedt, Thomas
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Agronomy
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Agronomy
Abstract

With rising energy demands and costs for fossil fuels, alternative energy from renewable sources such as maize cobs will become competitive. Maize cobs have beneficial characteristics for utilization as feedstock including compact tissue, high cellulose content, and low ash and nitrogen content. Nitrogen is quantitatively the most important nutrient for plant growth. However, the influence of nitrogen fertilization on maize cob production is unclear. In this study, quantitative trait loci (QTL) have been analyzed for cob morphological traits such as cob weight, volume, length, diameter and cob tissue density, and grain yield under normal and low nitrogen regimes. 213 doubled-haploid lines of the intermated B73 × Mo17 (IBM) Syn10 population have been resequenced for 8575 bins, based on SNP markers. A total of 138 QTL were found for six traits across six trials using composite interval mapping with ten cofactors and empirical comparison-wise thresholds (P = 0.001). Despite moderate to high repeatabilities across trials, few QTL were consistent across trials and overall levels of explained phenotypic variance were lower than expected some of the cob trait × trial combinations (R2 = 7.3–43.1 %). Variation for cob traits was less affected by nitrogen conditions than by grain yield. Thus, the economics of cob usage under low nitrogen regimes is promising.

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This article is published as Jansen, Constantin, Yongzhong Zhang, Hongjun Liu, Pedro J. Gonzalez-Portilla, Nick Lauter, Bharath Kumar, Ignacio Trucillo-Silva et al. "Genetic and agronomic assessment of cob traits in corn under low and normal nitrogen management conditions." Theoretical and applied genetics 128, no. 7 (2015): 1231-1242. 10.1007/s00122-015-2486-0. Posted with permission.

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