Root ideotype influences nitrogen transport and assimilation in maize
Maize (Zea mays L.) yield is strongly influenced by external nitrogen inputs and their availability in the soil solution. Overuse of nitrogen-fertilizers can have detrimental ecological consequences through increased nitrogen pollution of water and the release of the potent greenhouse gas, nitrous oxide. To improve yield and overall nitrogen use efficiency (NUE), a deeper understanding of nitrogen uptake and utilization is required. This study examines the performance of two contrasting maize inbred lines, B73 and F44. F44 was selected in Florida on predominantly sandy acidic soils subject to nitrate leaching while B73 was selected in Iowa on rich mollisol soils. Transcriptional, enzymatic and nitrogen transport analytical tools were used to identify differences in their N absorption and utilization capabilities. Our results show that B73 and F44 differ significantly in their genetic, enzymatic, and biochemical root nitrogen transport and assimilatory pathways. The phenotypes show a strong genetic relationship linked to nitrogen form, where B73 showed a greater capacity for ammonium transport and assimilation whereas F44 preferred nitrate. The contrasting phenotypes are typified by differences in root system architecture (RSA) developed in the presence of both nitrate and ammonium. F44 crown roots were longer, had a higher surface area and volume with a greater lateral root number and density than B73. In contrast, B73 roots (primary, seminal, and crown) were more abundant but lacked the defining features of the F44 crown roots. An F1 hybrid between B73 and F44 mirrored the B73 nitrogen specificity and root architecture phenotypes, indicating complete dominance of the B73 inbred. This study highlights the important link between RSA and nitrogen management and why both variables need to be tested together when defining NUE improvements in any selection program.
Main Authors: | , , , , , |
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Format: | Article biblioteca |
Language: | English |
Published: |
Frontiers
2018
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Subjects: | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Transport, Root System Architecture, MAIZE, NITROGEN FERTILIZERS, GREENHOUSE GASES, PHENOTYPIC VARIATION, GENE EXPRESSION, |
Online Access: | https://hdl.handle.net/10883/19520 |
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Summary: | Maize (Zea mays L.) yield is strongly influenced by external nitrogen inputs and their availability in the soil solution. Overuse of nitrogen-fertilizers can have detrimental ecological consequences through increased nitrogen pollution of water and the release of the potent greenhouse gas, nitrous oxide. To improve yield and overall nitrogen use efficiency (NUE), a deeper understanding of nitrogen uptake and utilization is required. This study examines the performance of two contrasting maize inbred lines, B73 and F44. F44 was selected in Florida on predominantly sandy acidic soils subject to nitrate leaching while B73 was selected in Iowa on rich mollisol soils. Transcriptional, enzymatic and nitrogen transport analytical tools were used to identify differences in their N absorption and utilization capabilities. Our results show that B73 and F44 differ significantly in their genetic, enzymatic, and biochemical root nitrogen transport and assimilatory pathways. The phenotypes show a strong genetic relationship linked to nitrogen form, where B73 showed a greater capacity for ammonium transport and assimilation whereas F44 preferred nitrate. The contrasting phenotypes are typified by differences in root system architecture (RSA) developed in the presence of both nitrate and ammonium. F44 crown roots were longer, had a higher surface area and volume with a greater lateral root number and density than B73. In contrast, B73 roots (primary, seminal, and crown) were more abundant but lacked the defining features of the F44 crown roots. An F1 hybrid between B73 and F44 mirrored the B73 nitrogen specificity and root architecture phenotypes, indicating complete dominance of the B73 inbred. This study highlights the important link between RSA and nitrogen management and why both variables need to be tested together when defining NUE improvements in any selection program. |
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