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Breeding effects on canopy light attenuation in maize: a retrospective and prospective analysis

Journal

JOURNAL OF EXPERIMENTAL BOTANY
Volume 73, Issue 5, Pages 1301-1311

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/jxb/erab503

Keywords

Breeding; canopy design; corn; light extinction coefficient; light interception; nitrogen distribution; photosynthesis; radiation; yield gains; Zea mays L

Categories

Funding

  1. Kansas Corn Commission
  2. ANPCyT of Argentina [PICT 2015/2671, PICT 2016/1504]

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The breeding process unintentionally led to changes in the vertical leaf nitrogen distribution of erectophile maize hybrids across different producing regions. The potential for modifications in canopy architecture is discussed.
The breeding process selected erectophile maize hybrids across contrasting producing regions, suggesting unintentional concomitant changes of vertical leaf nitrogen distribution. Prospects for potential modifications in canopy architecture are discussed. The light attenuation process within a plant canopy defines energy capture and vertical distribution of light and nitrogen (N). The vertical light distribution can be quantitatively described with the extinction coefficient (k), which associates the fraction of intercepted photosynthetically active radiation (fPARi) with the leaf area index (LAI). Lower values of k correspond to upright leaves and homogeneous vertical light distribution, increasing radiation use efficiency (RUE). Yield gains in maize (Zea mays L.) were accompanied by increases in optimum plant density and leaf erectness. Thus, the yield-driven breeding programs and management changes, such as reduced row spacing, selected a more erect leaf habit under different maize production systems (e.g., China and the USA). In this study, data from Argentina revealed that k decreased at a rate of 1.1% year(-1) since 1989, regardless of plant density and in agreement with Chinese reports (1.0% year(-1) since 1981). A reliable assessment of changes in k over time is critical for predicting (i) modifications in resource use efficiency (e.g. radiation, water, and N), improving estimations derived from crop simulation models; (ii) differences in productivity caused by management practices; and (iii) limitations to further exploit this trait with breeding.

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