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. 2011 Jul;156(3):1190-201.
doi: 10.1104/pp.111.175489. Epub 2011 May 31.

Root cortical aerenchyma enhances the growth of maize on soils with suboptimal availability of nitrogen, phosphorus, and potassium

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Root cortical aerenchyma enhances the growth of maize on soils with suboptimal availability of nitrogen, phosphorus, and potassium

Johannes Auke Postma et al. Plant Physiol. 2011 Jul.

Abstract

Root cortical aerenchyma (RCA) is induced by hypoxia, drought, and several nutrient deficiencies. Previous research showed that RCA formation reduces the respiration and nutrient content of root tissue. We used SimRoot, a functional-structural model, to provide quantitative support for the hypothesis that RCA formation is a useful adaptation to suboptimal availability of phosphorus, nitrogen, and potassium by reducing the metabolic costs of soil exploration in maize (Zea mays). RCA increased the growth of simulated 40-d-old maize plants up to 55%, 54%, or 72% on low nitrogen, phosphorus, or potassium soil, respectively, and reduced critical fertility levels by 13%, 12%, or 7%, respectively. The greater utility of RCA on low-potassium soils is associated with the fact that root growth in potassium-deficient plants was more carbon limited than in phosphorus- and nitrogen-deficient plants. In contrast to potassium-deficient plants, phosphorus- and nitrogen-deficient plants allocate more carbon to the root system as the deficiency develops. The utility of RCA also depended on other root phenes and environmental factors. On low-phosphorus soils (7.5 μM), the utility of RCA was 2.9 times greater in plants with increased lateral branching density than in plants with normal branching. On low-nitrate soils, the utility of RCA formation was 56% greater in coarser soils with high nitrate leaching. Large genetic variation in RCA formation and the utility of RCA for a range of stresses position RCA as an interesting crop-breeding target for enhanced soil resource acquisition.

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Figures

Figure 1.
Figure 1.
The utility of RCA formation under different nutrient deficiencies. On the x axis, stress due to nutrient deficiency is expressed as the relative plant biomass at 40 d after germination compared with nonstressed plants. The RCA utility on the y axis is expressed as growth increase due to RCA formation (note the different scales). The top panel shows the overall benefit of RCA, and the following panels show the benefit of RCA due to reallocation of nutrients and the benefit of RCA due to reduction in respiration. Each data point is an average of two repetitions. d.w., Dry weight.
Figure 2.
Figure 2.
The utility of RCA formation in roots when RCA only forms in the axial roots (laterals without RCA) or when RCA forms in all roots (laterals with RCA). The utility of RCA formation is given in percentage increase in plant dry weight (d.w.) at 40 d after germination relative to the dry weights of plants simulated without RCA given in the bottom right panel. Panels show utility on low-nitrogen, low-phosphorus, and low-potassium soils. Nitrogen, phosphorus, and potassium availability was such that yield reduction in plants without RCA was approximately 92%, corresponding to the typical yield reduction of small-scale subsistence farmers. Error bars present se for eight repeated runs. Variation is caused by simulated stochasticity in root growth rates, growth directions, and branching frequency.
Figure 3.
Figure 3.
Spatial map of RCA formation in simulated root systems at 40 d after germination. Colors show RCA formation as percentage of root cross-sectional area. The color range differed for the max RCA reference root system, which was rendered on a 0% to 40% scale instead of a 0% to 15% scale. See text for detailed description of the differences among these genotypes, which include variation in the steepness and number of major axes, lateral branching density, lateral root length, and RCA formation. Roots have been dilated (approximately two times) for better visibility and thus do not show true root thickness.
Figure 4.
Figure 4.
Comparison of the utility of RCA for different genotypes. See Figure 2 for description of the panels and error bars. Utility of RCA is much less than in Figure 2, as RCA formation in these genotypes was much less (Fig. 3). d.w., Dry weight.
Figure 5.
Figure 5.
Utility of RCA formation as affected by lateral root proliferation under nitrogen and phosphorus deficiency. Three levels of lateral root proliferation are shown: half, normal, and double, which correspond to 4, 8, and 16 lateral roots cm−1. This range represents the genotypic variation in lateral branching density measured by Trachsel et al. (2010). Low and medium nitrate availability correspond to residual nitrate in the top 60 cm (after fertilization), and low and medium phosphorus availability correspond to 5 and 7.5 μm in the buffered soil solution. d.w., Dry weight.
Figure 6.
Figure 6.
Nitrate leaching in a silt-loam and a loamy-sand soil given three different precipitation intensities. The total precipitation in mm over 40 d of growth is listed. The “0-d” gray line shows the nitrate profile at the start of growth, which had 21 kg ha−1 residual nitrogen in the top 60 cm. Data are from simulations of the maximum RCA reference genotype (Fig. 3).
Figure 7.
Figure 7.
Utility of RCA formation over 40 d of growth on a silt-loam and a loamy-sand soil under different precipitation regimes. There was 21 kg ha−1 residual nitrogen in the top 60 cm (Fig. 6.) The simulated genotype was the maximum RCA reference genotype (Fig. 3). See Figure 2 for error bars. d.w., Dry weight.
Figure 8.
Figure 8.
Utility of RCA in two different soils relative to the stress experienced due to nutrient deficiency. Axes are as in Figure 1. d.w., Dry weight.
Figure 9.
Figure 9.
Growth reduction (percentage plant dry weight [d.w.]) in 40-d-old maize plants due to root maintenance respiration. Simulations of the reference genotype with (w) and without (o) maintenance respiration were compared using the equation 100 × (ow)/o. Plants did not form RCA. The x axis is as in Figure 1.
Figure 10.
Figure 10.
Side view of a simulated maize root system and its mirror image. The image shows how the model simulates a realistic root density by mirroring the roots back into the column.

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