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Correction to: Allometric approach to crop nutrition and implications for crop diagnosis and phenotyping. A review

  • Gilles LemaireEmail author
  • Thomas Sinclair
  • Victor Sadras
  • Gilles Bélanger
Correction
  • 156 Downloads

Correction to: Agronomy for Sustainable Development

  https://doi.org/10.1007/s13593-019-0570-6

Due to a different interpretation of a query about figure numbering during proof stage, figures and captions in above mentioned article got mixed-up in the final version. The publisher and typesetter regret this occurrence and apologize for the inconvenience caused.

In this correction note you will find figures 4 - 8 with correct numbers and captions, as well as the correct version of Box 2.
Box 2

Consequences for assessing N use efficiency by crops

Derivative of Eq. (7) with time allows the expression of the rate of crop N uptake (dNupt/dt) in relation with the crop growth rate (dWsh/dt) and the shoot mass (Wsh):

dNupt/dt = abWshb-1 × dWsh/dt Eq. (7′)

Under non-limiting N supply, the crop N uptake rate (dNupt/dt) depends on the potential crop mass accumulation rate (dWsh/dt), but it declines as crop mass increases. Devienne-Barret et al. (2000) showed that the rate of crop N uptake is dependent on both crop growth rate and soil N availability leading to a family of Nupt-Wsh trajectories for each steady state condition of soil N supply as represented in Fig. 4. This dual dependency of N uptake is well explained by physiological evidence on feed-back regulation of root absorption capacity of mineral N (nitrate and ammonium) by shoot growth through C and N signals (Gastal and Saugier 1989; Lejay et al. 1999).

If Nf represents the rate of N fertilizer application, the Nitrogen Use Efficiency (NUE = dWsh/dNf) for crop mass production is a function of two components: (i) the N Absorption Efficiency (NAE = dNupt/dNf) and (ii) the N Conversion Efficiency (NCE = dWsh/dNupt), so that:

NUE = NAE × NCE (8)

dNf being the increment in N fertilization rate. Then the Nupt-Wsh allometry has two important consequences for analyzing variations in NUE due to genotype-environment-management interactions as underlined by Sadras and Lemaire (2014):

(i)NAE is partly determined by crop growth rate so that genotypes having a higher crop mass should have a higher NAE than slow growing genotypes. This effect is shown on Fig. 4 where any increment in Wsh is associated with a corresponding increment of Nupt for each N supply. So genotypic variation in NAE has to be compared at a similar shoot mass otherwise the difference would be trivial.

(ii)The N dilution process implies that dNupt/dWsh decreases as shoot mass increases, so that NCE (dWsh/dNupt) increases as shoot mass increases. Consequently, the NCE of different genotypes has also to be compared at a similar shoot mass otherwise the difference observed would be obvious with a larger crop having always a higher NCE than a smaller one.

Fig. 4

Trajectories of N uptake as a function of shoot mass accumulation (Wsh) for different steady-state levels of N supply: N soil (N supply only from the soil without any N fertilizer application), N fert (N supply with a limiting N fertilization rate); N crit. (N supply with a minimum N application for achieving maximum shoot mass accumulation); and N max (N supply with a supra-optimum N fertilizer rate). Adapted from Gastal et al. (2014)

Fig. 5

Illustration of the effect of N supply on the allometry between P uptake (a) and K uptake (b) and shoot mass for natural grasslands. This effect can be decomposed into two parts: (1) an increase in P or K uptake at a similar shootmass and (2) an increase in P and K uptake associated to the increment in shoot mass. Adapted from Duru et al. (1992)

Fig. 6

Relationship between P and N concentrations in shoots (%Psh and %Nsh expressed in per cent of dry matter) for different natural grasslands in spring under non-limiting P supply conditions and having received different levels of N supply at the end of winter: white square no N application; black square100 kgN ha − 1; black circle 150 kgN ha − 1. The regression line [%Psh = (0.091 × %Nsh) + 0.133; R2 = 0.97] represents the “critical %Psh.” Variations in %Nsh are due to either (i) variation in shoot mass (Wsh) due to different N supplies and (ii) a N dilution effect associated to biomass accumulation with time. A P nutrition index (PNI) can then be calculated as PNI = (Act.%Psh)/(Crit.%Psh) for estimating the P nutrition level of a given crop. Adapted from Salette and Huché (1991)

Fig. 7

Shift in the %P-%N relationship according to the N supply of a maize crop in conditions of high (a) or low (b) soil P availability in eastern Canada. The red arrow in a indicates the positive shift in both %P and %N as N supply increases, while the arrow in b indicates a negative shift in %P associated with a positive shift in %N. The N supply treatments were 0 (dark circles), 40 (open circles), 80 (dark triangles), 120 (open triangles), 160 (dark squares), and 200 kgN/ha (open squares). The critical %P-%N curve is %P = 0.107%N+ 0.094 as determined by Ziadi et al. (2008a, b, c). Redrawn from Ziadi et al. (2008a, b, c)

Fig. 8

Nitrogen–phosphorus interactions in natural grasslands receiving a factorial combination of high applications of N (squares) and P (dark symbols) and no application of N (circles) and P (open symbols). A Effects of the N and P supplies on shoot P and N concentration (P%, %N); the line represents the critical P concentration: %Pc = 0.065%Nc + 0.15 as determined by Duru and Thellier (1997). b Effects on the N and P supplies on shoot N concentration (N%); the line represents the critical N dilution curves for C3 grasses species (Lemaire and Gastal 1997). Adapted from Duru and Ducrocq (1997)

Notes

Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  • Gilles Lemaire
    • 1
    Email author
  • Thomas Sinclair
    • 2
  • Victor Sadras
    • 3
  • Gilles Bélanger
    • 4
  1. 1.Honorary Director of Research, INRALusignanFrance
  2. 2.North Carolina State UniversityRaleighUSA
  3. 3.South Australian Research and Development InstituteUrrbraeAustralia
  4. 4.Agriculture and Agri-Food CanadaQuébecCanada

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