Abstract
The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO2). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (Awithout). However, differences in predicted photosynthesis integrated over a day or over the growing season from Awithout depended on the value of the kinetic time constant (τ), suggesting that τ is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.
| Original language | English |
|---|---|
| Pages (from-to) | 2435-2447 |
| Number of pages | 13 |
| Journal | Journal of Experimental Botany |
| Volume | 70 |
| Issue number | 9 |
| Early online date | 25 Jul 2018 |
| DOIs | |
| Publication status | Published - 15 Apr 2019 |
Keywords
- Acclimation
- Chlorophyll
- Electron transport
- Modelling
- Optimization
- Photosynthesis
- Rubisco
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10.1093/jxb/ery277Licence: CC BY
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Yin, X., Schapendonk, A. H. C. M. (2019). Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions. Journal of Experimental Botany, 70(9), 2435-2447. https://doi.org/10.1093/jxb/ery277
Yin, Xinyou ; Schapendonk, Ad H.C.M. ; Struik, Paul C. / Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions. In: Journal of Experimental Botany. 2019 ; Vol. 70, No. 9. pp. 2435-2447.
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title = "Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions",
abstract = "The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO2). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (Awithout). However, differences in predicted photosynthesis integrated over a day or over the growing season from Awithout depended on the value of the kinetic time constant (τ), suggesting that τ is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.",
keywords = "Acclimation, Chlorophyll, Electron transport, Modelling, Optimization, Photosynthesis, Rubisco",
author = "Xinyou Yin and Schapendonk, {Ad H.C.M.} and Struik, {Paul C.}",
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Yin, X, Schapendonk, AHCM 2019, 'Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions', Journal of Experimental Botany, vol. 70, no. 9, pp. 2435-2447. https://doi.org/10.1093/jxb/ery277
Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions. / Yin, Xinyou; Schapendonk, Ad H.C.M.; Struik, Paul C.
In: Journal of Experimental Botany, Vol. 70, No. 9, 15.04.2019, p. 2435-2447.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions
AU - Yin, Xinyou
AU - Schapendonk, Ad H.C.M.
AU - Struik, Paul C.
PY - 2019/4/15
Y1 - 2019/4/15
N2 - The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO2). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (Awithout). However, differences in predicted photosynthesis integrated over a day or over the growing season from Awithout depended on the value of the kinetic time constant (τ), suggesting that τ is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.
AB - The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO2). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (Awithout). However, differences in predicted photosynthesis integrated over a day or over the growing season from Awithout depended on the value of the kinetic time constant (τ), suggesting that τ is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.
KW - Acclimation
KW - Chlorophyll
KW - Electron transport
KW - Modelling
KW - Optimization
KW - Photosynthesis
KW - Rubisco
U2 - 10.1093/jxb/ery277
DO - 10.1093/jxb/ery277
M3 - Article
SN - 0022-0957
VL - 70
SP - 2435
EP - 2447
JO - Journal of Experimental Botany
JF - Journal of Experimental Botany
IS - 9
ER -
Yin X, Schapendonk AHCM, Struik PC. Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions. Journal of Experimental Botany. 2019 Apr 15;70(9):2435-2447. Epub 2018 Jul 25. doi: 10.1093/jxb/ery277
