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. 2023 Jul 4:14:1225295.
doi: 10.3389/fpls.2023.1225295. eCollection 2023.

Leaf photosynthetic pigment as a predictor of leaf maximum carboxylation rate in a farmland ecosystem

Yue Li  1 , Qingtao Wang  2 , Taimiao Fu  2 , Yunfeng Qiao  3 , Lihua Hao  4 , Tao Qi  2
Affiliations

Leaf photosynthetic pigment as a predictor of leaf maximum carboxylation rate in a farmland ecosystem

Yue Li et al. Front Plant Sci. .

Abstract

The leaf maximum rate of carboxylation (Vcmax) is a key parameter of plant photosynthetic capacity. The accurate estimation of Vcmax is crucial for correctly predicting the carbon flux in the terrestrial carbon cycle. Vcmax is correlated with plant traits including leaf nitrogen (Narea) and leaf photosynthetic pigments. Proxies for leaf chlorophyll (Chlarea) and carotenoid contents (Cararea) need to be explored in different ecosystems. In this study, we evaluated the relationship between leaf maximum rate of carboxylation (scaled to 25°C; Vcmax25) and both leaf Narea and photosynthetic pigments (Chlarea and Cararea) in winter wheat in a farmland ecosystem. Our results showed that Vcmax25 followed the same trends as leaf Chlarea. However, leaf Narea showed smaller dynamic changes before the flowering stage, and there were smaller seasonal variations in leaf Cararea. The correlation between leaf Vcmax25 and leaf Chlarea was the strongest, followed by leaf Cararea and leaf Narea (R2 = 0.69, R2 = 0.47 and R2 = 0.36, respectively). The random forest regression analysis also showed that leaf Chlarea and leaf Cararea were more important than leaf Narea for Vcmax25. The correlation between leaf Vcmax25 and Narea can be weaker since nitrogen allocation is dynamic. The estimation accuracy of the Vcmax25 model based on Narea, Chlarea, and Cararea (R2 = 0.75) was only 0.05 higher than that of the Vcmax25 model based on Chlarea and Cararea (R2 = 0.70). However, the estimation accuracy of the Vcmax25 model based on Chlarea and Cararea (R2 = 0.70) was 0.34 higher than that of the Vcmax25 model based on Narea (R2 = 0.36). These results highlight that leaf photosynthetic pigments can be a predictor for estimating Vcmax25, expanding a new way to estimate spatially continuous Vcmax25 on a regional scale, and to improve model simulation accuracy.

Keywords: leaf carotenoid content; leaf chlorophyll content; leaf nitrogen content; maximum rate of carboxylation; photosynthetic capacity.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Seasonal changes in (A) photosynthetic rate and nitrogen content, (B) leaf chlorophyll and leaf carotenoid contents, and (C) Vcmax25 and Jmax25 for winter wheat in 2021.
Figure 2
Figure 2
Correlation between both leaf photosynthetic rate and leaf photosynthetic capacity with different leaf traits variables. ***, ** and * represent p< 0.001, p< 0.01and p< 0.05, respectively. The caption describes all significant situations of correlation between parameters, including significant correlation (*) and extremely significant correlation (** and ***). The results in Figure 2 showed that the parameters were highly correlated (** and ***) or uncorrelated.
Figure 3
Figure 3
Seasonal patterns in (A) leaf Chlarea to Narea ratios, (B) PR, (C) PB, and (D) PL, ± SD, in 2021.
Figure 4
Figure 4
Relationships between (A) leaf nitrogen and chlorophyll contents, (B) leaf nitrogen and carotenoid contents, (C) leaf carotenoid and chlorophyll contents in 2021. Horizontal error bars denote standard deviation of leaf chlorophyll and leaf carotenoid. Vertical error bars refer to standard deviation of leaf nitrogen and leaf carotenoid.
Figure 5
Figure 5
The importance of leaf Cararea, leaf Chlarea, leaf Narea, and SLA to Vcmax25 in 2021.
See this image and copyright information in PMC

References

    1. Ali A. A., Xu C. G., Rogers A., McDowell N. G., Medlyn B. E., Fisher R. A., et al. . (2015). Global-scale environmental control of plant photosynthetic capacity. Ecol. Appl. 25 (8), 2349–2365. doi: 10.1890/14-2111.1.sm - DOI - PubMed
    1. Alton P. B. (2017). Retrieval of seasonal rubisco-limited photosynthetic capacity at global FLUXNET sites from hyperspectral satellite remote sensing: impact on carbon modelling. Agric.For. Meteorol. 232, 74–88. doi: 10.1016/j.agrformet.2016.08.001 - DOI
    1. Anav A., Friedlingstein P., Beer C., Ciais P., Harper A. (2015). Spatiotemporal patterns of terrestrial gross primary production: a review. Rev. Geophysics 53 (3), 785–818. doi: 10.1002/2015RG000483 - DOI
    1. Bonan G. B., Doney S. C. (2018). Climate, ecosystems, and planetary futures: the challenge to predict life in earth system models. Science 359 (6375), 533–533. doi: 10.1126/science.aam8328 - DOI - PubMed
    1. Bondeau A., Smith P. C, Zaehle S., Schaphoff S., Lucht W., Cramer W., et al. . (2007). Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biol. 13(3), 679–706. doi: 10.1111/j.1365-2486.2006.01305.x - DOI

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