Li Yue, Wang Qingtao, Fu Taimiao, Qiao Yunfeng, Hao Lihua, Qi Tao
School of Earth Science and Engineering, Hebei University of Engineering, Handan, China.
School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan, China.
Front Plant Sci. 2023 Jul 4;14:1225295. doi: 10.3389/fpls.2023.1225295. eCollection 2023.
The leaf maximum rate of carboxylation (V) is a key parameter of plant photosynthetic capacity. The accurate estimation of V is crucial for correctly predicting the carbon flux in the terrestrial carbon cycle. V is correlated with plant traits including leaf nitrogen (N) and leaf photosynthetic pigments. Proxies for leaf chlorophyll (Chl) and carotenoid contents (Car) need to be explored in different ecosystems. In this study, we evaluated the relationship between leaf maximum rate of carboxylation (scaled to 25°C; V) and both leaf N and photosynthetic pigments (Chl and Car) in winter wheat in a farmland ecosystem. Our results showed that V followed the same trends as leaf Chl. However, leaf N showed smaller dynamic changes before the flowering stage, and there were smaller seasonal variations in leaf Car. The correlation between leaf V and leaf Chl was the strongest, followed by leaf Car and leaf N (R = 0.69, R = 0.47 and R= 0.36, respectively). The random forest regression analysis also showed that leaf Chl and leaf Car were more important than leaf N for V. The correlation between leaf V and N can be weaker since nitrogen allocation is dynamic. The estimation accuracy of the V model based on N, Chl, and Car (R= 0.75) was only 0.05 higher than that of the V model based on Chl and Car (R= 0.70). However, the estimation accuracy of the V model based on Chl and Car (R= 0.70) was 0.34 higher than that of the V model based on N (R= 0.36). These results highlight that leaf photosynthetic pigments can be a predictor for estimating V, expanding a new way to estimate spatially continuous V on a regional scale, and to improve model simulation accuracy.
叶片最大羧化速率（V）是植物光合能力的关键参数。准确估算V对于正确预测陆地碳循环中的碳通量至关重要。V与包括叶片氮（N）和叶片光合色素在内的植物性状相关。需要在不同生态系统中探索叶片叶绿素（Chl）和类胡萝卜素含量（Car）的替代指标。在本研究中，我们评估了农田生态系统中冬小麦叶片最大羧化速率（校正到25°C；V）与叶片N以及光合色素（Chl和Car）之间的关系。我们的结果表明，V与叶片Chl的变化趋势相同。然而，叶片N在开花期之前的动态变化较小，叶片Car的季节变化也较小。叶片V与叶片Chl之间的相关性最强，其次是叶片Car和叶片N（相关系数R分别为0.69、0.47和0.36）。随机森林回归分析还表明，对于V而言，叶片Chl和叶片Car比叶片N更重要。由于氮分配是动态的，叶片V与N之间的相关性可能较弱。基于N、Chl和Car的V模型的估算精度（R=0.75）仅比基于Chl和Car的V模型（R=0.70）高0.05。然而，基于Chl和Car的V模型的估算精度（R=0.70）比基于N的V模型（R=0.36）高0.34。这些结果表明，叶片光合色素可以作为估算V的预测指标，为在区域尺度上估算空间连续的V以及提高模型模拟精度开辟了一条新途径。
