Details

Autor(en) / Beteiligte

• Ma, Li
• Sun, Leigang
• Wang, Shaoqiang
• Chen, Jinghua
• Chen, Bin
• Zhu, Kai
• Amir, Muhammad
• Wang, Xiaobo
• Liu, Yuanyuan
• Wang, Pengyuan
• Wang, Junbang
• Huang, Mei
• Wang, Zhaosheng

Titel

Analysis on the relationship between sun-induced chlorophyll fluorescence and gross primary productivity of winter wheat in northern China

Ist Teil von

• Ecological indicators, 2022-06, Vol.139, p.108905, Article 108905

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2022

Quelle

ScienceDirect Journals (5 years ago - present)

Beschreibungen/Notizen

• •The PRI as an indicator of NPQ to characterize the change in heat dissipation.•SIF is strongly affected by radiation, while PRI is sensitive to soil moisture.•PRI can be used to improve the relationship between GPP and SIF. The sun-induced chlorophyll fluorescence (SIF) is directly related to the photosynthesis of winter wheat and has a good linear relationship with the gross primary production (GPP). However, the relationship of SIF and GPP is still uncertain under different soil water content conditions. The sun-induced chlorophyll fluorescence, GPP and non-photochemical quenching (NPQ) are the three ways of photosynthetically active radiation in plants. The photochemical reflectance index (PRI) can be used as a proxy indicator of NPQ to characterize the change in heat dissipation during photosynthesis process of winter wheat. To detect the impact of soil water content on winter wheat photosynthesis and SIF and GPP relationship, based on the ground measurement data at Zhaoxian Experimental Station in northern China during the growing season in 2018 and the simulated data by the SCOPE model, we use PRI to improve the GPP model estimated by SIF. The results indicate that: (1) PRI is sensitive to soil water content (R2 = 0.64), so it can be used to improve the estimation of GPP based on SIF under different soil water conditions; (2) For the ground measurement data, PRIobv can improve the estimation accuracy of GPPobv by SIFobv. Under different soil water content (SWC) conditions, the relationship between GPPobv and SIFobv is significantly correlated (R2 = 0.33–0.45, p < 0.01), and PRIobv can be used to improve the estimation between GPPobv and SIFobv (R2 = 0.57–0.62, p < 0.01); (3) The simulation results of the SCOPE model show that the simulation effect of the model can be better optimized by adding PRI under the condition of relatively dry soil (△R2 = 0.13–0.17). Our research suggests that PRI can be added when estimating GPP using SIF information, especially when winter wheat is under low soil water content conditions.