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Evaporative flux method of leaf hydraulic conductance estimation: sources of uncertainty and reporting format recommendation

BACKGROUND: The accurate estimation of leaf hydraulic conductance (K(leaf)) is important for revealing leaf physiological characteristics and function. However, the K(leaf) values are largely incomparable in previous studies for a given species indicating some uncertain influencing factors in K(leaf...

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Detalles Bibliográficos
Autores principales: Wang, Xiaoxiao, Zhao, Jinfang, Huang, Jianliang, Peng, Shaobing, Xiong, Dongliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9097237/
https://www.ncbi.nlm.nih.gov/pubmed/35549958
http://dx.doi.org/10.1186/s13007-022-00888-w
Descripción
Sumario:BACKGROUND: The accurate estimation of leaf hydraulic conductance (K(leaf)) is important for revealing leaf physiological characteristics and function. However, the K(leaf) values are largely incomparable in previous studies for a given species indicating some uncertain influencing factors in K(leaf) measurement. RESULT: We investigated the potential impacts of plant sampling method, measurement setup, environmental factors, and transpiration steady state identification on K(leaf) estimation in Oryza sativa and Cinnamomum camphora using evaporation flux method (EFM). The effects of sampling and rehydration time, the small gravity pressure gradients between water sources and leaves, and water degassing on K(leaf) estimation were negligible. As expected, the estimated steady flow rate (E) was significantly affected by multiple environmental factors including airflow around leaf, photosynthetically active radiation (PARa) on leaf surfaces and air temperature. K(leaf) decreased by 40% when PARa declined from 1000 to 500 µmol m(−2) s(−1) and decreased by 15.1% when air temperature increased from 27 to 37 °C. In addition, accurate steady-state flow rate identification and leaf water potential measurement were important for K(leaf) estimation. CONCLUSIONS: Based on the analysis of influencing factors, we provided a format for reporting the metadata of EFM-based K(leaf) to achieve greater comparability among studies and interpretation of differences. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-022-00888-w.