Estimating daytime respiration with steady-state and dynamic Laisk methods and its implications for mesophyll conductance.

Authors

Bar Ben-Zeev, Or Shapira, Yotam Zait

Published in

Tree physiology. Oct 30, 2026. Epub Oct 30, 2026.

Abstract

Daytime respiration (Rd), a crucial physiological process in plants, poses significant measurement challenges because it is difficult to isolate from photosynthetic processes under light conditions. The Laisk method, a widely used approach for measuring Rd, has been enhanced by the updated dynamic approach of the LI-COR 6800, which employs advanced equations for stable measurements under changing environmental conditions. We compared the steady-state and dynamic Laisk methods on banana plants (Musa acuminata cv. Cavendish) at four different growth temperatures and tested various CO2 decrease rates to identify a suitable measurement protocol. Banana was selected as a thermophilic species with strong stomatal sensitivity, making it suitable for evaluating methodological constraints under dynamic conditions. Our study indicates that the dynamic Laisk method provides comparable mean estimates of the apparent intercellular CO2 compensation point (Ci*) and Rd, with no significant effect of measurement method or method × growth temperature interaction. In addition, the dynamic method allowed measurements to be performed over shorter time intervals, enabling respiration to be resolved across the diurnal cycle. Rd varied substantially during the day, whereas Ci* remained comparatively stable. Using hourly Rd and Ci* values in mesophyll conductance (gm) calculations altered both the magnitude and timing of diurnal gm estimates and strengthened the relationship between net CO2 assimilation (An) and gm. Moreover, the dynamic method reduces the duration of leaf exposure to low-light and low-CO2 conditions, which may be advantageous during repeated measurements. Our findings highlight the dynamic method's practical value for repeated measurements and emphasize the importance of accounting for temporal variation in Rd when estimating gm.

PMID:
42961321
Bibliographic data and abstract were imported from PubMed on 30 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.