Leaf water potential measurements using the pressure chamber: Synthetic testing of assumptions towards best practices for precision and accuracy Article Swipe
Celia M. Rodríguez Domínguez
,
Alicia Forner
,
Sebastià Martorell
,
Brendan Choat
,
Rosana López
,
Jennifer M. R. Peters
,
Sebastian Pfautsch
,
Stefan Mayr
,
Madeline R. Carins‐Murphy
,
Scott A. M. McAdam
,
Freya Richardson
,
Antonio Díaz‐Espejo
,
Virginia Hernández‐Santana
,
Paulo Eduardo Menezes‐Silva
,
José Manuel Torres Ruiz
,
Timothy A. Batz
,
Lawren Sack
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1111/pce.14330
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1111/pce.14330
Leaf water potential ( ψ leaf ), typically measured using the pressure chamber, is the most important metric of plant water status, providing high theoretical value and information content for multiple applications in quantifying critical physiological processes including drought responses. Pressure chamber measurements of ψ leaf ( ψ leafPC ) are most typical, yet, the practical complexity of the technique and of the underlying theory has led to ambiguous understanding of the conditions to optimize measurements. Consequently, specific techniques and precautions diversified across the global research community, raising questions of reliability and repeatability. Here, we surveyed specific methods of ψ leafPC from multiple laboratories, and synthesized experiments testing common assumptions and practices in ψ leafPC for diverse species: (i) the need for equilibration of previously transpiring leaves; (ii) leaf storage before measurement; (iii) the equilibration of ψ leaf for leaves on bagged branches of a range of dehydration; (iv) the equilibration of ψ leaf across the lamina for bagged leaves, and the accuracy of measuring leaves with artificially ‘elongated petioles’; (v) the need in ψ leaf measurements for bagging leaves and high humidity within the chamber; (vi) the need to avoid liquid water on leaf surfaces; (vii) the use of ‘pulse’ pressurization versus gradual pressurization; and (viii) variation among experimenters in ψ leafPC determination. Based on our findings we provide a best practice protocol to maximise accuracy, and provide recommendations for ongoing species‐specific tests of important assumptions in future studies.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/pce.14330
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/pce.14330
- OA Status
- hybrid
- Cited By
- 128
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4224326980
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4224326980Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1111/pce.14330Digital Object Identifier
- Title
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Leaf water potential measurements using the pressure chamber: Synthetic testing of assumptions towards best practices for precision and accuracyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-04-08Full publication date if available
- Authors
-
Celia M. Rodríguez Domínguez, Alicia Forner, Sebastià Martorell, Brendan Choat, Rosana López, Jennifer M. R. Peters, Sebastian Pfautsch, Stefan Mayr, Madeline R. Carins‐Murphy, Scott A. M. McAdam, Freya Richardson, Antonio Díaz‐Espejo, Virginia Hernández‐Santana, Paulo Eduardo Menezes‐Silva, José Manuel Torres Ruiz, Timothy A. Batz, Lawren SackList of authors in order
- Landing page
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https://doi.org/10.1111/pce.14330Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/pce.14330Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/pce.14330Direct OA link when available
- Concepts
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Accuracy and precision, Environmental science, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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128Total citation count in OpenAlex
- Citations by year (recent)
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2025: 35, 2024: 53, 2023: 25, 2022: 14Per-year citation counts (last 5 years)
- References (count)
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62Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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