Worne, Savannah; Lacey, Jack H.; Barr, Cameron; Schulz, Cameron; Leng, Melanie J.
ORCID: https://orcid.org/0000-0003-1115-5166.
2025
Assessment of bias in carbon isotope composition of organic leaf matter due to pre‐analysis milling methods [in special issue: S1]
Rapid Communications in Mass Spectrometry, 39, e9134.
10.1002/rcm.9134
Abstract
Rationale
Stable isotope analysis of leaf material has many applications including assessment of plant water-use efficiency and paleoclimatology. To facilitate interpretations of small shifts in the carbon isotope composition (δ13C) of leaves, accurate and repeatable results are required. Pre-sample homogenisation is essential to ensure a representative sample is analysed, but can also introduce error.
Methods
We investigate how different grinding methods (freezer-milling and ball-milling) affect the carbon content and δ13C of tree leaves from a wetland in Queensland, Australia, commenting on how increased temperature, sample contamination, sample loss, or poor homogenisation may impact results.
Results
No alteration of leaf δ13C is observed due to different milling methods, although there may be a significant increase in %C of samples processed using ball-milling.
Conclusions
We suggest %C variability is possibly due to contamination from abraded plastic vials or insufficient homogenisation during ball-milling, with no significant impact on δ13C. Overall, we suggest that intermittent ball-milling may be the best solution to reduce costs, preparation time and use of liquid nitrogen, aiming to achieve complete homogenisation using the shortest possible duration of milling.
Documents
530489:263141
Open Access Paper
Rapid Comm Mass Spectrometry - 2021 - Worne - Assessment of bias in carbon isotope composition of organic leaf matter due.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
Rapid Comm Mass Spectrometry - 2021 - Worne - Assessment of bias in carbon isotope composition of organic leaf matter due.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
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BGS Programmes 2020 > Environmental change, adaptation & resilience
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