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Record W2796670645 · doi:10.1002/rcm.8136

A comparison of extraction systems for plant water stable isotope analysis

2018· article· en· W2796670645 on OpenAlexaff
Cody Millar, Dyan Pratt, David J. Schneider, Jeffrey J. McDonnell

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersCenters for Disease Control and Prevention
KeywordsChemistryExtraction (chemistry)DistillationVacuum distillationMass spectrometryIsotope analysisWater extractionAnalytical Chemistry (journal)Isotope-ratio mass spectrometryChromatographyEnvironmental chemistry

Abstract

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Rationale The stable isotope ratios of water (δ 2 H and δ 18 O values) have been widely used to trace water in plants in a variety of physiological, ecohydrological, biogeochemical and hydrological studies. In such work, the analyte must first be extracted from samples, prior to isotopic analysis. While cryogenic vacuum distillation is currently the most widely used method reported in the literature, a variety of extraction‐collection‐analysis methods exist. A formal inter‐method comparison on plant tissues has yet to be carried out. Methods We performed an inter‐method comparison of six plant water extraction techniques: direct vapour equilibration, microwave extraction, two unique versions of cryogenic vacuum distillation, centrifugation, and high‐pressure mechanical squeezing. These methods were applied to four isotopically unique plant portions (head, stem, leaf, and root crown) of spring wheat ( Triticum aestivum L.). Extracted plant water was analyzed via spectrometric (OA‐ICOS) and mass‐based (IRMS) analysis systems when possible. Spring wheat was grown under controlled conditions with irrigation inputs of a known isotopic composition. Results The tested methods of extraction yielded markedly different isotopic signatures. Centrifugation, microwave extraction, direct vapour equilibration, and high‐pressure mechanical squeezing produced water more enriched in 2 H and 18 O content. Both cryogenic vacuum distillation systems and the high‐pressure mechanical squeezing method produced water more depleted in 2 H and 18 O content, depending upon the plant portion extracted. The various methods also produced differing concentrations of co‐extracted organic compounds, depending on the mode of extraction. Overall, the direct vapor equilibration method outperformed all other methods. Conclusions Despite its popularity, cryogenic vacuum distillation was outperformed by the direct vapor equilibration method in terms of limited co‐extraction of volatile organic compounds, rapid sample throughput, and near instantaneous returned stable isotope results. More research is now needed with other plant species, especially woody plants, to see how far the findings from this study could be extended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.302
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations140
Published2018
Admission routes1
Has abstractyes

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