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Record W4309852416 · doi:10.1093/aob/mcac141

Foliar water uptake in <i>Pinus</i> species depends on needle age and stomatal wax structures

2022· article· en· W4309852416 on OpenAlexafffund
Anita Roth‐Nebelsick, Uwe G. Hacke, Dagmar Voigt, Stefan G. Schreiber, Matthias Krause

Bibliographic record

VenueAnnals of Botany · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaTechnische Universität DresdenEberhard Karls Universität TübingenUniversität Hohenheim
KeywordsWaxPinus <genus>BiologyBotanyHorticulture

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Foliar water uptake (FWU) has been documented in many species and is increasingly recognized as a non-trivial factor in plant-water relationships. However, it remains unknown whether FWU is a widespread phenomenon in Pinus species, and how it may relate to needle traits such as the form and structure of stomatal wax plugs. In this contribution, these questions were addressed by studying FWU in current-year and 1-year-old needles of seven Pinus species. METHODS: We monitored FWU gravimetrically and analysed the needle surface via cryo-scanning electron microscopy. Additionally, we considered the effect of artificial wax erosion by application of the surfactant Triton X-100, which is able to alter wax crystals. KEY RESULTS: The results show for all species that (1) FWU occurred, (2) FWU is higher in old needles compared to young needles and (3) there is substantial erosion of stomatal wax plugs in old needles. FWU was highest in Pinus canariensis, which has a thin stomatal wax plug. Surfactant treatment enhanced FWU. CONCLUSIONS: The results of this study provide evidence for (1) widespread FWU in Pinus, (2) the influence of stomatal wax plugs on FWU and (3) age-related needle surface erosion.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.232
Teacher spread0.181 · 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 teacher head, 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

Citations13
Published2022
Admission routes2
Has abstractyes

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