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pH affects ammonium, nitrate and proton fluxes in the apical region of conifer and soybean roots

2009· article· en· W2013774463 on OpenAlexafffund
B. J. Hawkins, Samantha Robbins

Bibliographic record

VenuePhysiologia Plantarum · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNitrateAmmoniumAmmonium nitrateChemistryBotanyAgronomyBiology

Abstract

fetched live from OpenAlex

The effect of pH on nitrate and ammonium uptake in the high-affinity transport system and low-affinity transport system ranges was compared in two conifers and one crop species. Many conifers grow on acidic soils, thus their preference for ammonium vs nitrate uptake can differ from that of crop plants, and the effect of pH on nitrogen (N) uptake may differ. Proton, ammonium and nitrate net fluxes were measured at seedling root tips and 5, 10, 20 and 30 mm from the tips using a non-invasive microelectrode ion flux measurement system in solutions of 50 or 1500 microM NH(4)NO(3) at pH 4 and 7. In Glycine max and Pinus contorta, efflux of protons was observed at pH 7 while pH 4 resulted in net proton uptake in some root regions. Pseudotsuga menziesii roots consistently showed proton efflux behind the root tip, and thus appear better adapted to maintain proton efflux in acid soils. P. menziesii's ability to maintain ammonium uptake at low pH may relate to its ability to maintain proton efflux. In all three species, net nitrate uptake was greatest at neutral pH. Net ammonium uptake in G. max and net nitrate uptake in P. menziesii were greatly reduced at pH 4, particularly at high N concentration, thus N concentration should be considered when determining optimum pH for N uptake. In P. menziesii and G. max, net N uptake was greater in 1500 than 50 microM NH(4)NO(3) solution, but flux profiles of all ions varied among species.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
Threshold uncertainty score0.155

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)0.0000.000

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 head0.018
GPT teacher head0.210
Teacher spread0.193 · 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 designObservational
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

Citations81
Published2009
Admission routes2
Has abstractyes

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