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Record W3152967905 · doi:10.33584/rps.13.2006.3103

High nutrient supply and carbohydrate content reduce endophyte and alkaloid concentration

2007· article· en· W3152967905 on OpenAlexaff
Susanne Rasmussen, A. J. Parsons, Q. Liu, Hong‐Wei Xue, Jonathan A. Newman

Bibliographic record

VenueNZGA Research and Practice Series · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsUniversity of Guelph
FundersAgResearch
KeywordsEndophyteLolium perenneNeotyphodiumBiologyPerennial plantAgronomyCultivarSugarNutrientLoliumBotanyPoaceaeFood scienceEcology

Abstract

fetched live from OpenAlex

Two controlled environment experiments were performed to test the effects of nitrogen, phosphorus and carbohydrates on endophyte (Neotyphodium lolii) and alkaloid concentrations in ryegrass (Lolium perenne). Three perennial ryegrass cultivars ('high sugar grasses' AberDove and AberDart; control Fennema) that differ in carbohydrate content were infected with three strains of N. lolii (common strain, CS; AR1; AR37). Infected and uninfected plants were grown under high (9 mM) and low (2.25 mM) nitrogen (AberDove, Fennema; CS, AR1, AR37) or under high (2 mM KH2PO4) and low (0.05 mM KH2PO4) phosphorus (AberDart, Fennema; CS, AR1). Quantitative realtime Polymerase Chain Reaction (qPCR) was used to estimate endophyte concentrations in harvested leaf tissues. High N and P supply as well as high carbohydrate content of the host grass reduced endophyte concentrations. Alkaloid production was also reduced under both increased N supply and in the high sugar cultivar, and was linearly related to endophyte concentration (except ergovaline). The results stress the need for wider quantification of fungal endophytes in the grassland/ foliar endophyte context, and have implications for how introducing new cultivars, novel endophytes, or increasing nutrient inputs, affect the role of endophytes in grassland ecosystems. Keywords: Neotyphodium lolii, foliar endophyte, Lolium perenne, perennial ryegrass, qPCR, high sugar ryegrass, nitrogen, phosphate, carbohydrate, AR1, AR37, alkaloids

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)0.001
metaresearch head score (Gemma)0.001
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 score0.697
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.111
GPT teacher head0.334
Teacher spread0.223 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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