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Record W4413989356 · doi:10.3390/plants14172766

Profiling Environmental Variations in Condensed Tannins and Other Metabolites of Birdsfoot Trefoil (Lotus corniculatus L.) Genotypes

2025· article· en· W4413989356 on OpenAlexafffundabout
Solihu Kayode Sakariyahu, Tim McDowell, Justin B. Renaud, Y. A. Papadopoulos, Kathleen Glover, Rebecca Brown, Michael D. Peel, Heathcliffe Riday, Susanne E. Kohalmi, Abdelali Hannoufa

Bibliographic record

VenuePlants · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaWestern University
FundersAgriculture and Agri-Food CanadaBeef Cattle Research Council
KeywordsLotus corniculatusTrefoilProanthocyanidinLotusGenotypeBiologyBotanyChemistryAgronomyBiochemistryAntioxidant

Abstract

fetched live from OpenAlex

L., also known as birdsfoot trefoil (BFT), is a perennial, non-bloating, temperate forage legume widely grown due to its accumulation of high levels of condensed tannins (CTs) in foliage. However, variations in the CT levels and other plant metabolites in BFT genotypes in response to environmental and yearly factors under field conditions remain largely unexplored. Here, we combine conventional CT quantification and metabolome profiling with high-resolution liquid chromatography-mass spectrometry (LC-MS) to understand how environmental factors impact CT and other metabolite profiles. Eight BFT genotypes grown in Kentville, Canada, and Rhode Island and Utah in the United States were investigated, revealing significant genotypic variations in soluble CT contents. The global metabolome profiles of the eight BFT genotypes clustered predominantly based on geographical location. These results demonstrate that geographical location strongly influences CT accumulation and metabolome composition, offering potential for selecting genotypes adapted to specific environments. Our findings provide an opportunity for targeted breeding strategies to optimize CT levels, improve forage quality, and enhance stress resilience in birdsfoot trefoil.

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 score0.709
Threshold uncertainty score0.109

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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

Citations3
Published2025
Admission routes3
Has abstractyes

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