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Record W4417359165 · doi:10.1080/07060661.2025.2595618

Emerging diseases affecting quinoa ( <i>Chenopodium quinoa</i> ) cultivation in Saskatchewan, Canada

2025· article· en· W4417359165 on OpenAlexaffvenueabout
E. Mangwende, Samira Safari, Zoé Lepage, Homa Askarian, Alireza Akhavan, Christopher K. Yost

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsSaskatchewan Ministry of AgricultureUniversity of Regina
Fundersnot available
KeywordsCropYield (engineering)PopulationCrop yieldCultivar

Abstract

fetched live from OpenAlex

Quinoa (Chenopodium quinoa) is a relatively new crop in Canada and is gaining interest among producers. To close critical knowledge gaps and support plant health in quinoa production, comprehensive disease surveys were conducted during the 2021 and 2022 growing seasons across 11 commercial fields representative of most of the quinoa production areas in Saskatchewan. Disease incidence was assessed at 10 sites per field along W-shaped transects, with infected plants destructively sampled and analysed in the laboratory. Five major diseases were identified: downy mildew, leaf spots, stem diseases, panicle rot and seedling disease. A total of 206 fungal isolates were recovered, with Fusarium species being the most prevalent (37.4%). Fusarium graminearum and F. avenaceum were consistently associated with panicle rot symptoms. Alternaria alternata and Stemphylium vesicarium accounted for 18.4% and 12.1% of isolates, respectively, and were linked to leaf spot symptoms. Sclerotinia sclerotiorum was primarily associated with stem rot. Seedling diseases and root rots were predominantly caused by F. redolens, F. culmorum and Rhizoctonia solani. Koch’s postulates were fulfilled, confirming these pathogens as causal agents of diseases observed in the field. This study establishes a critical baseline for quinoa disease research in Canada, highlighting the need for ongoing monitoring and research to develop adaptive management strategies. Such efforts are essential to mitigate disease impacts and ensure the long-term sustainability of quinoa production in Canada and beyond.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.482

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 head0.005
GPT teacher head0.179
Teacher spread0.174 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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