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Molecular identification and morphological characterisation of multiple fungal pathogens of triticale in Northern Kazakhstan

2024· article· en· W4403229239 on OpenAlexaff
O. Y. Solovyov, Vitalij Zaika, Vladimir Kiyan, Ainura Smagulova, U.I. Amanbayeva, Vladimir Shvidchenko, Ludovic J. A. Capo-chichi

Bibliographic record

VenueHERALD OF SCIENCE OF S SEIFULLIN KAZAKH AGRO TECHNICAL UNIVERSITY · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTriticaleIdentification (biology)BiologyComputational biologyBotany

Abstract

fetched live from OpenAlex

Background and Aim. Тtriticale is classified as an amphidiploids and is the first grain crop created by humans, possessing high yield potential along with favorable biochemical and technological characteristics. For a long time, it was believed that triticale, during selection, inherited disease resistance from wheat and resistance to abiotic factors from rye. However, in recent years, there have been several reports that triticale is to fungal diseases, which reduces the quality of the harvested crop. The aim of our study is to examine and characterize the fungal pathogens of triticale in Northern Kazakhstan, and conduct molecular-genetic identification of the main fungal pathogens.MaterialsandMethods. The study was conducted of triticale from two varieties, Dauren and Rossika. Primary fungal isolation was carried out on agarized nutrient media, with preliminary identification using microscopy. Molecular genetic analysis was performed to determine the species of fungi. Results. During the study, we isolated five major fungal pathogens from different parts of the plant. Data on the percentage of infection by the main fungal pathogens were provided. Three of them are pathogens of alternariosis – Alternaria alternate (more common in grains 39%, in leaves and scales of seeds 19-21%), fusariosis – Fusarium tricinctum (occurrence: in roots 57%, in grains 17%, in leaves 10%) and helminthosporiosis – Bipolaris sorokiniana (occurrence in roots and leaves 0.83%) of grain crops, which can lead to a decrease and loss of yield due to their production of mycotoxins. A cultural and morphological description of the main fungal pathogens of grain crops was provided. Moleculargenetic identification was carried out using the ribosomal marker ITS (internal transcribed spacer).Conclusion. According to result of our research, we characterized and molecular-genetically identified the most common fungi found on different parts of the triticale plant.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.206
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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueHERALD OF SCIENCE OF S SEIFULLIN KAZAKH AGRO TECHNICAL UNIVERSITYSame topicWheat and Barley Genetics and PathologyFrench-language works237,207