MétaCan
Menu
Back to cohort

Loose smut resistance and adaptability of spring soft wheat varieties of VIR collection

2020· article· en· W3010519531 on OpenAlexaboutno aff
А. В. Харина, О. С. Амунова

Bibliographic record

VenueAgricultural science Euro-North-East · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsSmutInfestationBiologyHorticultureGrain yieldResistance (ecology)Plant disease resistanceAdaptabilityAgronomyYield (engineering)GeographyEcology

Abstract

fetched live from OpenAlex

In 2013-2019 in the conditions of Kirov region 178 varieties of spring soft wheat from the collection of the Federal Research Center of N.I.Vavilov All-Russian Institute of Plant Genetic Resources (VIR) were studied according to loose smut resistance, plasticity and yield stability. Among studied varieties 36 immune and 12 practically immune to loose smut infestation samples have been revealed. They can be used as sources of resistance in selection. The most favourable conditions for infestation of spring soft wheat plants with loose smut develop since the beginning of blossoming till grain filling. The higher the air temperature and the amount of precipitation during this period, the higher is the percentage of wheat plants affected with this disease. As the percentage of the stems affected by loose smut increased, total yield losses grew as well (r = 0.99). Nineteen varieties of spring wheat significantly exceeded the standard variety Bazhenka (Russia) in yield on an infection background. Five mid-susceptible varieties which showed tolerance to the disease have been selected. They are Tulaykovskaya Nadezhda (Russia), Samgau, Dostyk, Karabalykskaya 91 (Kazakhstan) and Visa (Belarus). During the years the following varieties revealed the highest and stable productivity: Stepnaya 50, Dostyk (Kazakhstan), Kazanskaya Yubileynaya, Niva 2, Provincia, Egisar 29, Sudarushka, Tulaykovskaya Nadezhda (Russia), Hoffman (Canada), UL Pettit (USA) and Leguan (Czechoslovakia). The following varieties were designated as the intensive type: Tyumenskaya 26, Elizaveta, Maria 1, Melodiya, Niva 2 (Russia), Kharkovskaya 10 (Ukraine), Samgau (Kazakhstan), Visa (Belarus), and American varieties Ranger and UL Pettit (b i > 1). Varieties Ranger and UL Pettit showed high productivity in favorable cultivation conditions. Varieties Mazhor (Ukraine), Favorit (Russia) and Karabalykskaya 91(Kazakhstan) (b i <1) should be used on an extensive background. By deterioration of cultivation conditions the productivity of these varieties decreased insignificantly. The relationship between productivity and adaptability parameters has been established (b i , Ноm). The highyielding varieties have been characterized as more plastic (r = 0.69) and stress resistant (r = 0.73).

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 score0.895
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.182
Teacher spread0.161 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAgricultural science Euro-North-EastSame topicAgricultural Productivity and Crop ImprovementFrench-language works237,207