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Record W3195401970 · doi:10.3390/agronomy11081640

Estimation of Stem-Solidness and Yield Components in Selected Spring Wheat Genotypes

2021· article· en· W3195401970 on OpenAlexaboutno aff
Mateusz Pluta, Danuta Kurasiak‐Popowska, Jerzy Nawracała, Jan Bocianowski, Sylwia Mikołajczyk

Bibliographic record

VenueAgronomy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsPithCultivarPlant stemBiologyHorticultureAgronomyBiplotHectareGenotypeAgriculture

Abstract

fetched live from OpenAlex

Solid-stemmed wheat genotypes are better protected from damage caused by wheat stem sawfly (Cephus pygmaeus L.) larvae and at lower risk of lodging, as they are additionally strengthened. The aim of the study was to analyse the stem-solidness of fifty spring wheat cultivars with pith. A field experiment was conducted at the Agricultural Research Station Dłoń, Poland in the years 2012–2014. The method recommended by the International Union for the Protection of New Varieties of Plants (UPOV) and the methodology described by DePauw and Read were used to analyse the stem-solidness. The statistical analysis of the results showed that the stems of the wheat cultivars differed in their, therefore, they were divided into seven classes. There were nine Polish cultivars, two genotypes from Canada (BW 597 and AC Elsa) and one Portuguese genotype (I 836) with hollow stems. There were only nine solid-stemmed cultivars. Both methodologies were used to assess the filling of the stem in the whole plant upon analysis of its filling at the cross-section of the first internode. Both methods gave the same results. The DePauw and Read methodology showed that the internodes in the lower part of the plants were filled to the greatest extent. The same genotypes collected in the consecutive years of the study differed in the filling of their stems with pith. These differences were influenced by the environmental conditions.

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 score0.779
Threshold uncertainty score0.083

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 head0.035
GPT teacher head0.210
Teacher spread0.175 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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