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Record W2253525880 · doi:10.4141/cjps09102

Relationships of phenotypic stability measures for genotypes of three cereal crops

2010· article· en· W2253525880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Plant Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsnot available
Fundersnot available
KeywordsAmmiTriticum turgidumStability (learning theory)Hordeum vulgareGene–environment interactionBiologyAgronomySelection (genetic algorithm)Total sum of squaresMathematicsGrain yieldStatisticsSpearman's rank correlation coefficientCrop yieldCorrelationYield (engineering)Winter wheatGenotypeLinear regressionCultivarPoaceaeGenetics

Abstract

fetched live from OpenAlex

Multi-environment trial (MET) data are required to obtain stability performance parameters as selection tools for effective genotype evaluation. The main objective of this study was to investigate the interrelationships among nine phenotypic stability methods using grain yield from three sets of cereal experiments [15 durum wheat (Triticum turgidum var. durum) genotypes × 12 environments; 20 bread wheat (T. aestivum L.) genotypes × 18 environments; and 13 barley (Hordeum vulgare L.) genotypes × 18 environments]. The experiments were conducted in representative rain-fed areas of Iran in collaboration with the International Center for Agricultural Research in the Dry Areas (ICARDA). The combined ANOVA for environments (E), genotypes (G) and G × E interaction was highly significant (P < 0.01) for each set of data, suggesting differential genotypic responses and the need for stability analysis. The inter-relationships among the parameters and their association with mean yield based on Spearman’s rank correlation were determined in each of the three cereal experiments. Highly significant correlations were found between several of the stability measures indicating that several of the statistics probably measure similar aspects of phenotypic stability for these crop species. The AMMI stability value (ASV), variance of regression deviation (S 2 di ) and Wricke’s ecovalence (W 2 i ) were consistently and highly correlated with each other over these crops and, therefore, could be used if selection is to be based primarily on stability. The superiority index (Pi) and geometric adaptability index (GAI), which are related to the dynamic concept of stability showed significant correlation with mean yield over these crops, suggesting P i and GAI would be the best methods for ranking genotypes across environments. The coefficient of variation (CV), regression coefficient (b i ), yield reliability index (I i ), and environmental variance (S 2 x ) showed inconsistent relationships with either the static or dynamic concepts of stability over these crops. The correlation analysis provided a good description of static and dynamic concepts of stability for interpreting the G × E interaction and verified that the groups of stability methods (dynamic vs. static) discriminated genotypes in different fashions in these crops.

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.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.699
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.080
GPT teacher head0.207
Teacher spread0.127 · 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