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Record W2328678519 · doi:10.4141/cjps2013-386

Evaluation of genotype×environment interaction and stability of corn hybrids and relationship among univariate parametric methods

2014· article· en· W2328678519 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 · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsnot available
Fundersnot available
KeywordsUnivariateStability (learning theory)StatisticsMathematicsHybridAdaptabilityGrain yieldGene–environment interactionPrincipal component analysisRank (graph theory)Parametric statisticsAnalysis of varianceCoefficient of variationRank correlationGenotypeBiologyMultivariate statisticsAgronomyEcologyGeneticsComputer scienceCombinatorics

Abstract

fetched live from OpenAlex

Changizi, M., Choukan, R., Heravan, E. M., Bihamta, M. R. and Darvish, F. 2014. Evaluation of genotype×environment interaction and stability of corn hybrids and relationship among univariate parametric methods. Can. J. Plant Sci. 94: 1255–1267. There have been many approaches available in multi-location crop variety trial. However, the relationship among these approaches is not understood. In this study, therefore, grain yields of 16 corn hybrids were measured in 12 locations in Iran in 2011 and 2012 in order to compare the 23 parametric methods and to assess stability and adaptability of the hybrids. The combined ANOVA indicated that variances due to the genotypes, environments and genotype×environment interaction were substantially significant, which represents great variation among them. Principal component analysis based on rank correlation matrix indicated that stability methods can be classified into four groups. The group related to the dynamic concept and strongly associated with mean grain yield consisted of the measures, superiority index (Pi), desirability index (DI), geometric adaptability index (GAI) and genotypic stability (Di 2 ). This group was more useful in agronomic goals in comparison with other methods. The second group also indicated the dynamic concept contained slope of regression models. The third group reflected the static concept included, the environmental variance (EV), the variance in regression deviation (S 2 di) and type IV stability concept ([Formula: see text]). The fourth group impressed concurrently by grain yield and stability included the measures coefficient of variability (CV), Wrick's ecovalence (W2), Shukla's stability variance (SH), Plaisted and Peterson's parameter (pp59), Plaisted's parameter (p60), yield reliability index (Ii), residual MS of regression models and coefficient of determination (R 2 ). Based on both concepts of stability (dynamic and static), hybrids (KLM76002/3×MO17), (KLM77002/10-5-1×K19/1) and (K47/2×MO17) were the most stable and (KSC704), (KSC720 (K74/1×K19)) and (K48/3×K18) were found to be the most adaptable to favorable environments. The methods of Pi, Di 2 , DI and GAI were more useful and more convenient than other methods. [Formula: see text] and [Formula: see text] showed an acceptable static concept of stability methods whereas study [Formula: see text] was more efficient than [Formula: see text].

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 head0.097
GPT teacher head0.267
Teacher spread0.171 · 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