A comparison of univariate and multivariate methods to analyze G×E interaction

Flores, Fernando; Moreno, M. T.; Cubero, J. I.

doi:10.1016/s0378-4290(97)00095-6

Cited by 216 publications

(197 citation statements)

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“…In contrast, GY was not associated with ω i ; σ ˆ2 di ; IPCA1 and with stability analysis by GGE biplot, indicating that stable genotypes are not necessarily more productive, a fact also reported by Franceschi et al (2010). Flores et al (1998) reported that methodologies which measure genotype performance, by integrating GY and stability, are strongly associated with GY. The static concept of stability refers to the constancy of genotype performance across environments, unresponsive to environmental enhancement, whereas the dynamic concept refers to the GY response of the genotype parallel to the average genotypes tested in each environment (Annicchiarico 2002).…”

Section: Resultsmentioning

confidence: 80%

Statistical methods to study adaptability and stability of wheat genotypes

et al. 2017

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Section: Resultsmentioning

confidence: 80%

Statistical methods to study adaptability and stability of wheat genotypes

et al. 2017

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“…Scapim et al (2000) also found significantly positive correlations between the S i (1) , S i (2) and S i (3) nonparametric statistics. Similarly, Flores et al (1998) reported high rank correlations between S i (1) and S i (2) in faba bean (Vicia faba L.) and pea (Pisum sativum L.). Consequently, only one of these statistics would be sufficient to select the stable genotypes in a breeding program.…”

Section: The Relationship Between the Four Different Sets Of Stabilitmentioning

confidence: 85%

“…In fact, there are several reasons to prefer nonparametric stability models, one being that outlier bias is avoided and no assumptions are needed about the distribution of the data and the second is that nonparametric statistics are easy to use and to interpret. Based on these considerations, it appears that the estimation of stability is an appropriate approach for GEI analysis, this view being supported by the fact that a variety of parametric and nonparametric stability measures have been compared in the literature (Lin et al, 1986;Flores et al, 1998;Sabaghnia et al, 2006).…”

Section: The Relationship Between the Four Different Sets Of Stabilitmentioning

confidence: 99%

“…A genotype is considered stable if its kr or gy value is relatively consistent in all the environments. i.e., showing low kr or high gy and having a low σr (Flores et al, 1998). The σr, calculated from the yield rank of genotypes in each environment (r ij ) based on the uncorrected mean yield values (X ij ), is expressed as All the stability statistics were compared using Spearman's rank correlation (Steel and Torrie, 1980).…”

Section: S Imentioning

confidence: 99%

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Nonparametric stability methods for interpreting genotype by environment interaction of bread wheat genotypes (Triticum aestivum L.)

Akçura¹,

Kaya²

2008

Genet. Mol. Biol.

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Evaluation of performance stability and high yield is essential for yield trials conducted in different environments. We determined the stability of 10 bread wheat (Triticum aestivum L.) genotypes (5 cultivars and 5 advanced lines) using nonparametric stability measures and compared nonparametric stability statistics across 19 environments in the Central Anatolian Region of Turkey. Experiments were setup in a randomized complete block design with four replications. Nonparametric stability measures revealed that AL-2, Karahan-99 and Altay-2000 were the most stable and well adapted genotypes across the 19 environments. In addition, it was concluded that graphs of mean grain yield (t ha -1 ) vs. nonparametric measures (S i (1) , S i (2) , S (3) , S i (6) and σgy) values and kr vs. σr values could enhance visual efficiency of genotype selection based on genotype by environment interaction. Furthermore, high TOP values, S i (3) and S i (6) were associated with high grain yield, but the other nonparametric stability measures were not positively correlated with grain yield and instead characterized a static concept of stability. Choice of genotype for increased grain yield in bread wheat would, therefore, be expected to change yield stability by increasing the values of the S i (3) , S i (6) and TOP nonparametric stability statistics.

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“…-Mean value (M) of each trait: a genotype was classified as the most favourable if its mean value was relatively consistent in all the environments (Ketata et al 1989;Flores et al 1998). …”

Section: Univariate Analysismentioning

confidence: 99%

Assessment of field pea (Pisum sativum L.) grain yield, aerial biomass and flowering date stability in Mediterranean environments

Iglesias-García

Prats

Flores³

et al. 2017

Crop Pasture Sci.

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Mediterranean environments are of most interest to study pea adaptability to terminal drought conditions especially in the current context of global climate change. In our work we have tested 9 pea cultivars in five South European and North African locations, characterized by different agro climatic conditions within the Mediterranean climate. Data were processed through the additive main effects and multiplicative interaction (AMMI) analysis. Grain yield, aboveground biomass and flowering date were assessed within each Mega Environment (ME) with parametric and non-parametric methods, establishing ranks for the genotypes within each condition attending to their stability parameters and mean values. The field analysis revealed HR1 as a wide adapted genotype, whereas others such as Desso showed the best adaptation in South Mediterranean areas. Our results also highlighted the potential interest of these genotypes and others (i.e. Messire and ZP108) in breeding programs and further studies on drought tolerance.Additional Keywords: dry pea, phenology, Genotype × Environment interaction, drought tolerance Pea behaviour in Mediterranean field environments 5 IntroductionDry pea (Pisum sativum L.) is the most widely grown temperate grain legume in Europe and the second-most in the world (FAOSTAT 2013), being a versatile and inexpensive protein source for animal feeding with a widely acknowledged beneficial role in cropping systems (Drinkwater et al., 1998; Badgley et al., 2006;Nemecek et al. 2008). In spite of these advantages, dry pea acreage shows a constantly decreasing trend at a world level from 10.3 million ha in 1962 to 6.3 ha in 2012 (Rubiales and Mikic 2015).Yield variability and instability are the major problems for pea both within and between sites and seasons due to a poor adaptability and a low tolerance to biotic and abiotic stress (Moot et al. 1995;Jacobsen et al. 2012). Significant efforts have been made in pea breeding for adaptability to continental and oceanic conditions (Cousin 1997). In contrast, little efforts have been paid to improve adaptability to Mediterranean environments with mild winters and dry springs, where spring pea types are autumn sown and challenged by different stresses (Rubiales et al. 2009). As a result, pea cultivation is particularly low in the Mediterranean Basin and recently released pea cultivars are poorly adapted to Mediterranean environments (Rubiales 2015). This is somehow surprising as the East Mediterranean and the West Asia are the primary centre of diversity for pea, where wild forms, such as P. fulvum Sm. and P. sativum subsp. elatius (M. Bieb.) Asch. and Graebn can still be found growing today (Rubiales et al. 2011; and where pea once played a very important role in human diets, as witnessed by the first attested ancient DNA extraction from any legume species Medović et al. 2011).In field conditions, the development of pea genotypes producing high and stable seed yield is most decisive (Cousin, 1997;Rubiales et al. 2011;Smýkal et al. 2012), albeit high...

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A comparison of univariate and multivariate methods to analyze G×E interaction

Cited by 216 publications

References 42 publications

Statistical methods to study adaptability and stability of wheat genotypes

Statistical methods to study adaptability and stability of wheat genotypes

Nonparametric stability methods for interpreting genotype by environment interaction of bread wheat genotypes (Triticum aestivum L.)

Assessment of field pea (Pisum sativum L.) grain yield, aerial biomass and flowering date stability in Mediterranean environments

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