Studies on Estimation of Phenotypic Stability: Tests of Significance for Nonparametric Measures of Phenotypic Stability

Nassar, Raja; Hühn, M.

doi:10.2307/2531947

Cited by 229 publications

(299 citation statements)

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“…The genotypes were distributed in the different sections of Figures 1 and 2 as follows: section 1 contained the Karahan-99, Altay-2000 and AL-2 genotypes, which can be considered to be the most stable and well adapted genotypes in all environments (i.e., had general adaptation ability); section 2 contained the Gerek-79 and AL-3 genotypes, which were assumed to be sensitive to environmental changes and to be more specific with regard to their adaptability to highyielding environments; section 3 contained the Bagci-2002, AL-1 and AL-5 genotypes, which appeared to be poorly adapted in all the environments; and section 4 contained the Yakar-99 and AL-4 genotypes, which showed greater resistance to environmental fluctuation and therefore increasing specificity of adaptability to low-yielding environments. Regarding the choice between the S i (1) and S i (2) statistic, Nassar and Huehn (1987) suggest that the S 1…”

Section: Resultsmentioning

confidence: 99%

“…One of them (Huehn, 1979;Nassar and Huehn, 1987) consisted of four nonparametric stability statistics (S i (1) , S i (2) , S i (3) and S i (6) ) combining mean yield and stability (see also Becker and Leon, 1988 Two-way data with k genotypes and q environments used r ij as the rank of the i th genotype in the j th environment and r i as the mean rank across all environments for the i th genotype, the equations used being as follows:…”

Section: Discussionmentioning

confidence: 99%

“…(2) , between-ranks variance over n environments (Huehn, 1990a) The significance tests for the S i (1) and S i (2) statistics were determined as suggested by Nassar and Huehn (1987). The chi-square (χ 2 ) values associated with S i (1) and S i…”

Section: S Imentioning

confidence: 99%

“…The other approach is to use nonparametric techniques, and several procedures have been proposed based on comparing ranks of genotypes in each environment, with genotypes with similar ranking across environments being considered stable (Huehn, 1979;Nassar and Huehn, 1987;Kang, 1988;Ketata et al, 1989;Fox et al, 1990). The following four nonparametric measures of phenotypic stability have been proposed by Huehn (1979) and Nassar and Huehn (1987): S i (1) , the genotype absolute rank difference mean as tested over n environments; S i (2) , the between-ranks variance over the n environments; S i (3) , the sum of the absolute deviations of the squares of ranks for each genotype; and S i (6) , the sum of the squares of ranks for each genotype relative to the mean of ranks.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: S Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…-Si (1) , Si (2) , Si (3) and Si (6) : non parametric statistics (Huehn 1979;Nassar and Huehn 1987) combining mean yield and stability (Becker and Leon 1988). S (1) and S (2) are based on ranks of genotypes across environments and give equal weight to each environment, whereas S (3) and S (6) combine yield and stability based on variable´s ranks of the genotypes in each environment (Nassar and Huehn 1987).…”

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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Quantitative Genetics of Forest Trees

Namkoong

Kang

1990

Plant Breeding Reviews

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Studies on Estimation of Phenotypic Stability: Tests of Significance for Nonparametric Measures of Phenotypic Stability

Cited by 229 publications

References 10 publications

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

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

Quantitative Genetics of Forest Trees

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