Identification of the most stable genotypes in multi-environment trials by using nonparametric methods

Sabaghnia, Naser

doi:10.14720/aas.2015.105.1.11

Cited by 7 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The genotypic classification (Thillainathan and Fernandez, 2002) or GC identified G1, G2, G13 and G18 as the most stable genotypes (Table 5) which were the high yielding genotypes. The first nonparametric statistic of Sabaghnia (2015), NS1, introduced genotypes G6, G10 and G12 as the most stable genotypes while the second nonparametric statistic (NS2) introduced genotypes G3, G4 and G10 as the most stable genotypes (Table 5).…”

Section: Resultsmentioning

confidence: 99%

“…Also, this SAS macro program computes S1, S2, S3, S6 of Hühn (1979), RS of Kang (1988), Top, Mid and Low indices of Fox et al (1990), and NP1, NP2, NP3 and NP4 of Thennarasu (1995). The percent adaptability (PA) statistic of St-Pierre et al (1967), S4 and S5 of Hühn (1979), RN1 and RN2 of Langer et al (1979, KR1 and KR2 of Ketata et al (1989), S7 of Huehn (1990a, Li and Ri of Piepho and Lotito (1992), and NS1 and NS2 of Sabaghnia (2015) were calculated via spreadsheet program of Microsoft Excel software. Most of these nonparametric statistics tests have been described in detail by Sabaghnia (2016).…”

Section: Methodsmentioning

confidence: 99%

“…OF BARLEY TRIALS BASED ON RANKS Table 5. Nonparametric stability statistics of Thennarasu (1995), Kang and Magari (1996), Harfouche (2000), Thillainathan and Fernandez (2002) Thennarasu (1995); YSI, yield stability index (Kang and Magari, 1996); RII, relative interactivity index (Harfouche, 2000); GC, genotypic classification (Thillainathan and Fernandez, 2002); NS1 and NS2, nonparametric statistics of Sabaghnia (2015).…”

Section: Behrouz Vaezi Et Al: Nonparametric Analysis Of Genotype Grai...mentioning

confidence: 99%

“…Thillainathan and Fernandez (2002) suggested genotypic classification (GC) to classify genotypes evaluated under multiple environments by classification of the environments into three classes, low, medium and high; and then grouping of genotypes into three groups, low, medium and high in each environmental class. Sabaghnia (2015) discussed two nonparametric statistics (NS1 and NS2) for yield stability analysis according to nonparametric dispersion indices, inter-quartile range and inter-decile range and nonparametric central tendency index as median. Stability statistics based on ranks need no statistical assumptions about the distribution of the values, are easy to use and interpret and compared with parametric methods, are less sensitive to errors of measurement (Sabaghnia and Janmohammadi, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Nonparametric Analysis of Genotype Grain Yield Performance of Barley Trials Based on Ranks

Vaezi,

Sabgahnia,

Mehraban

et al. 2022

RAR

View full text Add to dashboard Cite

Plant breeding has been concerned with genotype by environment (GE) interaction and high yielding genotypes with stable performance are desirable while this target is difficult to achieve due to high environmental variations and unpredictable GE interaction. Stability of grain yield performance of 18 barley genotypes was evaluated at 5 locations for 3 years in the rainfed conditions and it was studied through 25 nonparametric stability methods. Four nonparametric tests indicated highly significant GE interaction due to differential performance of genotypes across fifteen environments. Regarding mean yield and six Hühn’s statistics, genotype G12 (1946 kg ha-1) was the most favorable genotype while based on the RN1, G4, G10 and G11 were the most stable genotypes. Genotypes G4, G8 and G10 were the most favorable genotypes according to rank-sum while genotypes G2, G13 and G18 were the most favorable genotypes based on nonparametric superiority. The relative interactivity index identified G4, G16 and G8 as the most stable genotypes while the genotypic classification identified G1, G2, G13 and G18 as the most stable genotypes. Clustering of the nonparametric stability methods indicated that there were two groups with different static and dynamic characteristics. In this study, five nonparametric stability methods as GC, FM, PA, RN2 and KR2 were associated with high grain yield and reflected the dynamic concept of stability, but the other twenty nonparametric stability methods were not positively correlated with yield and characterized a static concept of stability. Finally, genotypes genotype G13 (2114.13 kg ha-1) and G18 (2062.69 kg ha-1) were found to be the most favorable genotypes and are thus recommended for commercial release in semiarid areas of Iran.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Behrouz Vaezi Et Al: Nonparametric Analysis Of Genotype Grai...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonparametric Analysis of Genotype Grain Yield Performance of Barley Trials Based on Ranks

Vaezi,

Sabgahnia,

Mehraban

et al. 2022

RAR

View full text Add to dashboard Cite

show abstract

“…GEI is defined as an inconsistent performance of genotypes across different environments (Zakir 2018). This confounds the evaluation of genotypes in many environments difficult because some genotypes may perform well in one environment but poor in another (Eberhart and Russell 1966;Sabaghnia 2015). According to Thillainathan and Fernandez (2002), cultivars that perform well across a wide range of testing locations and years are recommended and released.…”

Section: Introductionmentioning

confidence: 99%

Heritability for Morphological Traits Determine Adaptability of Elite Cowpea Genotypes in different Environments

Asiwe¹

2021

IJAB

View full text Add to dashboard Cite

Lack of improved and high-yielding adapted varieties constitutes limitation to cowpea (Vigna unguiculata (L.) Walp) production in South Africa. Therefore, field trials were conducted in two locations (the University of Limpopo Experimental Farm, (Mankweng) and Towoomba Research Station, Bela-Bela) during 2015–16 and 2016–17, to assess yield components, genotype x environment interaction as well as the adaptability of elite cowpea genotypes. The experiment was laid out using a randomized complete block design in three replications. Data were collected on flowering, maturity and yield components. Results revealed that “genotype, and genotype × year and genotype × location interactions were significant for most of the traits evaluated”. „The days to 50% flowering‟ and „90% maturity‟ ranged between 53 and 60 days, and between 89 and 96 days, respectively. The „100-seed weight‟ varied from 15.8 g to 22.5 g. „Broad-sense heritability‟ varied from 0 to 93% for days to maturity and grain yield, respectively. „Grain yield‟ varied from 1465.7 to 2594.9 kg ha-1, and the best yielders were lines „L2‟, „L10‟, and „L7‟. The „PC1‟ and „PC2‟ explained 82.57% variation for maturity, 79.12% for the „pods per plant‟, 83.78% for „seeds per pod‟, 93.09% for „100-seed weight‟ and 95.84% for „grain yield‟. Towoomba was a more productive location compared to Sykerfuil. Lines „L2‟, „L10‟, and „L7‟ yielded very well in both locations and years. This implies that they are adapted and are recommended for registration and commercial release in the region. © 2021 Friends Science Publishers

show abstract

Evaluating leaf rust reactions of pure bread wheat landrace lines using non-parametric statistics

Hocaoğlu

Akan²,

Akçura

2020

Phytoparasitica

View full text Add to dashboard Cite

Identification of the most stable genotypes in multi-environment trials by using nonparametric methods

Cited by 7 publications

References 26 publications

Nonparametric Analysis of Genotype Grain Yield Performance of Barley Trials Based on Ranks

Nonparametric Analysis of Genotype Grain Yield Performance of Barley Trials Based on Ranks

Heritability for Morphological Traits Determine Adaptability of Elite Cowpea Genotypes in different Environments

Evaluating leaf rust reactions of pure bread wheat landrace lines using non-parametric statistics

Contact Info

Product

Resources

About