Non-parametric stability analysis of sunflower oil yield trials

Balalić, Igor; Zorić, Miroslav; Miklič, Vladimir; Dušanić, Nenad; Terzić, S.; Radić, Velimir

doi:10.2298/hel1154067b

Cited by 12 publications

(14 citation statements)

References 11 publications

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“…The significant genotype × location interaction implied that the responses of the genotypes changed depending on the environmental conditions. These finding are in agreement with the results reported by Balalić and Zorić (2013). There was no significant genotype × year interaction that means genotype behavior in a location between years is not significant.…”

Section: Analysis Of Variance and Nature Of Ge Interactionsupporting

confidence: 93%

“…The studied genotypes showed cross over types of GE interaction while environments showed both cross over and non-cross over types of GE interaction (Table 3). The relative contributions of G and GE interaction effects to the total variation for grain yield found in this study are in agreement with those found in other crop adaptation studies such as cereals or food legumes in rain-fed environments (Alagarswamy and Chandra, 1998;Balalić et al, 2011;Ceccarelli and Grando, 1991;Mohammadi et al, 2007;Sabaghnia et al, 2008;Živanović et al, 2012). Therefore, it would be very difficult to achieve an indirect response to selection over all of the canola target population of environments from selection in a few environments, ignoring the observed GE interactions. )…”

Section: Analysis Of Variance and Nature Of Ge Interactionsupporting

confidence: 92%

“…These statistics ranked genotypes similarly for stability. The similarity result of these two parameters was also found in Balalić and Zorić (2013). Genotypes Licord, Okapi, Elite and Ebonite were most unstable.…”

Section: Analysis Of Variance and Nature Of Ge Interactionsupporting

confidence: 55%

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Nonparametric Stability Analysis in Multi-Environment Trial of Canola

Mortazavian¹,

Azizinia²

2014

Turkish Journal of Field Crops

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Rapeseed is the world's second most important source of vegetable oils. Development of genotypes having high seed yield with stable performance is of paramount importance. In the present investigation seventeen genotypes were grown at seven locations during two growing seasons in semi-cold regions of Iran. Data recorded on seed yield were subjected to different nonparametric measures which do not require distributional assumptions. Results of nonparametric tests of G, E and GE interaction and a combined ANOVA across environments showed there were both cross over and non-cross over interactions for G and E and only non-cross over type for GE interaction. In this study, high values of Top (proportion of environments in which a genotype ranked in the top third) and mean of rank were associated with high mean yield. However Rank-sum measure was successful to detect genotypes showing simultaneous high yield and yield stability. Cluster analysis and principal component (PC) analysis help to group genotypes and measures and they revealed association among different statistics. Finally, among nonparametric measures, Top, Si(1) and Ranksum statistics of nonparametric procedures were found to be useful in detecting the stability of the genotypes. According to these parameters Geronimo was found as stable and high yield canola genotype.

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Section: Analysis Of Variance and Nature Of Ge Interactionsupporting

confidence: 93%

Section: Analysis Of Variance and Nature Of Ge Interactionsupporting

confidence: 92%

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Nonparametric Stability Analysis in Multi-Environment Trial of Canola

Mortazavian¹,

Azizinia²

2014

Turkish Journal of Field Crops

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“…Highly significant negative correlations were found between grain yield and stability indices S i (3) and S i (6) in both progeny groups, and very strong and highly significant correlations were found between S i (3) and S i (6) values (Table 5). High values of rank correlation coefficients between S i (1) and S i (2) values were also found by DELIĆ et al (2009), FLORES et al (1998), SCAPIM et al (2000) and BALALIĆ et al, (2011). The presence of high rank correlations between stability indices S i (1) and S i (2) justifies the selection of one of them for the proper stability assessment.…”

Section: Correlations Between Yield and Non-parametric Stability Meassupporting

confidence: 58%

Non-parametric approach to the analysis of phenotypic stability of two half-sib maize populations

et al. 2018

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One of the most important phases in commercial maize breeding programs is the assessment of the value of newly-developed progeny by testing in hybrid combinations. In this study, non-parametric stability measures were applied to analyze the genotype ? environment interaction and to assess phenotypic stability of two half-sib maize populations, each consisting of 40 genotypes, across 9 variable environments. Non-parametric tests of significance determined the presence of qualitative interaction for grain yield in both observed populations. Results of the stability analysis showed no significant differences between the two progeny groups indicating that the used testers did not bring significant increase in stability in either of the analyzed half-sib populations. Individual genotypes were also compared based on grain yield stability within both progeny groups using the stability parameters Si(1), Si(2), Si(3) and Si(6). Association between the grain yield and stability indices Si(1) and Si(2) of the analyzed genotypes was presented graphically enabling the identification of genotypes which can be recommended for further breeding process as the most promising ones. The correlations between grain yield and stability parameters were tested by Spearman?s rank correlations. Both progeny groups (HS1 and HS2) showed no significant correlations between the grain yield and stability parameters Si(1) and Si(2), but the rank correlations between Si(1) and Si(2) values were very strong and highly significant. Highly significant negative correlations were found between grain yield and stability indices Si(3) and Si(6) in both progeny groups, and very strong and highly significant correlations were found between Si(3) and Si(6) values.

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“…Also, Khalili & Aboughadareh (2016) have proposed some procedures to test the GxE interaction apart from methods based on analysis of variance. Among these nonparametric procedures, stable performance of genotypes evaluated under in MET were determined by Huehns' statistics (Balalić et al, 2011;Lima et al, 2013;Farshadfar et al, 2014). The objectives of this study were to apply nonparametric measures to estimate GxE interaction in coordinated trials to identify stable dual purpose barley genotypes possess high forage and grain yield.…”

Section: Introductionmentioning

confidence: 99%