Comparison of Non Parametric Stability Statistics for Improvement of Adaptation in Wheat-Rye Disomic Addition Lines

2014 ◽  
Vol 4 (22) ◽  
pp. 3409-3419
Author(s):  
Ezatollah Farshadfar
Keyword(s):  
Addition Lines ◽  
Parametric Stability ◽  
Disomic Addition Lines ◽  
Stability Statistics ◽  
Non Parametric

scholarly journals Comparison of Non-parametric Stability Statistics for Selecting Stable and Adapted Soybean Genotypes under Different Environments

2019 ◽  
pp. 1-16
Author(s):  
E. F. El-Hashash ◽  
S. M. Tarek ◽  
A. A. Rehab ◽  
M. A. Tharwat
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Rank Correlation ◽  
Static Stability ◽  
Parametric Stability ◽  
Spearman’S Rank Correlation ◽  
Ammi Analysis ◽  
Soybean Genotypes ◽  
Stability Statistics ◽  
Non Parametric

The objectives of this study were to investigate the comparison among non-parametric stability statistics and to evaluate seed yield stability of the sixteen soybean genotypes across four locations during the 2016, 2017 and 2018 growing seasons in Egypt. All trials were laid down in a randomized complete block design (RCBD) with three replications. The AMMI analysis showed ahighly significant effect of genotype (G), environment (E) and G x E interaction (GEI). The major contributions to treatment sum of squares were GEI, followed by G and E. The AMMI analysis also partitioned the total GEI component into eleven PCAs and Residual. The first eight PCAs were highly significant and accounted for about 99.56% of the total GEI. Based on the static and dynamic concepts, the results of spearman’s rank correlation and PCA showed that stability measures could be classified into three groups. The non-parametric stability statistics i.e., YSi, KR, TOP, RSM and δgy related to the dynamic concept and strongly correlated with mean seed soybean yield of stability. While, the other non-parametric stability statistics (Si(1) ,Si(2) ,Si(3)  and Si(6),NPi(1) ,NPi(2) ,NPi(3) and NPi(4)  , δr, MID, LOW) represented the concept of static stability, which were influenced simultaneously by both yield and stability. The non-parametric stability statistics in each the groups I, II, and III were positively and significantly correlated with each other, thus; any of these parameters could be considered as appropriate alternatives for each other. According to cluster analysis, soybean genotypes G6, G4, G8, G11, G9, G1, G7 and G2 were more stable varieties on the basis of mean seed yield and non-parametric stability statistics. In conclusion, both yield and stability should be considered simultaneously to exploit the useful effect of GEI and to make the selection of genotypes more precise and refined. Thus, the YSi, KR, TOP, RSM and δgy were more useful statistics in soybean breeding programmes and could be useful alternatives to parametric stability statistics. According to most non-parametric stability statistics, the genotypes G6 and G11 were more stable coupled with high seed yield; therefore, these genotypes might be used for genetic improvement of soybean and they must be released in studied regions and other regions in Egypt.

scholarly journals STABILITYSOFT: A new online program to calculate parametric and non-parametric stability statistics for crop traits

2019 ◽  
Vol 7 (1) ◽  
pp. e01211 ◽  
Author(s):  
Alireza Pour-Aboughadareh ◽  
Mohsen Yousefian ◽  
Hoda Moradkhani ◽  
Peter Poczai ◽  
Kadambot H. M. Siddique
Keyword(s):  
Online Program ◽  
Parametric Stability ◽  
Stability Statistics ◽  
Non Parametric

scholarly journals Non-parametric stability analyses of protein content in multi-environment trials of wheat (T. aestivum L.)

Genetika ◽  
2015 ◽  
Vol 47 (3) ◽  
pp. 795-810 ◽  
Author(s):  
Yuksel Kaya ◽  
Mehmet Sahin
Keyword(s):  
Standard Deviation ◽  
Protein Content ◽  
Parametric Stability ◽  
Ge Interaction ◽  
Stability Parameters ◽  
Breeding Lines ◽  
Wide Range ◽  
The Stability ◽  
Stability Statistics ◽  
Non Parametric

According to literature, a detailed paper has not been published yet on using non-parametric stability statistics for evaluating genotypic stability in protein content (PC) of wheat. Thus, this study aimed to investigate the stability for PC of wheat using sixteen non-parametric stability measures (YSD-PC standard deviation, RM-Rank mean, RSD-Rank?s standard deviation, RS-Rank Sum stability statistic, PA-Percentage of adaptability, R1 and R2-Range indexes, TOP-Ranking, Si(1), Si(2), Si(3), Si(6), NPi(1), NPi(2) NPi(3)and NPi(4) rank statistics, together with Y-PC mean). The study included 13 wheat genotypes, consisting of 5 registered cultivars and 8 breeding lines, selected from National Wheat Breeding Program of Turkey. The genotypes were grown in ten rain-fed environments, representative of major rain-fed wheat-growing areas of Turkey, during 2011-2013 cropping seasons. The ANOVA showed that the effects due to environments (E), genotypes (G) and GE interaction (GEI) were significant (P < 0.01). Spearman?s rank correlation and principal component analyses (PCA) also revealed that two types of associations were found between the stability parameters: the first type included Si(1), Si(2), Si(3), Si(6), NPi(1), NPi(2) NPi(3), NPi(4), RSD and YSD parameters which were related to static stability, whereas the second type consisted of the Y, RM, TOP, PA, RS, R1 and R2 parameters which are related to dynamic concept of stability. Among the 8 breeding lines, G7 and G8 were the best genotypes in terms of both high PC and stability. In conclusion it could be suggested that dynamic non-parametric stability statistics should be used for selecting genotypes with high PC and stable when tested across a wide range of environments.

scholarly journals Non-Parametric Stability Analysis of Tuber Yield in Potato (Solanum tuberosum L.) Genotypes

2018 ◽  
Vol 10 (28) ◽  
pp. 50-63
Author(s):  
mina moghaddaszadeh ◽  
Rasool Asghari Zakaria ◽  
Davoud Hassanpanah ◽  
naser zare ◽  
◽  
...  
Keyword(s):  
Solanum Tuberosum ◽  
Stability Analysis ◽  
Tuber Yield ◽  
Solanum Tuberosum L ◽  
Parametric Stability ◽  
Non Parametric

scholarly journals Development of new PCR-based markers specific for chromosome arms of rye (Secale cereale L.)

Genome ◽  
2016 ◽  
Vol 59 (3) ◽  
pp. 159-165 ◽  
Author(s):  
Ling Qiu ◽  
Zong-xiang Tang ◽  
Meng Li ◽  
Shu-lan Fu
Keyword(s):  
Secale Cereale ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Addition Lines ◽  
Breeding Programs ◽  
Effective Utilization ◽  
Secale Cereale L ◽  
Monosomic Addition ◽  
Monosomic Addition Lines ◽  
Disomic Addition Lines

PCR-based rye (Secale cereale L.) chromosome-specific markers can contribute to the effective utilization of elite genes of rye in wheat (Triticum aestivum L.) breeding programs. In the present study, 578 new PCR-based rye-specific markers have been developed by using specific length amplified fragment sequencing (SLAF-seq) technology, and 76 markers displayed different polymorphism among rye Kustro, Imperial, and King II. A total of 427 and 387 markers were, respectively, located on individual chromosomes and chromosome arms of Kustro by using a set of wheat–rye monosomic addition lines and 13 monotelosomic addition lines, which were derived from T. aestivum L. ‘Mianyang11’ × S. cereale L. ‘Kustro’. In addition, two sets of wheat–rye disomic addition lines, which were derived from T. aestivum L. var. Chinese Spring × S. cereale L. var. Imperial and T. aestivum L. ‘Holdfast’ × S. cereale L. var. King II, were used to test the chromosomal specificity of the 427 markers. The chromosomal locations of 281 markers were consistent among the three sets of wheat–rye addition lines. The markers developed in this study can be used to identify a given segment of rye chromosomes in wheat background and accelerate the utilization of elite genes on rye chromosomes in wheat breeding programs.

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