Sasg × estab: A sas program for computing genotype × environment stability statistics

Hussein, Mohammed Ali; Bjørnstad, Åsmund; Aastveit, Are H.

doi:10.2134/agronj2000.923454x

Cited by 71 publications

(40 citation statements)

References 38 publications

(41 reference statements)

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“…A detailed explanation on mathematical basis of AMMI analysis and its interpretations has been presented by Hussein et al (2000). All analyzes performed using SAS GLM procedures (SAS Institute, 1999).…”

Section: Methodsmentioning

confidence: 99%

Stability Analyses for Seed Yield of Chickpea (Cicer arietinum L.) Genotypes in the Western Cold Zone of Iran

Kanouni¹,

Farayedi²,

Saeid³

et al. 2015

JAS

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Different methods have been developed to estimate of genotype by environment interaction (GEI) in crop plants. In this study, 14 kabuli type chickpea genotypes were assessed for seed yield in four stations over three successive years (2010)(2011)(2012)(2013) at west highlands of Iran. Randomized complete block design was used in all test environments with four replicates. Combined analysis of variance for seed yield revealed significant differences between genotypes, locations, and interaction between these two sources. The mean seed yield of genotypes averaged over environments showed that V4 and V2 had the highest (1163.58 kg ha -1 ) and the lowest seed yield (759.07 kg ha -1 ), respectively. Significant GE interaction implied that chickpea genotypes had various responses to different environments and, the stability analysis could be performed. To investigate GEI and identify the best performing stable genotypes, several stability parameters were employed. According to Wricke's ecovalance, stability variance, Plaisted method, and genotypic stability V5, V8 and V3 were the most stable genotypes. Based on CV, regression coefficient and MS(GE), V1 and V5 found to be stable and adapted to diverse environments, and the other genotypes distributed among stability statistics. Based on the AMMI biplot, 12 test environments divided into two mega environments. These mega environments included very cold districts like Maragheh and similar areas, and relatively softened regions of Kurdistan and similar environments. For these two mega environments, V6 and V4 showed more adaptability, respectively. In conclusion, the two genotypes, V4 (FLIP 00-39C) and V6 (FLIP 99-26C) could be recommended as new cultivars to chickpea farmers for autumn sowing in west areas of Iran.

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Section: Methodsmentioning

confidence: 99%

Stability Analyses for Seed Yield of Chickpea (Cicer arietinum L.) Genotypes in the Western Cold Zone of Iran

Kanouni¹,

Farayedi²,

Saeid³

et al. 2015

JAS

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“…For calculation of these nonparametric stability statistics, SAS-based computer programs of Lu (1995) and Hussein et al (2000) were used.…”

Section: Nonparametric Statistical Methodsmentioning

confidence: 99%

Graphic analysis of yield stability in new improved lentil (Lens culinaris Medik.) genotypes using nonparametric statistics

Sabaghnia

Karimizadeh²,

Mohammadi³

2015

AAS

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Yield stability is an interesting feature of today’s lentil breeding programs, due to the high annual variation in mean yield, particularly in the arid and semi-arid areas. The genetic effects including genetic main and genotype × environment (GE) interaction effects for grain yield of eighteen lentil (Lens culinaris Medik.) genotypes were studied with fourteen nonparametric stability statistics. Results of five distinct nonparametric tests of GE interaction and combined ANOVA showed there were both additive and crossover interaction types and genotypes varied significantly for grain yield. According to most of the nonparametric stability statistics, genotypes G5, G6, G8 and G18 were the most stable genotypes. Considering mean yield versus stability values via their plotting, indicates that genotypes G2, G11 and G14 following to G5, G16 and G18 were the most favorable genotypes. None of the nonparametric stability statistics were correlated with mean yield and so had static concept of stability. Our results confirmed that rankings of genotypes within environments and using mean yield information permit ease of interpretation of nonparametric results. Finally genotypes G2 (FLIP 92-12L), G11 (Gachsaran) and G14 (ILL 6206) were found to be the most stable and high mean yielding genotype and thus recommended for commercial release. Such an outcome could be used to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for lentil and other crops.

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“…NPSSs were done using SAS codes proposed by Hussein et al (2000) for S i (3) and S i (6) (Huehn, 1996), RS (Kang, 1988), and TDP (Fox et al, 1990) and by Lu (1995) for S i (1) and S i (2) (Huehn, 1996). The other NPSSs, RM and RSD (Ketata, 1988) were estimated using Excel©.…”

Section: Discussionmentioning

confidence: 99%

Non-parametric stability analyses of dough properties in wheat

Kaya¹,

Şahin²

2015

Food Sci. Technol

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Literature has unveiled that a paper has not been published yet on using non-parametric stability statistics (NPSSs) for evaluating genotypic stability in dough properties of wheat. Accordingly, the effects of genotype (G), environment (E) and GE interaction (GEI) on alveograph parameters, i.e. dough baking strength (W) and its tenacity (P)/extensibility (L), of 18 wheat (T. aestivum L.) genotypes were studied under irrigated field conditions in an 8-year trial (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) in central Turkey. Furthermore, genotypic stability for W and P/L was determined using 8 NPSSs viz. RM-Rank mean, RSD-Rank's standard deviation, RS-Rank Sum, TDP-Ranking, S i (1) , S i (2) , S i (3) and S i (6) rank statistics. The ANDVA revealed that W and P/L were primarily controlled by E, although G and GEI also had significant effects. Among the 8 NPSSs, only RM, RS and TDP statistics were suitable for detecting the genotypes with high stable and bread making quality (e.g. G1 and G17). In conclusion, using RM, RS and TDP statistics is advisable to select for dough quality in wheat under multi-environment trials (METs).

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Sasg × estab: A sas program for computing genotype × environment stability statistics

Cited by 71 publications

References 38 publications

Stability Analyses for Seed Yield of Chickpea (Cicer arietinum L.) Genotypes in the Western Cold Zone of Iran

Stability Analyses for Seed Yield of Chickpea (Cicer arietinum L.) Genotypes in the Western Cold Zone of Iran

Graphic analysis of yield stability in new improved lentil (Lens culinaris Medik.) genotypes using nonparametric statistics

Non-parametric stability analyses of dough properties in wheat

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