Stability Analysis in Plant Breeding

Becker, Heiko C.; Léon, J.

doi:10.1111/j.1439-0523.1988.tb00261.x

Cited by 816 publications

(744 citation statements)

References 72 publications

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“…We found significant positive rank correlations between gy and the nonparametric S i (3) , S i (6) and TOP statistics (Table 4), supporting the findings of Becker and Leon (1988) who also reported high rank correlations between gy and the Si (3) and Si (6) statistics. Selection for increased grain yield in bread wheat would, therefore, be expected to change grain yield stability by increasing the S i (3) , S i (6) and TOP stability statistics.…”

Section: The Relationship Between the Four Different Sets Of Stabilitsupporting

confidence: 79%

“…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: Resultsmentioning

confidence: 99%

“…This concept of stability is not acceptable to most breeders and agronomists, who prefer genotypes with high mean yields and the potential to respond to agronomic inputs or better environmental conditions (Becker, 1981). The high yield performance of released varieties is one of the most important targets of breeders, which explains why they prefer a dynamic concept of stability (Becker and Leon, 1988).…”

Section: Introductionmentioning

confidence: 98%

“…On the basis of this idea, genotypes with a minimal variance for yield across different environments are considered stable. This idea of stability may be considered as a biological or static concept of stability (Becker and Leon, 1988). This concept of stability is not acceptable to most breeders and agronomists, who prefer genotypes with high mean yields and the potential to respond to agronomic inputs or better environmental conditions (Becker, 1981).…”

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: The Relationship Between the Four Different Sets Of Stabilitsupporting

confidence: 79%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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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“…In the third step, each combination between treatments and seasons was considered an environment (E) for the estimation of stability and adaptability of clones. The dynamic concept of stability was applied for all the (Becker and Leon 1988). This concept recognizes a specific set of tested genotypes and equals Type II stability with high goodness of fit (Lin et al 1986).…”

Section: Methodsmentioning

confidence: 99%

Genotype × environment interaction and selection for drought adaptation in sweetpotato (Ipomoea batatas [L.] Lam.) in Mozambique

et al. 2016

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Sweetpotato is grown throughout the year in Mozambique but drought affects storage root yield and biomass productivity. The objectives of this research were to estimate the impact of genotype 9 environment interactions (G 9 E) in sweetpotato and select genotypes based on drought indices such as geometric mean, percent yield reduction, drought sensitivity index and harvest index. A total of 58 clones were evaluated during the dry season of 2006, 2008 and 2009. Two treatments were applied for this multi-year trial: full irrigation and without irrigation at the middle of root initiation growth stage. The field layout was a randomized complete block design with three replications. 'Jonathan', 'Resisto' and 'Tanzania' were the check cultivars in each treatment. Storage root and vine yields were recorded at harvest in the trials. Harvest index was computed from the yield data. The analysis of variance, regression and the additive main effects multiplicative interaction (AMMI) analyses, plus phenotypic coefficient of variation and ecovalence were used for dissecting the G 9 E and assessing the stability of each clone. Treatment, genotype 9 treatment and genotype 9 year (G 9 Y) interactions had highest contributions to the variation in storage root yield observed among clones. The stability of harvest index was significantly correlated with the absolute AMMI's IPCA1 and IPCA2 values for storage root yield. Cultivar performance varied within treatments. Four clones had significantly higher storage root yield (t ha -1 ) than 'Tanzania', the best check cultivar under drought. In conclusion, storage root yield (t ha -1 ) was negatively affected by drought and G 9 Y interaction. Harvest index stability and the geometric mean may be key to identify clones with storage root yield stability and high storage root yield under both treatments. At least two environments should be used at early breeding stages to consider harvest index in the early breeding cycle.

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Quantitative Trait Loci: Separating, Pyramiding, and Cloning

1997

Plant Breeding Reviews

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Stability Analysis in Plant Breeding

Cited by 816 publications

References 72 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.)

Genotype × environment interaction and selection for drought adaptation in sweetpotato (Ipomoea batatas [L.] Lam.) in Mozambique

Quantitative Trait Loci: Separating, Pyramiding, and Cloning

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