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“ADAPTABILITY AND STABILITY”
ADAPTABILITY AND STABILITY
• The success of crop improvement activities largely depend on the
identification of superior varieties for mass propagation.
• A variety can be considered superior if it has potential for high yield
under favorable environment and the same time great deal of phenotypic
stability.
• Stability of a genotype refers to its performance with respect to
changing environment factor over time within a given location.
• Adaptability is Ability to genotype to exhibit relatively stable
performance in different environment or capacity of a genotype or
population for genetic change in adaptation.
 Types of Adaptability –
1. Specific genotype adaptation – It is the close adaptation of genotype to a limited
environment.
2. General genotypic adaptation – It is refers to the capacity of a genotype to
produce a wide range of phenotypes compatible with a wide range of environmental
conditions.
3. Specific Population adaptation – It refers to the capacity of heterogeneous
population to adapt to specific environment.
4. General population adaptation – It is the capacity of heterogeneous population
to adapt to the variety of environment.
FACTOR AFFECTING ADAPTABILITY
1. Heterogeneity – The heterogeneous population have broad genetic base, Such
population have greater capacity to stabilize production over a wide range of
changing environment.
2. Heterozygosity – It has been observed that heterozygous individual such as F1
hybrids are more stable than their homozygous parents to environmental
variation.
3. Genetic polymorphism – The regular occurrence of several phenotypes in a
genetic population is known as genetic polymorphism.
4. Mode of Pollination – The cross pollination species have better buffering
capacity that self pollination species because of more heterozygosity.
STABILITY ANALYSIS
 It refers to the suitability of variety for general cultivation over wide range
of environments.
 Stability refers to the performance with respective changing environmental
factors overtime within given location.
 Selection for stability is not possible until a biometrical model with
suitable parameters is available to provide criteria necessary to rank
varieties / breeds for stability.
 Low magnitude of G.E interaction involves the consistent performance of
a population over variable environments.
 It consists of following steps: Location / environment wise analysis of
variance. Pooled analysis of variance for all the locations/ environments.
 Stability analysis can be carried out using one of the four methods:
1.Finlay and Wilkinson model (1963)
2.Eberhat and Russell model(1966)
3.Perkins and Jinks model(1968)
4.Freeman and Perkins model (1971)
1. Finlay and Wilkinson model (1963)
Used two parameters
1)Mean performance over environments.
2)Regression performance in different environments.
The following inferences can be drawn:
1)The regression coefficient of unity indicates average stability.
2)If the regression coefficient is >1,it means below average stability.
3) If the regression coefficient is <1, it means above average stability.
4) Regression coefficient of 0 would express absolute stability.
 MERITS
Analysis of this model is simple.
2 parameters- mean yield over locations and regression coefficient are used to asses
the phenotypic stability.
 DEMERITS
The deviations from the regression line are not estimated which are important for
the
stability analysis.
Greater emphasis is given on mean performance over environments than regression
coefficients.
2. Eberhat and Russell model(1966)
It is the most popular and useful model.
In 1966 both made further improvement in stability analysis by partitioning the
G.E interaction of each variety into 2 parts. one is slope of the regression line ,
second is deviation from regression line.
In this model total variance is first divided into 2 components: -genotypes –
environment plus interaction (E+G*E).
The second component is further divided in to 3 components.
I. Environment linear
II. G.E linear
III. Pooled deviations
Sum of squares due to pooled deviations are further divided into sum of squares
due to individual genotype.
MAINFEATURESOF THISMODEL
This model consists of three parameters
a) mean yield over locations
b)regression coefficient =bi
C)Deviation from regression =s²di
Analysis of stability parameters is simple as compared to other models of
stability analysis.
The degree of freedom for environment is 1.
It requires less area hence less expensive when compared to other models.
It does not provide independent estimation for mean performance and
environmental index
Merits:
It measures three parameters of stability
A=mean yield over environments
B=regression coefficient
C=deviation from regression line
• It provides more reliable information on stability than Finlay and Wilkinson
model.
• Analysis is simple.
Demerits:
Estimation of mean performance and environment index is not independent.
There is a combined estimation of sum of squares of environment and interactions
which is not proper.
Eberhart and Russell (1956) defined stable variety as one with a regression
coefficient of unity(b=1) and a minimum deviation from the regression lines(s²d=0).
3. Perkins and Jinks model(1968)
• In this model total variance is first divided into 3 components.
1) Genotypes
2) Environments
3) Genotypes x Environment
G-E variance is sub divided into
a) heterogeneity due to regression
b) sum of square due to remainder
This model is less expensive than Freeman and Perkins.
It requires less area for experimentation.
The degree of freedom for environment is e-2
Analysis is more difficult than Eberhart and Russell model.
It does not provide independent estimation of mean performance and
environmental
index.
4. Freeman and Perkins model (1971)
• In this model total variance is first divided into 3 components.
1) Genotypes
2) Environment
3) G*E
The environmental s.s is sub divided into 2 components
a) combined regression
b) residual 1 The interaction variance is also subdivided into two parts
a)homogeneity of regression b) residual 2
This model also includes 3 parameters like Eberhart and Russell model and
provides independent estimation of mean performance and environmental index.
The degree of freedom for environment is e-2 like perkins and jinks model.
Analysis of this model is more difficult and expensive as compared to earlier two
models. Source of variation D
Applications of Stability Analysis –
1. Stability analysis is helps in understand the adaptability of crop varieties over wide
range of environment conditions and in the identification of adaptable genotype.
2. The use of adaptable genotype for general cultivation over wide range of
environmental conditions helps in achieving stabilization in crop production over
locations and year.
3. Use the stable genotypes in the hybridization programme will lead to development of
phenotypically stable high potential cultivars of crop species.
4. Stability analysis is an important tool for plant breeders in predicting response of
various genotypes over changing environments.

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ADAPTABILITY, Types of Adaptability AND STABILITY ANALYSIS method.pptx

  • 2. ADAPTABILITY AND STABILITY • The success of crop improvement activities largely depend on the identification of superior varieties for mass propagation. • A variety can be considered superior if it has potential for high yield under favorable environment and the same time great deal of phenotypic stability. • Stability of a genotype refers to its performance with respect to changing environment factor over time within a given location. • Adaptability is Ability to genotype to exhibit relatively stable performance in different environment or capacity of a genotype or population for genetic change in adaptation.
  • 3.
  • 4.  Types of Adaptability – 1. Specific genotype adaptation – It is the close adaptation of genotype to a limited environment. 2. General genotypic adaptation – It is refers to the capacity of a genotype to produce a wide range of phenotypes compatible with a wide range of environmental conditions. 3. Specific Population adaptation – It refers to the capacity of heterogeneous population to adapt to specific environment. 4. General population adaptation – It is the capacity of heterogeneous population to adapt to the variety of environment.
  • 5. FACTOR AFFECTING ADAPTABILITY 1. Heterogeneity – The heterogeneous population have broad genetic base, Such population have greater capacity to stabilize production over a wide range of changing environment. 2. Heterozygosity – It has been observed that heterozygous individual such as F1 hybrids are more stable than their homozygous parents to environmental variation. 3. Genetic polymorphism – The regular occurrence of several phenotypes in a genetic population is known as genetic polymorphism. 4. Mode of Pollination – The cross pollination species have better buffering capacity that self pollination species because of more heterozygosity.
  • 6. STABILITY ANALYSIS  It refers to the suitability of variety for general cultivation over wide range of environments.  Stability refers to the performance with respective changing environmental factors overtime within given location.  Selection for stability is not possible until a biometrical model with suitable parameters is available to provide criteria necessary to rank varieties / breeds for stability.  Low magnitude of G.E interaction involves the consistent performance of a population over variable environments.  It consists of following steps: Location / environment wise analysis of variance. Pooled analysis of variance for all the locations/ environments.  Stability analysis can be carried out using one of the four methods: 1.Finlay and Wilkinson model (1963) 2.Eberhat and Russell model(1966) 3.Perkins and Jinks model(1968) 4.Freeman and Perkins model (1971)
  • 7. 1. Finlay and Wilkinson model (1963) Used two parameters 1)Mean performance over environments. 2)Regression performance in different environments. The following inferences can be drawn: 1)The regression coefficient of unity indicates average stability. 2)If the regression coefficient is >1,it means below average stability. 3) If the regression coefficient is <1, it means above average stability. 4) Regression coefficient of 0 would express absolute stability.
  • 8.  MERITS Analysis of this model is simple. 2 parameters- mean yield over locations and regression coefficient are used to asses the phenotypic stability.  DEMERITS The deviations from the regression line are not estimated which are important for the stability analysis. Greater emphasis is given on mean performance over environments than regression coefficients.
  • 9. 2. Eberhat and Russell model(1966) It is the most popular and useful model. In 1966 both made further improvement in stability analysis by partitioning the G.E interaction of each variety into 2 parts. one is slope of the regression line , second is deviation from regression line. In this model total variance is first divided into 2 components: -genotypes – environment plus interaction (E+G*E). The second component is further divided in to 3 components. I. Environment linear II. G.E linear III. Pooled deviations Sum of squares due to pooled deviations are further divided into sum of squares due to individual genotype.
  • 10. MAINFEATURESOF THISMODEL This model consists of three parameters a) mean yield over locations b)regression coefficient =bi C)Deviation from regression =s²di Analysis of stability parameters is simple as compared to other models of stability analysis. The degree of freedom for environment is 1. It requires less area hence less expensive when compared to other models. It does not provide independent estimation for mean performance and environmental index
  • 11.
  • 12. Merits: It measures three parameters of stability A=mean yield over environments B=regression coefficient C=deviation from regression line • It provides more reliable information on stability than Finlay and Wilkinson model. • Analysis is simple. Demerits: Estimation of mean performance and environment index is not independent. There is a combined estimation of sum of squares of environment and interactions which is not proper. Eberhart and Russell (1956) defined stable variety as one with a regression coefficient of unity(b=1) and a minimum deviation from the regression lines(s²d=0).
  • 13. 3. Perkins and Jinks model(1968) • In this model total variance is first divided into 3 components. 1) Genotypes 2) Environments 3) Genotypes x Environment G-E variance is sub divided into a) heterogeneity due to regression b) sum of square due to remainder This model is less expensive than Freeman and Perkins. It requires less area for experimentation. The degree of freedom for environment is e-2 Analysis is more difficult than Eberhart and Russell model. It does not provide independent estimation of mean performance and environmental index.
  • 14.
  • 15. 4. Freeman and Perkins model (1971) • In this model total variance is first divided into 3 components. 1) Genotypes 2) Environment 3) G*E The environmental s.s is sub divided into 2 components a) combined regression b) residual 1 The interaction variance is also subdivided into two parts a)homogeneity of regression b) residual 2 This model also includes 3 parameters like Eberhart and Russell model and provides independent estimation of mean performance and environmental index. The degree of freedom for environment is e-2 like perkins and jinks model. Analysis of this model is more difficult and expensive as compared to earlier two models. Source of variation D
  • 16.
  • 17. Applications of Stability Analysis – 1. Stability analysis is helps in understand the adaptability of crop varieties over wide range of environment conditions and in the identification of adaptable genotype. 2. The use of adaptable genotype for general cultivation over wide range of environmental conditions helps in achieving stabilization in crop production over locations and year. 3. Use the stable genotypes in the hybridization programme will lead to development of phenotypically stable high potential cultivars of crop species. 4. Stability analysis is an important tool for plant breeders in predicting response of various genotypes over changing environments.