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1. VARIABILITY ANALYSIS – PCV, GCV, HERITABILITY AND
GENETIC ADVANCE
GPB 621 – PRINCIPLES OF QUANTITATIVE GENETICS
Class - 3
Dr. K. SARAVANAN
Professor
Department of Genetics and Plant Breeding
Faculty of Agriculture
Annamalai University

2. Dr. K. Saravanan, GPB, AU
• Phenotype = Genotype + Environment
Co-efficient of Variations
• For comparing the variability of different populations or between characters
of the same population, the estimation of co-efficient of variation is required.
The formulae for estimating the phenotypic co-efficient of variation (PCV) and
genotypic co-efficient of variation (GCV) as suggested by Burton (1952) are as
follows.
PCV = GCV =
.
VARIATION ASSOCIATED WITH POLYGENIC RAITS
100
var
X
mean
General
iance
Phenotypic
100
var
X
mean
General
iance
Genotypic
• From Non Replicated data
100
X
PCV X
SD
 100
X
GCV X
SE
SD


3. Dr. K. Saravanan, GPB, AU
Analysis of Variance
• In plant breeding, normally Randomized Block Design (RBD) is used for several
experiments.
• Such analysis divides the total variation into two main parts viz., variation
between varieties and variation within varieties, i.e. environmental variation.
• It helps in partitioning of phenotypic variation into genotypic and
environmental components.
• Phenotype = Genotype + Environment
• VPH = VG +VE
.

4. Dr. K. Saravanan, GPB, AU
.
Where r = number of replications
t = number of varieties / treatments
• From the above table, environmental, genotypic and phenotypic variances are estimated, as follows as
suggested by Lush (1940).
• Environmental variance = σ2
e
• Genotypic variance (σ 2
g) = MS1 – MS2 / r
• Phenotypic variance (σ 2
p) = σ 2
g + σ 2
e
• Analysis of variance also permits estimation of phenotypic, genotypic and environmental coefficients of
variation (Burton, 1952).
Source df SS MS Expectations of MS
Replication r-1 - - -
Varieties t-1 SS1 MS1 σ2
e + r σ2
g
Error (r-1) (t-1) SS2 MS2 σ2
e
Total (rt-1)
Analysis of Variance RBD

5. Dr. K. Saravanan, GPB, AU
• Phenotypic coefficient of variation (PCV) = (σ p/mean) x 100
• Genotypic coefficient of variation (GCV) = (σ g/mean) x 100
• Environmental coefficient of variation (ECV) = (σ e/mean) x 100
• Where, σp, σ g and σ e are phenotypic, genotypic and environmental standard
deviations respectively.
• The PCV and GCV are classified as follows as suggested by
Sivasubramanian and Madhavamenon (1973).
• Low : Less than 10%,
• Moderate : 10-20% ,
• High : More than 20%
.

6. Dr. K. Saravanan, GPB, AU
Interpretation of PCV, GCV & ECV
• GCV is higher than PCV
• It indicates that there is little influence of environment on the expression of
character selection for improvement of such character will be rewarding.
• PCV is higher than GCV
• It means that the apparent variation is not only due to genotypes but also due
to the influence of environment. Selection for such traits sometimes may be
misleading.
• ECV is higher than PCV & GCV
• It indicates that environment is playing a significant role in the expression of
such character. Selection for the improvement of such character will be
ineffective.
.

7. Dr. K. Saravanan, GPB, AU
Heritability & Genetic Advance
• Heritability and genetic advance are important selection parameters.
• Heritability estimates along with genetic advance are normally more helpful
in predicting the gain under selection.
Heritability
• The ratio of genotypic variance to the phenotypic variance or total variance is
known as heritability.
• It is generally expressed in percent.
• Thus heritability is the heritable portion of phenotypic variance.
• It is a good index of the transmission of characters from parents to their
offspring.
.

8. Types of heritability
2 types.
1. Broad sense heritability
2. Narrow sense heritability
Dr. K. Saravanan, GPB, AU

9. Broad sense heritability
• It is the ratio of phenotypic variance to total or phenotypic variance.
• It is calculated from total genetic variance which consists of additive, dominance
and epistatic variances.
• 𝐻𝑒𝑟𝑖𝑡𝑎𝑏𝑖𝑙𝑡𝑦 (ℎ2
) =
𝑉𝑔
𝑉𝑝
=
𝑉𝑔
(𝑉𝑔+𝑉𝑒)
• 𝑉
𝑔- Genotypic variance, 𝑉
𝑝 - Phenotypic variance and 𝑉
𝑒 - Environmental variance.
Dr. K. Saravanan, GPB, AU
Co-heritability
• The analysis of covariance permits estimation of co-heritability for related
characters
• Co-heritability between characters x and y = (σgxy / σpxy ) x 100
• Where, σgxy = genotypic covariance, σpxy = phenotypic covariance

10. Features of broad sense heritability
•It can be estimated from both parental as well as
segregating populations.
•It is estimated from total genetic variance.
•It is more useful in animal breeding than in plant
breeding.
Dr. K. Saravanan, GPB, AU

11. Narrow sense heritability
•It is the ratio of additive or fixable genetic
variance to the total or phenotypic
variances.
•𝐻𝑒𝑟𝑖𝑡𝑎𝑏𝑖𝑙𝑡𝑦 ℎ2 =1/2 D/Vp
•D – Additive genetic variance &
•𝑉
𝑝 - Phenotypic variance.
Dr. K. Saravanan, GPB, AU

12. Features of broad sense heritability
• For estimation of narrow sense heritability, crosses
have to be made in a definite fashion.
• It is estimated from additive genetic variance.
• It is useful in both plant and animal breeding.
• It is useful in the selection from segregating
populations.
Dr. K. Saravanan, GPB, AU

13. Scales for heritability
Narrow sense Scale
Below 10 Low
10 to 30 Medium
Above 30 High
Broad sense Scale
Below 30 Low
30 to 60 Medium
Above 60 High
Dr. K. Saravanan, GPB, AU
Suggested by Johnson et al. (1955)

14. Interpretation
Estimates Values Gene effects Selection
Heritability (BS) High Additive & Non-additive May not useful
Heritability (BS) Low Non-additive Ineffective
Heritability (NS) High Additive Effective
Heritability (NS) Low Non-additive Ineffective
Dr. K. Saravanan, GPB, AU

15. Genetic advance
•Improvement in the mean genotypic value of
selected plants over the parental population is
known as genetic advance.
•It is the measure of genetic gain under selection.
Dr. K. Saravanan, GPB, AU
K
x
Vph
x
Vph
Vg
GA 
Where, Vg = Genotypic variance, Vph = Phenotypic variance, K = Selection
differential at a particular level of selection intensity.

16. Success of genetic gain
• The success of genetic advance under selection depends on three
main factors.
• Genetic variability: The greater the genetic variability the higher is
the genetic advance and vice versa.
• Heritability: The genetic advance is generally high with the characters
having high heritability and vice versa.
• Selection intensity: The proportions of plants or families selected for
the study is called as selection intensity, which plays important role in
the success of genetic advance.
Dr. K. Saravanan, GPB, AU

17. Scales for genetic advance
The range of genetic advance as percent of mean is classified as suggested by Johnson et al.
(1955)
Genetic advance Scale
Less than 10 Low
10 to 20 Medium
Above 20 High
Dr. K. Saravanan, GPB, AU

18. Interpretation
Estimates Values Gene effects Selection
Genetic advance High Additive Effective
Genetic advance Low Non-additive Ineffective
Dr. K. Saravanan, GPB, AU

19. Interpretation of heritability & genetic advance
Heritability Genetic advance Gene effects Selection
High High Additive Effective
High Low Non-additive May not useful
Low High Additive Effective
Low Low - Ineffective
Dr. K. Saravanan, GPB, AU

20. Dr. K. Saravanan, GPB, AU
Calculation of PCV, GCV, ECV, Heritability, Genetic Advance and Genetic advance as
Per cent of mean.
Problem : An experiment with 20 rice genotypes is given below. These genotypes have
been evaluated in RBD with 3 replications. Workout Variability parameters for grain yield
per plant.
.
GENOTYPES R1 R2 R3
G1 22.21 31.86 22.33
G2 37.46 25.64 27.19
G3 29.26 29.38 28.12
G4 37.11 36.24 36.87
G5 32.36 39.12 32.84
G6 27.4 37.33 27.9
G7 35.39 15.85 36.3
G8 46.02 45.74 46.33
G9 28.35 28.82 29.04
G10 21.19 20.53 20.98
GENOTYPES R1 R2 R3
G11 28.67 28.11 27.88
G12 21.44 23.92 22.16
G13 24.65 24.96 35.18
G14 19.91 30.1 23.42
G15 24.55 24.83 25.02
G16 21.36 22.71 22.09
G17 23.68 23.99 24.22
G18 31.66 49.07 31.84
G19 45.76 49.33 42.99
G20 32.56 37.9 25.2

21. Dr. K. Saravanan, GPB, AU
Genotypes R1 R2 R3 TOTAL
G1 22.21 31.86 22.33 76.4
G2 37.46 25.64 27.19 90.29
G3 29.26 29.38 28.12 86.76
G4 37.11 36.24 36.87 110.22
G5 32.36 39.12 32.84 104.32
G6 27.4 37.33 27.9 92.63
G7 35.39 15.85 36.3 87.54
G8 46.02 45.74 46.33 138.09
G9 28.35 28.82 29.04 86.21
G10 21.19 20.53 20.98 62.7
G11 28.67 28.11 27.88 84.66
G12 21.44 23.92 22.16 67.52
G13 24.65 24.96 35.18 84.79
G14 19.91 30.1 23.42 73.43
G15 24.55 24.83 25.02 74.4
G16 21.36 22.71 22.09 66.16
G17 23.68 23.99 24.22 71.89
G18 31.66 49.07 31.84 112.57
G19 45.76 49.33 42.99 138.08
G20 32.56 37.9 25.2 95.66
TOTAL 590.99 625.43 587.9 1804.32
.
Total no. of genotypes = 20
Total no. of replication = 3
Observation = 20 x 3 = 60
Grand total = 1804.32
Grand Mean = GT/N = 30.07
1. Correction factor = (GT)2/N = 54259.51
2. Raw Sum of Square = 58102.46
3. Total Sum of square = 3842.949
4. Genotype Sum of square = 2907.39
5. Replication Sum of square = 43.40271
6. Error Sum of square = 892.156

22. Dr. K. Saravanan, GPB, AU
ANOVA
SOURCE DF SS MSS F-RATIO
REP 2 43.40 21.70 0.92
GENO 19 2907.39 153.02 6.52
ERROR 38 892.16 23.48
TOTAL 59 3842.95
.
PCV = 27.15
GCV= 21.85
ECV= 16.11
HERITABILITY = 64.78
GA = 10.89
GA as % of mean = 36.23
Environmental Variance = σ2
e
23.48
Genotypic Variance = (σ 2g) = MS1 – MS2 / r 43.18
Phenotypic variance = (σ 2p) = σ 2g + σ 2e 66.66

23. Dr. K. Saravanan, GPB, AU
Problem 2 : Estimation of variability parameters for given ratoon sugar cane
data.
.
ANOVA
SOURCE DF
MSS
No. of
tillers
NO. of
millable
cane
Stalk
length
stalk
inernode
length
Single
stalk
weight
Juice brix
percent
Juice
purity
percent
CCS per
cent
Cane
yield
Sugar
yield
Replication 1 73.04 56.26 0.0002 4.27 0.00001 0.31 0.31 0.19 48.6 1.19
Genotypes 29 1539.51 587.94 0.13 5.51 0.26 5.02 6.11 2.48 2537.84 39.42
Error 29 103.26 67.62 0.04 2.03 0.04 0.45 2.65 0.44 59.49 1.47
Mean 180.44 105.72 2.13 12.39 1.39 18.25 92.09 11.82 120.64 14.03
Meter cm kg t/ha t/ha

24. Thank q
Dr. K. Saravanan, GPB, AU