The document describes methods for identifying and evaluating heterotic groups in plant breeding, including hybridization, pedigree analysis, quantitative genetic analysis using diallel crosses, and molecular marker analysis. A study is described that classified 14 maize inbred lines into heterotic groups using diallel analysis. The lines were crossed in a diallel design and evaluated for traits like grain yield. Estimates of general and specific combining ability were used to classify the lines into heterotic groups, which was validated using biplot analysis and molecular markers. The results provided insights into the combining ability of different inbred lines with different testers under varying environments.

1. Submitted by :- Alka
Admission no :- L-2021-A-82-M
Identification and Evaluation
of Heterotic Groups

2. Hybrids
Hybrids are produced by crossing plants of two dissimilar
genotypes. The main objective of hybridization is to create
genetic variation. The aim of hybridization is
 Transfer of one or few qualitative characters
 Improvement of one or more quantitative characters
 Use of the F1 as a hybrid variety.
 To exploit the heterosis and use it for quality hybrid
production.

3. Heterotic Groups
 A heterotic group is set of genetically related or unrelated
genotypes from same or different population that show
similar hybrid performance when crossed with individuals
from another genetically distinct germplasm group.
 More the divergence in heterotic groups, more heterosis
hybrids will have.
 Plants from same heterotic group known to have same
phenotype and genotype.

4. Different Methods of Developing
Heterotic Groups
 Pedigree Analysis
 Quantitative Genetic Analysis
 Geographical isolation inference
 Use of Molecular markers

5. 1. Pedigree Analysis
 Pedigree is the complete record of ancestral history of
lines.
 In this method the germplasm is grouped into different
heterotic groups on the basis of pedigree analysis.
 The pedigree of each and every line is studied thoroughly.
The pedigree depict the idea about heredity and control
of characters in respective line.
 On the basis of pedigree the lines showing similar genetic
control, similar physiology, agro-morphological characters
are grouped into different groups.

6. 2. Quantitative Genetic Analysis
 In quantitative genetic analysis the different quantitative
approaches are used to evaluate lines and group them into
different heterotic groups.
 Diallel and line into tester analysis are widely used for
quantitative genetic analysis.
 Basis of grouping the germplasms into different heterotic
groups is specific combining ability (SCA) and general
combining ability effects for different traits.
 Cluster analysis based on SCA can be used to classify
inbred lines into heterotic groups

7. 3. Geographical isolation inference
 In this method the geographical isolation is used as
parameter for evaluation and grouping of germplasm.
 Generally lines from more distant origins are predicted to
give excellent heterotic combinations.
 Crops originate from different centers they are more
likely to perform good and there hidden potential is
observed through hybrids.

8. 4. Molecular Markers
 Grouping of germplasm on the basis of agro-morphological
characters.
 Clustering germplasm based on genetic similarities using the
molecular markers.
 Selecting representative genotype from each subgroup.
 Evaluation of crosses among representative genotype in field
trials for different combining abilities (GCA/SCA)
 Finally we select the heterotic group based on hybrid
performance.

9. Quantitative Genetic Analysis by Diallel
 The diallel approach is given by Hayman and Griffing in
1954 and 1956 respectively.
 This method is used to evaluate the crosses for different
components viz SCA, GCA and RCA.
 With evaluation of these above components we are able
to estimate additive, dominant and epistatic effects.
 From above two models, Griffing’s approach is more
preferable as it also gives estimates of reciprocal
combining ability.

10. Griffing’s Approach
Griffing’s approach involves two models
 Fixed Effect model – fixed model involves the deliberate
selection of parents. The experimental material includes a
set of fixed inbreds/varieties as parents.
 Random Effect Model – in this model the parents are
selected at random.
The fixed effect model is more used as most of the plant
breeders are usually interested in genetic information about
a particular set of parents.

11. Procedure
1. Selection of Parents – In this design, parents are selected either on
the basis of model 1 or model 2. Parents may be inbreds, varieties,
newly developed cultures etc.
2. Mating of Parents - Selected parents are mated in all possible
combinations to get crosses. However, depending upon the method
used for analysis, either all crosses (direct and reciprocal crosses) or
direct crosses alone (without reciprocals) are made.
3. Evaluation of Crosses – The crosses, obtained by mating all parents in
all possible combinations, along with parents (depending upon method
followed) are evaluated in standard statistical design (normally RBD)
with required no of replications. The biometrical observation are
taken on all replications and the data are used for statistical analysis.

12. Conti…
4. Statistical Analysis- The mean data of biometrical
characters recorded on all the genotypes are subjected to
appropriate analysis of variance (RBD).the significance of F
value for genotypes indicates significant difference among
the genotypes studied and may be continued for combining
ability analysis.
5. Combining Ability Analysis – The degrees of freedom and
formulae to workout sum of squares due to various sources
of variation are used for combining ability analysis.

13. Heterotic grouping of maize germplasm by
Diallel (6 Inbred lines)
Steps :
1. Diallel analysis for testing for combining ability effects.
2. Secondly we can check these all lines for agronomic traits.
3. At last SSR markers are applied to access polymorphism
present in these 15 lines.

14. Mating scheme of 6 inbreds in Diallel
X are direct crosses, + are reciprocals, * are parents selfing
Parents 1 2 3 4 5 6
1 P1XP1 * P1XP2 x P1XP3 x P1XP4 x P1XP5 x P1XP6 x
2 P2XP1 + P2XP2 * P2XP3 x P2XP4 x P2XP5 x P2XP6 x
3 P3XP1 + P3XP2 + P3XP3 * P3XP4 x P3XP5 x P3XP6 x
4 P4XP1 + P4XP2 + P4XP3 + P4XP4 * P4XP5 x P4XP6 x
5 P5XP1 + P5XP2 + P5XP3 + P5XP4 + P5XP5 * P5XP6 x
6 P6XP1 + P6XP2 + P6XP3 + P6XP4 + P6XP5 + P6XP6 *

15. Evaluation of Crosses in RBD(ANOVA)
Source of
variation
Degree of
freedom
Sum of
Squares
Mean sum of
Squares
F value
Replication R-1 SSR MSR MSR/MSE
Genotypes p²-1 SSG MSG MSG/MSE
Error (R-1)(p²-1) SSE MSE
Total N-1 TSS
Calculated value of F is compared with table value of F. If the calculated value if
greater then the table value of F then it is concluded that the genotypes are
significantly different. Further we can proceed for analysis for combining ability.

16. Combining Ability Analysis (ANOVA)
Source Degree of
Freedom
Sum of
Squares
Mean Sum of
Squares
F value
GCA p-1 SSGCA MGCA MGCA/MSE
SCA c SSSCA MSCA MSCA/MSE
RCA c SSRCA MSRCA MRCA/MSE
Error (r-1) (t-1) SSE MSE
Genetic Components are estimated as following
GCA² = MGCA-MSE / 2P
SCA²= MSCA- MSE
Ratio of GCA² /SCA² is calculated. If this value is comes to be less than unity(1)
then the character is governed by dominance gene action.
If value comes to be more than 1 then character is governed by additive gene
action.

17. Estimation of Genetic Effects
 GCA effect for all parents is calculated.
 Significance of effects is evaluated by t test.
 Then SCA effects of hybrids are evaluated and significance of SCA effects is
checked.
 The parents having positively significant GCA effects can be used in crop
improvement breeding programs. These parents are grouped in heterotic
groups.

18. Evaluation for Agronomic Traits
 The germplasm is then evaluated for agronomic traits.
 The plants are evaluated in different experimental designs
e.g RBD(Randomized complete block design), CRD
(completely randomized design)
 The proper agronomic practices are followed.
 Plant density is taken into consideration.

19. Evaluation by Molecular Markers
 PCR is carried out on genomic DNA extracted from
different plants from inbred lines.
 Any kind of markers are used for evaluation of genome.
SSR markers are widely used as these are easily available.
 After amplification data is generated and we can
evaluate existed polymorphism present in the germplasm.

20. World Academy of Science, Engineering and Technology International Journal of Agricultural
and Biosystems Engineering Vol:6, No:7, 2012
By:- Mozhgan Ziaie Bidhendi, Rajab Choukan, Farokh Darvish, Khodadad Mostafavi, Eslam
Majidi
Paper
Classifying of Maize Inbred Lines into Heterotic Groups using Diallel Analysis M World
Academy of Science, Engineering and Technology(2012) International Journal of Agricultural
and Biosystems Engineering 6(7): 556-59.
Related Article

21. Procedure
 Plant Material: Plant material Fourteen maize inbred lines were
introduced from maize breeding programs in Iran. The inbreds
consisted of five lines from two well-known USA heterotic groups, as
well as two derived lines from Mo17 (K18 and K19/1 which are
selected in Iran), five lines were extracted from CIMMYT germplasm,
and four lines from a late synthetic (SYN L.) population originating
from Iran. All lines and their pedigree sources/origin (if known) are
listed. Ninety-one crosses were made by hand pollination among the
14 maize lines according to Griffing’s diallel method. A total of 105
genotypes (91 crosses and 14 parental inbreds) were evaluated. The
105 genotypes were arranged in a randomized complete blocks design
with three replications at each location. Estimates of GCA and SCA
effects were calculated and their significance determined by t-test.
Finally, a biplot analysis of diallel data was conducted using GGEbiplot
software.

22. Biplot based on diallel data of 14 maize inbred lines for grain
yield. Genotypes are labeled with uppercase letters when viewed
as entries and with lowercase letters when viewed as testers, The
circle indicates the average tester

23. Results

24. Conclusion
 Therefore, they purpose that biplot analysis could be useful to demonstrate
performance of inbred lines with different testers under the different
environments. It purposes to better understand the combining ability of
different inbred lines with different testers.