ELUCIDATION OF RICE ADVANCED BREEDING LINES (F6 GENERATION) FOR GENETIC DIVERSITY THROUGH PRINCIPAL COMPONENT AND HIERARCHICAL CLUSTERING ANALYSIS
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Keywords:
Correlation, Genetic diversity, Hierarchical cluster analys, Principal component analysis, Rice.Abstract
The current study aimed to evaluate 200 advanced breeding lines along with three checks during kharif,2024 to delineate the extent of genetic diversity for yield and its component trait using multivariate techniques using Principal Component Analysis (PCA), Hierarchical clustering and correlation. In PCA, the principal components having eigen values greater than one viz., PC1, PC2, PC3,PC4 and PC5 detailing 20.3%, 16.7%, 14%, 12.8% and 12.7% respectively with
a cumulative effect of 76.7% of the total variation. Based upon Wards method of hierarchical clustering, 200 rice advanced breeding lines along with three checks were divulged into 14 clusters based on different traits studied, in which cluster I topped with 30 advanced breeding lines followed by cluster XIII and VI with 29 and 25 advanced breeding lines, respectively. The advanced breeding linesconfined to cluster X registered higher cluster mean values for grain yield. Besides, cluster XIV showed highest values for panicle length, ear bearing tillers/m2 and grains per panicle. The trait grain yield registered positive association with days to 50 % flowering, days to maturity, ear bearing tillers/m2, grains per panicle and test weight through correlation analysis.
From the present study, the advanced breeding lines viz., NDRA 78, NDRA 225, NDRA 226, NDRA 227 and NDRA 50 were identified as genetically potential advanced breeding lines for commercial exploitation for enhancing yield and component traits in rice.
References
Edukondalu, B., Reddy, V.R., Rani, T.S.,
Kumari, C.A. and Soundharya, B., 2024.
Assessment of variation in rice maintainer
lines using principal component
analysis. Electronic Journal of Plant
Breeding, 15(1): 270-276.
Fathima M.A, Geetha S, Amudha K, Uma
D.2021. Genetic variability, frequency
distribution and association analysis in
ADT (R) 48 x Kavuni derived F2
population of rice (Oryza sativa L.).
Electronic Journal of Plant Breeding,
12(3):659-666
Howlader, N.C., Bulbul, M.T.A., Islam, M.Z.,
Arafat, E., Rana, M.S. and Hasan, M.Z.,
2025. Assessing rice genotypes based
on agro-morphological characterization
and diversity analysis in southern
Bangladesh. Discover Plants, 2(1): 1-19.
Kusuma Kumari, B., Ravi Kumar, B.R., Jyothula,
D.P.B. and Rao, N.M. 2021. Diversity
analysis in rice breeding lines for yield
and its components using principal
40
ELUCIDATION OF RICE ADVANCED BREEDING LINES (F6
GENERATION) FOR GENETIC DIVERSITY
component analysis. Journal of
Pharmacognosy& Phytochemistry, 10(1):
905-909.
Mondal, S., Pradhan, P., Das, B., Kumar, D.,
Paramanik, B., Yonzone, R., Barman, R.,
Saha, D., Karforma, J., Basak, A. and
Dey, P., 2024. Genetic characterization
and diversity analysis of indigenous
aromatic rice. Heliyon, 10(10).
Paramanik, S., Panda, K.K., Rao, M.S., Jaishi,
A. and Pati, A.K., 2025. Unlocking the
genetic diversity and principal
component analysis of selected rice
(Oryza sativa L.) genotypes using
physical and biochemical
characteristics. Plant Molecular Biology
Reporter, 1-15.
Pavan Kumar, G.K., Durga Prasad, A.V.S and
Reddy, C.V.C.M. 2019. Hierarchical
cluster analysis for yield and nutritional
traits in elite foxtail millet genetic
resources [Setaria italica (L.)
Beauv.].International Journal of
Innovative Science and Research
Technology, 4(7): 1253-1257.
Ratnam,V.T., Ravi Kumar, B., Rao, L.V.,
Srinivas, T. and Kumar, A.A. 2022.
Principal component analysis of yield and
quality traits in Zinc rich landraces of
rice (Oryza sativa L.). Electronic Journal
of Plant Breeding, 13(4): 1162-1169.
Ravi Kumar, B.N.V.S.R., Kumari, P.N., Rao,
P.V.R., Rani, M.G., Satyanarayana, P.V.,
Chamundeswari, N., Vishnuvardhan,
K.M., Suryanarayana, Y., Bharatha
lakshmi, M. and Reddy, A.V. 2015.
Principal component analysis and
character association for yield
components in rice (Oryza sativa L.)
cultivars suitable for irrigated ecosystem.
Current Biotica, 9(1): 25-35. Ricepedia,
2025. Rice as food. http://ricepedia.org/
rice-as-food
Roy, T.K., Sannal, A., Tonmoy, S.S., Akter, S.,
Roy, B., Rana, M.M., Alam, Z. and Hasan,
M.R., 2024. Trait analysis of short
duration boro rice (Oryza sativa L.)
varieties in northern region of
Bangladesh: insights from heatmap,
correlation and PCA. Nova
Geodesia, 4(2):175-175.
Sudeepthi, K., Srinivas, T., Ravi Kumar,
B.N.V.S.R., Jyothula, D.P.B. and Umar,
S.N. 2020a. Genetic divergence studies
for anaerobic germination traits in rice
(Oryza sativa L.). Current Journal of
Applied Science and Technology, 39(1):
71-78.
Sudeepthi, K., Srinivas, T., Ravi Kumar,
B.N.V.S.R., Jyothula, D.P.B. and Umar,
S.N. 2020b. Assessment of genetic
variability, character association and
path analysis for yield and yield
component traits in rice Oryza sativa
L. Electronic Journal of Plant
Breeding, 11 (01): 144-148.
Vasudeva Reddy, D., Suneetha, Y., Ravi Kumar,
B.N.V.S R. and Ramesh, D. 2023.
Evaluation of experimental hybrids for
yield and yield component traits in Rice
(Oryza sativa L.). The Andhra Agricultural
Journal, 70 (1): 050-061.
Vijay Kumar, R., Ravi Kumar, B.N.V.S.R.,
Amarnath, K., Kavitha, G., Nageshwara
Reddy,A.V., Vishnuvardhan, K.R., Divya
Mani, B., Venkateswarlu, N.C. 2024.
Genetic insights into yield potential in
advanced rice cultures: A multivariate
analysis of yield components.
International Journal of Research in
Agronomy, 7(9S):100-104.
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