A review on genetic parameters estimation, trait association, and multivariate analysis for crop improvement
https://doi.org/10.26832/24566632.2024.0903029
Abstract
This review paper aims to elucidate the critical genetic parameters essential for practical crop breeding, focusing on the nature and extent of variability, its inheritance, and the complexity of traits. By evaluating genetic parameters such as Genetic Coefficient of Variation (G.C.V.), Heritability, Genetic Advance as a percentage of the Mean (G.A.M.), correlation coefficients, path coefficient analysis, cluster analysis, and principal component analysis, the review provides a comprehensive framework for optimizing breeding strategies. Emphasizing higher G.C.V. values minimizes environmental effects while highlighting Heritability and G.A.M. aids in predicting trait transmission and potential genetic improvement. The review also underscores the importance of traits with high G.C.V., Heritability, and G.A.M. for effective selection and improvement. Additionally, cluster and principal component analyses are powerful tools for identifying genetically diverse parents and reducing trait dimensionality. The findings suggest that thoroughly understanding and applying these genetic parameters can significantly enhance decision-making in plant breeding programs, ultimately leading to more efficient and targeted genetic improvements.
Keywords:
Cluster analysis, Genetic variability, Path coefficient, Principal component analysisDownloads
References
Adhikari, B. N., Joshi, B. P., Shrestha, J., & Bhatta, N. R. (2018). Genetic variability, Heritability, genetic advance and correlation among yield and yield components of rice (Oryza sativa L.). Journal of Agriculture and Natural Resources, 1(1), 149–160. https://doi.org/10.3126/janr.v1i1.22230
Ahmed, B., Dhasarathan, B., Singh, S., & Gaur, H. (2023). Edition 1 st Genetic Improvement of Crops Editors (Issue August).
Al-Naggar, A. M. M., Al-Azab, K. F., Younis, A. S. M., Hassan, I. O., Basyouny, M. A. E., & Ayaad, M. (2021). Genetic parameters controlling the inheritance of glaucousness and yield traits in bread wheat. Brazilian Journal of Biology, 82, e253864.
Ali, N., Hussain, I., Ali, S., Khan, D. N., & Hussain, I. (2020). Multivariate analysis for various quantitative traits in wheat advanced lines. Saudi Journal of Biological Sciences, 28. https://doi.org/10.1016/j.sjbs.2020.10.011
Aman, M. (2021). Genetic Variability, Heritability and Association of Quantitative Traits in Maize (Zea mays L) Genotypes: Review Paper. E.A.S. Journal of Biotechnology and Genetics, 3(2), 38–46. https://doi.org/10.36349/easjbg.2021.v03i02.002
Anand, A., Subramanian, M., & Kar, D. (2023). Breeding techniques to dispense higher genetic gains. January, 1–6. https://doi.org/10.3389/fpls.2022.1076094
Bartaula, S., Panthi, U., Timilsena, K., Acharya, S. S., & Shrestha, J. (2019). Variability, Heritability and genetic advance of maize (Zea mays L.) genotypes. Research in Agriculture Livestock and Fisheries, 6(2), 163–169. https://doi.org/10.3329/ralf.v6i2.42962
Baye, A., Berihun, B., Bantayehu, M., & Derebe, B. (2020). Genotypic and phenotypic correlation and path coefficient analysis for yield and yield-related traits in advanced bread wheat (Triticum aestivum L.) lines. Cogent Food & Agriculture, 6(1), 1752603.
Beattie, J. R., & Esmonde-White, F. W. L. (2021). Exploration of principal component analysis: deriving principal component analysis visually using spectra. Applied Spectroscopy, 75(4), 361–375.
Bhadru, D., Swarnalatha, V., Mallaiah, B., Sreelatha, D., Kumar, M. V. N., & Reddy, M. L. (2020). Study of Genetic Variability and Diversity in Maize (Zea mays L.) Inbred Lines. Current Journal of Applied Science and Technology, 31–39. https://doi.org/10.9734/cjast/2020/v39i3831093
Bhatia, S. (2018). Introduction to genetic engineering. In Introduction to Pharmaceutical Biotechnology, Volume 1 (pp. 3–64). I.O.P. Publishing. https://doi.org/10.1088/978-0-7503-1299-8ch3
Bradshaw, J. E. (2017). Plant breeding: past, present and future. Euphytica, 213(3), 60. https://doi.org/10.1007/s10681-016-1815-y
Burton, G. W. (1952). Quantitative inheritance in grasses. Pro VI Int Grassl Cong, 277–283.
Cobb, J. N., Juma, R. U., Biswas, P. S., Arbelaez, J. D., Rutkoski, J., Atlin, G., Hagen, T., Quinn, M., & Ng, E. H. (2019). Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder's Equation. Theoretical and Applied Genetics, 132(3), 627–645. https://doi.org/10.1007/s00122-019-03317-0
Daleo, P., Alberti, J., Chaneton, E. J., Iribarne, O., Tognetti, P. M., Bakker, J. D., Borer, E. T., Bruschetti, M., MacDougall, A. S., Pascual, J., Sankaran, M., Seabloom, E. W., Wang, S., Bagchi, S., Brudvig, L. A., Catford, J. A., Dickman, C. R., Dickson, T. L., Donohue, I., & Hautier, Y. (2023). Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass. Nature Communications, 14(1), 1809. https://doi.org/10.1038/s41467-023-37395-y
Das, S., Sarma, D., Chakraborty, I., Roy, N., & Das, S. S. (2017). Principal Component Analysis in Plant Breeding.
Dewey, D. R., & Lu, K. H. (1959). A Correlation and Path-Coefficient Analysis of Components of Crested Wheatgrass Seed Production 1. Agronomy Journal, 51(9), 515–518. https://doi.org/10.2134/agronj1959.00021962005100090002x
Dey, P. (2019). Estimation of Phenotypic Coefficients of Variation (PCV),
Genotypic Coefficients of Variation (G.C.V.), Heritability and Genetic Gain for Yield and its Components in Rice Landraces of Odisha. International Journal of Agriculture Environment and Biotechnology, 12(3). https://doi.org/10.30954/0974-1712.08.2019.1
Escobar-Flores, P. C., Ladroit, Y., & O’Driscoll, R. L. (2019). Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00507
Fikret, I. (2023). Unravelling nature’s blueprint: Understanding Heritability and genetic influence in plant and animal breeding. V.S.N. International Ltd. https://vsni.co.uk/blogs/Understanding-Heritability
Forina, M., Lanteri, S., & Rosso, S. (2001). Confidence intervals of the prediction ability and performance scores of classifications methods. Chemometrics and Intelligent Laboratory Systems, 57(2), 121–132. https://doi.org/10.1016/S0169-7439(01)00129-0
Gholamin, R., & Khayatnezhad, M. (2020). The study of path analysis for durum wheat (Triticum durum Desf.) yield components. Bioscience Biotechnology Research Communications, 13(4), 2139–2144.
Gomez, K. A., & Gomez, A. A. (1984). Statistical procedures for agricultural research. John Wiley & Sons.
Graffelman, J., & De Leeuw, J. (2023). Improved approximation and visualization of the correlation matrix. The American Statistician, 77(4), 432–442.
Greenacre, M., Groenen, P. J. F., Hastie, T., D’Enza, A. I., Markos, A., & Tuzhilina, E. (2022). Principal component analysis. Nature Reviews Methods Primers, 2(1), 100. https://doi.org/10.1038/s43586-022-00184-w
Hallauer, A. R. (2023). Breeding systems. In C.R.C. Handbook of Plant Science in Agriculture (pp. 61–87). C.R.C. press.
Hoffmann, A. A., & Sgró, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470(7335), 479–485. https://doi.org/10.1038/nature09670
Ilska, J. J., Tolhurst, D. J., Tumas, H., Maclean, J. P., Cottrell, J., Lee, S. J., Mackay, J., & Woolliams, J. A. (2023). Additive and non-additive genetic variance in juvenile Sitka spruce (Picea sitchensis Bong. Carr). Tree Genetics & Genomes, 19(6), 53.
Isaac, U. C. (2021). Phenotypic, genetic and environmental correlations between body weight and linear body traits of chicken genotypes. Agrobiological Records. https://api.semanticscholar.org/CorpusID:230532831
Johnson, H. W., Robinson, H. F., & Comstock, R. E. (1955). Estimates of Genetic and Environmental Variability in Soybeans 1. Agronomy Journal, 47(7), 314–318. https://doi.org/10.2134/agronj1955.00021962004700070009x
Kahani, F., & Hittalmani, S. (2016). Identification of F2 and F3 segregants of fifteen rice crosses suitable for cultivation under aerobic situation. SABRAO Journal of Breeding and Genetics, 48, 219–229.
Khan, M. M. H., Rafii, M. Y., Ramlee, S. I., Jusoh, M., & Mamun, A. (2020). Genetic Variability, Heritability, and Clustering Pattern Exploration of Bambara Groundnut (Vigna subterranea L. Verdc) Accessions for the Perfection of Yield and Yield-Related Traits. BioMed Research International, 2020, 1–31. https://doi.org/10.1155/2020/2195797
Khan, S., Mahmud, F., & Ahmmed, T. (2022). Genetic Diversity with Cluster Analysis of Maize Genotypes Zea mays L.). Advances in Bioscience and Biotechnology, 13(07), 273–283. https://doi.org/10.4236/abb.2022.137017
Khatun, M., Islam, M. R., Khan, M. A. R., Hossain, M. K., & Islam, A. (2023). Principal component analysis and estimated breeding values for selecting suitable parental genotypes in rice (Oryza sativa L.). Sabrao Journal of Breeding & Genetics, 55(6).
Kherif, F., & Latypova, A. (2020). Chapter 12 - Principal component analysis (A. Mechelli & S. B. T.-M. L. Vieira (eds.); pp. 209–225). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-815739-8.00012-2
Kumar, M., Sandhya, P. K., Gaurav, A., Soni, R. K., & Meena, D. (2022). Principal component analysis for assessment of genetic diversity in rice under Humid South-Eastern plain of Rajasthan.
Lephuthing, M. C., Khumalo, T. P., Tolmay, V. L., Dube, E., & Tsilo, T. J. (2022). Genetic Mapping of Quantitative Trait Loci Associated with Plant Height and Yield Component Traits in a Wheat (Triticum aestivum L.) Doubled Haploid Population Derived from Tugela-DN × Elands. In Agronomy (Vol. 12, Issue 10). https://doi.org/10.3390/agronomy12102283
Lipi, L., Hasan, M., Akter, A., Quddus, M., Biswas, P., Ansari, A., & Akter, S. (2021). Genetic Variation, Heritability and Genetic Advance in Some Promising Rice Hybrids. SAARC Journal of Agriculture, 18(2), 39–49. https://doi.org/10.3329/sja.v18i2.51107
Marinković, R. (1992). Path-coefficient analysis of some yield components of sunflower (Helianthus annuus L.), I. Euphytica, 60(3), 201–205. https://doi.org/10.1007/BF00039399
Mishra, A. (2023). Characterization, heterosis and gene action studies for biomass related quantitative traits in rice. Department of Plant Breeding and Genetics, OUAT, Bhubaneswar.
Mitchell, R. J. (2020). Path analysis: pollination. In Design and analysis of ecological experiments (pp. 211–231). Chapman and Hall/C.R.C.
Moll, R. H., & Stuber, C. W. (1974). Quantitative Genetics—Empirical Results Relevant to Plant Breeding (pp. 277–313). https://doi.org/10.1016/S0065-2113(08)60874-3
Nishisato, S., Beh, E. J., Lombardo, R., Clavel, J. G., Nishisato, S., Beh, E. J., Lombardo, R., & Clavel, J. G. (2021). History of the biplot. Modern Quantification Theory: Joint Graphical Display, Biplots, and Alternatives, 167–179.
Olawamide, D. O., & Fayeun, L. S. (2020). Correlation and Path Coefficient Analysis for Yield and Yield Components in Late Maturing Pro-vitamin A Synthetic Maize (Zea mays L.) Breeding Lines. Journal of Experimental Agriculture International, 64–72. https://doi.org/10.9734/jeai/2020/v42i130452
P.C. Mahalanobis. (1936). 1936_Mahalanobis.pdf (pp. 541–588).
Pai, S., Emmerling, J., Drouet, L., Zerriffi, H., & Jewell, J. (2021). Meeting well-below 2°C target would increase energy sector jobs globally. One Earth, 4(7), 1026–1036. https://doi.org/10.1016/j.oneear.2021.06.005
Palaniyappan, S., Arunachalam, P., Banumathy, S., Mini, M. L., & Muthuramu, S. (2020). Genetic divergence and clustering studies in advanced breeding lines of rice (Oryza sativa L.). Electronic Journal of Plant Breeding, 11(02), 499–504.
Pennington, L. K., & Sexton, J. P. (2024). Species Range Limits. In S. M. Scheiner (Ed.), Encyclopedia of Biodiversity (Third Edition) (Third Edit, pp. 219–236). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-822562-2.00357-1
Plant, M., Montesinos-lo, O. A., Isidro, J., Alemu, A., Johanna, A., Tadesse, W., Vetukuri, R. R., Carlsson, A. S., Ortiz, R., Chawade, A., & Ceplitis, A. (2024). Genomic selection in plant breeding : Key factors shaping two decades of progress. 2023, 552–578. https://doi.org/10.1016/j.molp.2024.03.007
Rasheed, A., Ilyas, M., Khan, T. N., Mahmood, A., Riaz, U., Chattha, M. B., Al Kashgry, N. A. T., Binothman, N., Hassan, M. U., & Wu, Z. (2023). Study of genetic variability, Heritability, and genetic advance for yield-related traits in tomato (Solanum lycopersicon MILL.). Frontiers in Genetics, 13, 1030309.
Reddy, V. R., & Jabeen, F. (2016). Narrow sense heritability , correlation and path analysis in maize (Zea mays L.). https://api.semanticscholar.org/CorpusID:199423598
Regmi, S., Poudel, B., Ojha, B. R., Kharel, R., Joshi, P., Khanal, S., & Kandel, B. P. (2021). Estimation of Genetic Parameters of Different Wheat Genotype Traits in Chitwan, Nepal. International Journal of Agronomy, 2021, 6651325. https://doi.org/10.1155/2021/6651325
Rehman, A., Mustafa, N., Du, X., & Azhar, M. T. (2020). Heritability and correlation analysis of morphological and yield traits in genetically modified cotton. Journal of Cotton Research, 3(1), 23. https://doi.org/10.1186/s42397-020-00067-z
Rekha, M. (2019). Eigen Decomposition and P.C.A. Clairvoyant Blog, Medium. https://blog.clairvoyantsoft.com/eigen-decomposition-and-pca-c50f4ca15501
Resende, R. T., Piepho, H.-P., Rosa, G. J. M., Silva-Junior, O. B., e Silva, F. F., de Resende, M. D. V, & Grattapaglia, D. (2021). Enviromics in breeding: applications and perspectives on envirotypic-assisted selection. Theoretical and Applied Genetics, 134(1), 95–112. https://doi.org/10.1007/s00122-020-03684-z
Rettew, D. C., Rebollo-Mesa, I., Hudziak, J. J., Willemsen, G., & Boomsma, D. I. (2008). Non-additive and Additive Genetic Effects on Extraversion in 3314 Dutch Adolescent Twins and Their Parents. Behavior Genetics, 38(3), 223–233. https://doi.org/10.1007/s10519-008-9192-5
Sanchez, D., Sadoun, S. Ben, Mary-Huard, T., Allier, A., Moreau, L., & Charcosset, A. (2023). Improving the use of plant genetic resources to sustain breeding programs’ efficiency. Proceedings of the National Academy of Sciences, 120(14), e2205780119.
Scheffers, B. R., De Meester, L., Bridge, T. C. L., Hoffmann, A. A., Pandolfi, J. M., Corlett, R. T., Butchart, S. H. M., Pearce-Kelly, P., Kovacs, K. M., Dudgeon, D., Pacifici, M., Rondinini, C., Foden, W. B., Martin, T. G., Mora, C., Bickford, D., & Watson, J. E. M. (2016). The broad footprint of climate change from genes to biomes to people. Science, 354(6313). https://doi.org/10.1126/science.aaf7671
Shrestha, S., Niraula, D., Regmi, S., Basnet, S., Chhetri, S. T., & Kandel, B. P. (2023). Performance evaluation and genetic parameters estimation of multi-companies maize hybrids in Lamahi Dang, Nepal. Heliyon, 9(3), e14552. https://doi.org/10.1016/j.heliyon.2023.e14552
Singh, A., Singh, A., Barb, J., & Mahama, A. A. (2023). Genetic variation and germplasm usage. Crop Improvement.
Singh, P., Jain, P. K., & Tiwari, A. (2020). Principal component analysis approach for yield attributing traits in chilli (Capsicum annum L.) genotypes. Chemical Science Review and Letters, 9(33), 87–91.
Singh, R. K., & Chaudhary, B. D. (1977). Biometrical methods in quantitative genetic analysis. Kalyani.
Soliman, A. A., Mousa, M. I., Mosalam, A. M., Ghareeb, Z. E., Ibrahim, S. D., Rehan, M., Yu, H., & He, Y. (2023). The Potential Genetic Effect for Yield and Foliar Disease Resistance in Faba Bean (Vicia faba L.) Assessed via Morphological and SCoT Markers. Plants, 12(20), 3645. https://doi.org/10.3390/plants12203645
Tadesse, J., Leta, T., Techale, B., & Lemi, B. (2018). Genetic variability, heritability and genetic advance of maize (Zea mays L.) inbred lines for yield and yield related traits in southwestern Ethiopia. Journal of Plant Breeding and Crop Science, 10(10), 281–289. https://doi.org/10.5897/JPBCS2018.0742
Talefe, W. (2023). Cluster and principal component analysis of maize inbred lines in low moisture stress areas in Ethiopia. International Journal of Agricultural Science and Food Technology, 9, 59–63. https://doi.org/10.17352/2455-815X.000194
Tena, E., Tadesse, F., Million, F., & Tesfaye, D. (2023). Phenotypic diversity, Heritability, and association of characters in sugarcane genotypes at Metehara Sugar Estate, Ethiopia. Journal of Crop Improvement, 37(6), 874–897.
Thell, L. (2022). Analysis of Genetic Divergence in some Elite Cultivars of Bread Wheat. 14(3), 573–576.
Tiwari, D. N., Tripathi, S. R., Tripathi, M. P., Khatri, N., & Bastola, B. R. (2019). Genetic Variability and Correlation Coefficients of Major Traits in Early Maturing Rice under Rainfed Lowland Environments of Nepal. Advances in Agriculture, 2019, 1–9. https://doi.org/10.1155/2019/5975901
Toor, A. K., & Singh, A. (2023). Evaluation of variability, Heritability and genetic advance for yield and yield components in linseed (Linum usitatissimum L.) genotypes. Journal of Eco-Friendly Agriculture, 18(1), 80–85.
Tuliozi, B., Mantovani, R., Schoepf, I., Tsuruta, S., Mancin, E., & Sartori, C. (2023). Genetic correlations of direct and indirect genetic components of social dominance with fitness and morphology traits in cattle. Genetics Selection Evolution, 55(1), 84. https://doi.org/10.1186/s12711-023-00845-8
Vennela, M. (2023). Genetic Variability, Heritability and Genetic Advance Studies in Field Pea (Pisum Sativum L.) for Yield and Its Attributing Traits. Int. J. Environ. Clim. Change, 13(8), 2190–2197.
Wanga, M. A., Shimelis, H., Mashilo, J., & Laing, M. D. (2021). Opportunities and challenges of speed breeding: A review. Plant Breeding, 140(2), 185–194.
Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557.
Yeshitila, M., Gedebo, A., Degu, H. D., Olango, T. M., & Tesfaye, B. (2023). Study on characters associations and path coefficient analysis for quantitative traits of amaranth genotypes from Ethiopia. Scientific Reports, 13(1), 20981. https://doi.org/10.1038/s41598-023-47869-0
Yin, J., Zhou, M., Lin, Z., Li, Q. Q., & Zhang, Y. Y. (2019). Transgenerational effects benefit offspring across diverse environments: a meta-analysis in plants and animals. Ecology Letters, 22(11), 1976–1986. https://doi.org/10.1111/ele.13373
You, F. M., Song, Q., Jia, G., Cheng, Y., Duguid, S., Booker, H., & Cloutier, S. (2016). ScienceDirect Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design. C.J., 4(2), 107–118. https://doi.org/10.1016/j.cj.2016.01.003
Zewdu, D., Mekonnen, F., & Geleta, N. (2024). Correlation and Path Analysis for Yield and Yield Component Traits on Bread Wheat (Triticum aestivum L.) Genotypes. International Journal of Bio-Resource and Stress Management, 15(1), 1–13. https://doi.org/10.23910/1.2024.5040
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