PARAMETER GENETIK DAN ANALISIS HUBUNGAN ANTAR SIFAT PADA GENERASI F2 PADI HASIL PERSILANGAN INPARI 31 X BASMATI DELTA 9

Agus Riyanto; Dyah Susanti; Totok Agung Dwi Haryanto

doi:10.25181/jppt.v23i1.2433

Authors

Agus Riyanto Fakultas Pertanian Universitas Jenderal Soedirman
Dyah Susanti
Totok Agung Dwi Haryanto Jurusan Agroteknologi Fakultas Pertanian Universitas Jenderal Soedirman

DOI:

https://doi.org/10.25181/jppt.v23i1.2433

Abstract

One of the goals of Indonesia's rice improvement program is to develop high-yielding varieties with long and slender rice grains. This study aimed to estimate the genetic parameters affecting gene action, amount of gene action, number of gene control, magnitude of genetic variability, heritability, genetic advance, and correlations between yield components and yield of Inpari 31 x Basmati Delta 9 in the F2 generation. The experiment was carried out at an experimental farm at the Faculty of Agriculture, Jenderal Soedirman University, Purwokerto, Central Java, Indonesia. The genetic material used was seed from an F2 population crossed between Inpari 31 and Basmati Delta 9 with the two parental genotypes. Estimates of skewness, kurtosis, genetic variability, heritability, genetic advance, correlations between traits and path analysis were calculated for yield and yield component traits. Results show that additive and complementary epistatic action control yield-related and yield traits. Yield-related trait components and yield are controlled by a monogenic or polygenic genes, depending on the observed trait. Wide genetic variability, high broad sense heritability and high genetic advance were found in the number of productive tillers per hill and grain weight per panicle. These traits show a significant positive correlation and have a direct effect on the yield; therefore, they can be used as traits in the selection to produce high-yielding rice, with long rice sizes and slender shapes. Keywords: F2 population; genetic parameters; interrelationship among traits; rice

Downloads

Download data is not yet available.

References

Ali, E. N. et al. (2018) ‘Genetic variability and character association for earliness, yield and its contributing traits in F2 population of rice (Oryza sativa L.)’, Electronic Journal of Plant Breeding, 9(3), pp. 1163–1169. doi: 10.5958/0975-928X.2018.00145.X.

Anbanandan, V. and Eswaran, R. (2018) ‘Genetic variability studies in rice genotypes’, European Journal of Biotechnology and Bioscience, 6(5), pp. 74–75.

Anwar, M. C. (2021) ‘BPS ungkap Indonesia masih impor beras 356.286 ton di 2020’, Kompas, 29 Maret 2021.

Archana, R. S. et al. (2018) ‘Correlation and path coefficient analysis for grain yield and yield components in rice (Oryza sativa L.)’, International Journal of Chemical Studies, 6(4), pp. 189–195. doi: 10.22271/chemi.2020.v8.i2n.8888.

Balla, M. Y. and Ibrahim, S. E. (2017) ‘Genotypic correlation and path coefficient analysis of soybean [Glycine max (L.) Merr.] for yield and its components’, Agricultural Research and Technology, 7(3), pp. 3–7. doi: 10.19080/ARTOAJ.2017.07.555715.

Barmawi, M. (2007) ‘Pola segregasi dan heritabilitas sifat ketahanan kedelai terhadap Cowpea Mild Mottle Virus populasi Wilis X MLG2521’, Journal HPT Tropika, 7(1), pp. 48–52.

Begum, H. A. and Sobhan, M. A. (1991) ‘Genetic variability, heritability and correlation study in C. capsularis’, Bangladesh J. Jute Fibre Res., 16, pp. 113–118.

Bornare, S. S., Mittra, S. K. and Mehta, A. K. (2014) ‘Genetic variability, correlation and path analysis of floral, yield and its component traits in CMS and Restorer lines of rice (Oryza sativa L)’, Bangladesh Jouranal of Botany, 43(1), pp. 45–52.

BPS (2021) Luas Panen dan Produksi Padi di Indonesia 2020 (Angka Tetap). Badan Pusat Statistik Indonesia, Jakarta.

Chaudhari, P. R. et al. (2018) ‘Rice nutritional and medicinal properties: A review article’, Journal of Pharmacognosy and Phytochemistry, 7(2), pp. 150–156.

Choudhary, A. K., Haider, Z. A., Mishra, S. B., et al. (2018) ‘Assessment of genetic variability for yield and yield attributing traits in F2 and F3 population of rice (Oryza sativa L.) cross’, Current Journal of Applied Science and Technology, 31(2), pp. 1–5. doi: 10.9734/cjast/2018/45875.

Choudhary, A. K., Haider, Z. A., Prasad, K., et al. (2018) ‘Selection response and genetic variability for yield and its component traits of rice (Oryza sativa L.)’, International Journal of Current Microbiology and Applied Sciences, 7(04), pp. 931–945. doi: 10.20546/ijcmas.2018.704.099.

Chozin, M., Sudjatmiko, S., et al. (2017) ‘Analysis of traits association in sweet corn inbred lines as grown under organic crop management’, Sabrao Journal of Breeding and Genetics, 49(4), pp. 361–367.

Chozin, M., Sumardi, et al. (2017) ‘Genetic variability and traits association analyses on F2 generations for determination of selection criteria in Indonesian inland swamp rice breeding’, Australian Journal of Crop Science, 11(5), pp. 535–541. doi: 10.21475/ajcs.17.11.05.p317.

Cuevas, R. P. et al. (2016) ‘Rice grain quality and consumer preferences: A case study of two rural towns in the Philippines’, PLoS ONE, 11(3), pp. 1–17. doi: 10.1371/journal.pone.0150345.

Custodio, M. C. et al. (2019) ‘Rice quality: how is it defined by consumers, industry, food scientists, and geneticists?.’, Trends in Food Science and Technology, 92, pp. 122–137. doi: 10.1016/j.tifs.2019.07.039.

Cyprien, M. and Kumar, V. (2011) ‘Correlation and path coefficient analysis of rice cultivars data’, Journal of Reliability and Statistical Studies, 4(2), pp. 119–131.

Devi, K. R. et al. (2017) ‘Analysis of variability, correlation and path coefficient studies for yield and quality traits in rice (Oryza Sativa L.)’, Agricultural Science Digest, 37(1), pp. 1–9. doi: 10.18805/asd.v0iof.7328.

El-Mohsen, A. A. A., Mahmoud, G. O. and Safina, S. A. (2013) ‘Agronomical evaluation of six soybean cultivars using correlation and regression analysis under different irrigation regime conditions’, Journal of Plant Breeding and Crop Science, 5(5), pp. 91–102.

Faot, M. M., Zubaidah, S. and Kuswantoro, H. (2019) ‘Genetic correlation and path analysis of agronomical traits of soybean (Glycine max) lines infected by CpMMV’, Biodiversitas, 20(6), pp. 1496–1503. doi: 10.13057/biodiv/d200602.

Fehr, W. R. (1991) Principles of Cultivar Development: Theory and Technique. IOWA, USA: Macmillan Publishing Company. doi: 10.1097/00010694-198805000-00012.

Fisher, R. A., Immer, F. R. and Tedin, O. (1932) ‘The genetical interpretation of statistics of the third degree in the study of quantitative inheritance’, Genetics, 17(2), pp. 107–24. doi: 10.1093/genetics/17.3.368.

Govintharaj, P., Manonmani, S. and Robin, S. (2018) ‘Variability and genetic diversity study in an advanced segregating population of rice with bacterial blight resistance genes introgressed’, Ciencia e Agrotecnologia, 42(3), pp. 291–296. doi: 10.1590/1413-70542018423022317.

Hajiaqatabar, A., Kiani, G. and Kazemitabar, S. K. (2016) ‘Correlation and path coefficient analysis for yield and yield components in F2 segregating populations of rice: Scientific note’, Jordan Journal of Agricultural Sciences, 12(3), pp. 749–755. doi: 10.12816/0033377.

Haryanto, T. A. D. et al. (2014) ‘Path coefficient analysis on G39×Ciherang and Mentik Wangi×G39 Rice in F4 Generation’, Agrivita, 36(1), pp. 9–13. doi: 10.17503/agrivita-2014-36-1-p009-013.

Haryanto, T. A. D. and Yoshida, T. (1996) ‘Performance and interrelationship among several characters of pearl millet (Pennisetum typhoideum Rich.) population’, Journal of the Faculty of Agriculture, Kyushu University, 41(1–2), pp. 1–9.

Hema, T. et al. (2019) ‘Studies on genetic variability, association and path coefficient analysis in F2 derivatives of CR 1009 × WP 22-2 for earliness and semi-dwarfism in rice (Oryza sativa L.)’, Electronic Journal of Plant Breeding, 10(2), pp. 585–591. doi: 10.5958/0975-928X.2019.00074.7.

Herawati, R., Masdar and Alnopri (2019) ‘Genetic analysis of grain yield of F4 populations for developing new type of upland rice’, Sabrao Journal of Breeding and Genetics, 51(1), pp. 68–79.

Hermanto, S. (2017) ‘KEBIJAKAN HARGA BERAS DITINJAU DARI DIMENSI PENENTU HARGA Rice Price Policy’, Forum Penelitian Agro Ekonomi, Vol. 35 No. 1, Juli 2017: 31-43, 35(1), pp. 31–43. Available at: http://dx.doi.org/10.21082/fae.v35n1.2017.31-43 31.

Jayaramachandran, M. et al. (2010) ‘Gene action for yield attributing characters in segregating generation (M2) of sorghum (Sorghum bicolor L.)’, Electronic Journal of Plant Breeding, 1(4), pp. 802–805.

Johnson, H. W., Robinson, H. F. and Comstock, R. E. (1955) ‘Estimates of genetic and environmental variability in soybeans’, Agronomy Journal, 47(7), pp. 314–318. doi: 10.2134/agronj1955.00021962004700070009x.

Kementan (2020) Stok beras aman sampai 2020, Kementerian Pertanian Indonesia. doi: 10.5025/hansen1930.13.4_251.

Kishore, N. S. et al. (2015) ‘Genetic variability, correlation and path analysis for yield and yield components in promising rice (Oryza sativa L.) genotypes’, SAARC Journal of Agriculture, 13(1), pp. 99–108. doi: 10.3329/sja.v13i1.24184.

Kozak, M. and Kang, M. S. (2006) ‘Note on modern path analysis in application to crop science’, Communications in Biometry and Crop Science, 1(1), pp. 32–34.

Kozak, M., Krzanowski, W. and Tartanus, M. (2012) ‘Use of the correlation coefficient in agricultural sciences: problems, pitfalls and how to deal with them’, Anais da Academia Brasileira de Ciencias, 84(4), pp. 1147–1156. doi: 10.1590/S0001-37652012000400029.

Lestari, A. P. et al. (2015) ‘Panicle length and weight performance of F3 population from local and introduction hybridization of rice varieties’, HAYATI Journal of Biosciences, 22(2), pp. 87–92.

Mahmud, I. and Kramer, H. H. (1951) ‘Segregation for yield, height, and maturity following a soybean cross’, Agronomy Journal, 43(12), pp. 605–609. doi: 10.2134/agronj1951.00021962004300120005x.

Mustafa, M. et al. (2019) ‘Inheritance study for fruit characters of tomato IPBT78 X IPBT73 using joint scaling test’, IOP Conference Series: Earth and Environmental Science, 382(1), pp. 1–5. doi: 10.1088/1755-1315/382/1/012009.

Muthuramu, S. and Ragavan, T. (2020) ‘Genotypic correlation and path coefficient analysis for yield traits in rainfed rice (Oryza sativa L.)’, Journal of Pharmacognosy and Phytochemistry, 9(2), pp. 1621–1623.

Nafisah et al. (2020) ‘Genetic variabilities of agronomic traits and bacterial leaf blight resistance of high yielding rice varieties’, Indonesian Journal of Agricultural Science, 20(2), pp. 43–54.

Nirmaladevi, G. et al. (2015) ‘Genetic variability, heritability and correlation coefficients of grain quality characters in rice (Oryza sativa L.)’, Sabrao Journal of Breeding and Genetics, 47(4), pp. 424–433. doi: 10.1093/eurpub/ckl252.

Nurhidayah, S., Wahyu, Y. and Suwarno, W. B. (2017) ‘Estimation of genetic parameters and identification of transgressive segregants of population of peanut (Arachis hypogaea L.) in F3 generation’, J. Agron. Indonesia, 45(2), pp. 162–168. doi: 10.24831/jai.v45i2.12940.

Olivoto, T. et al. (2017) ‘Multicollinearity in path analysis: A simple method to reduce its effects’, Agronomy Journal, 109(1), pp. 131–142. doi: 10.2134/agronj2016.04.0196.

Patil, S. and Sahu, V. (2009) ‘Correlation and path analysis of rice germplasm accessions’, International Journal of Plant Sciences, 4(2), pp. 426–428.

Petersen, R. G. (1994) Agricultural Field Experiments: Design and Analysis. New York: Marcel Dekker, Inc.

Prakash, H. P. et al. (2018) ‘Correlation and path coefficient analysis in elite germplasm of rice (Oryza sativa L.)’, International Journal of Current Microbiology and Applied Sciences, 7(7), pp. 177–187. doi: 10.20546/ijcmas.2018.707.400.

Raghavendra, P. and Hittalmani, S. (2016) ‘Genetic parameters of two BC2F1 populations for development of superior male sterile lines pertaining to morpho-floral traits for aerobic rice (Oryza sativa L.)’, SAARC Journal of Agriculture, 13(2), pp. 198–213. doi: 10.3329/sja.v13i2.26580.

Rajamadhan, R., Eswaran, R. and Anandan, A. (2011) ‘Investigation of correlation between traits and path analysis of rice (Oryza Sativa L.) grain yield under coastal salinity’, Electronic Journal of Plant Breeding, 2(4), pp. 538–542.

Rani, C. S. et al. (2016) ‘Genetic variability studies and multivariate analysis in F2 segregating populations involving medicinal rice (Oryza sativa L.) cultivar Kavuni’, International Journal of Agriculture Sciences, 8(35), pp. 1733–1735.

Ratna, M. et al. (2015) ‘Correlation and path coefficients analyses in Basmati rice’, Bangladesh Journal of Agricultural Research, 40(1), pp. 153–161. doi: 10.3329/bjar.v40i1.23768.

Ratner, B. (2009) ‘The correlation coeffi cient: Its values range between + 1 / − 1 , or do they?.’, Journal of Targeting, Measurement and Analysis for Marketing, 17, pp. 139–142. doi: 10.1057/jt.2009.5.

Riyanto, A. et al. (2021) ‘Genetic parameter and analysis of traits interrelationship in F2 rice generation of Inpago Unsoed 1 X Basmati Delta 9’, American-Eurasian Journal of Sustainable Agriculture, 15(1), pp. 15–28. doi: 10.22587/aejsa.2021.15.1.2.

Robson, D. (1956) ‘Applications of the K4 statistic to genetic variance component analyses’, Biometrics, 12(4), pp. 433–444.

Roy, D. (2000) Plant Breeding: Analysis an Explotation of Varian. New Delhi: Narosa Publishing House.

Saleem, M. Y., Iqbal, Q. and Asghar, M. (2013) ‘Genetic variability, heritability, character association and path analysis in F1 hybrids of tomato’, Pakistan Journal of Agricultural Sciences, 50(4), pp. 649–653.

Samak, N. A. et al. (2011) ‘Exploratory studies on genetic variability and genetic control for protein and micronutrient content in F4 and F5’, Asian Journal of Plant Sciences, 10(7), pp. 376–379.

Sembiring, S. A., Siregar, H. and Saragih, B. (2010) ‘IMPLEMENTASI KEBIJAKAN PERBERASAN DI TINGKAT PETANI : KINERJA DAN PERSPEKTIF KE DEPAN Implementation of Rice Policy at Farmers Level : Performance and Future Perspectives PENDAHULUAN Kebijakan perberasan pada dasarnya berkenaan dengan tindakan yang dipili’, Analisis Kebijakan Pertanian, 8(1), pp. 339–361. Available at: http://124.81.126.57/bitstream/handle/123456789/6671/Implementasi Kebijakan Perberasan di Tingkat Petani- Kinerja dan Perspektif ke Depan.pdf?sequence=1&isAllowed=y.

Shah, A. et al. (2018) ‘Estimation of genetic parameters and interrelationship among important traits in bread wheat’, International Journal of Farming and Allied Sciences, 7(3), pp. 93–99.

Sheshaiah et al. (2018) ‘Studies on variability and frequency distribution of yield and yield related traits in F2 population of rice (Oryza sativa L.)’, International Journal of Current Microbiology and Applied Sciences, 7(9), pp. 2048–2052. doi: 10.5958/0975-928X.2018.00145.X.

Singh, R. K. and Chaudhary, B. D. (1979) Biometrical Methods in Quantitative Genetics Analysis. New Delhi: Kalyani Publishers.

Singh, S. K., Singh, C. M. and Lal, G. M. (2011) ‘Assessment of genetic variability for yield and its component characters in rice (Oryza sativa L.)’, Research in Plant Biology, 1(4), pp. 73–76.

Sivasubramanian, S. and Menon, M. (1973) ‘Heterosis and inbreeding depression in rice’, Madras Agricultural Journal, 60, pp. 1139–1144.

Stansfield, W. D. (1991) Schaum’s Outline of Theory and Problems of Genetics. Third. New York: McGraw-Hill Companies.

Steel, R. and Torrie, J. (1960) Principle and Procedure of Statistics. New York, USA: Mc Graw Bork Hall.

Sudeepthi, K. et al. (2020) ‘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(1), pp. 65–69. doi: 10.37992/2020.1101.026.

Sujata, B. et al. (2017) ‘Estimation of gene actions and character association in F3 and F4 generations of little millet cross JK 8 X Peddasame Purple Early (Panicum miliare)’, International Journal of Agricultural Sciences, 13(1), pp. 119–123. doi: 10.15740/has/ijas/13.1/119-123.

Sumathi, K., Ganesan, K. K. N. and Senthil, N. (2018) ‘Variability parameters studies in sorghum downy mildew resistant BC3F3 progenies of maize’, International Journal of Current Microbiology and Applied Sciences, 7(06), pp. 3847–3854. doi: 10.20546/ijcmas.2018.706.453.

Sundaram, K. M. et al. (2019) ‘Genetic variability studies for yield and its components and quality traits with high iron and zinc content in segregating population of rice (Oryza sativa L.)’, International Journal of Chemical Studies, 7(3), pp. 800–805.

Supardi (2013) Aplikasi Statistik Dalam Penelitian: Konsep Statistik Yang Lebih Komprehensif. Jakarta: Change Publication.

Tiwari, D. N. et al. (2019) ‘Genetic variability and correlation coefficients of major traits in early maturing rice under rainfed lowland environments of Nepal’, Advances in Agriculture, 2019, pp. 1–9. doi: 10.1101/520338.

Vijaya, I. and Shailaja, H. (2018) ‘Assessment of genetic parameters for yield and its related traits in f2 populations involving traditional varieties of rice (Oryza sativa L.)’, International Journal of Current Microbiology and Applied Sciences, 7(1), pp. 2210–2217. doi: 10.20546/ijcmas.2018.701.266.

Wahyu, Y. et al. (2018) ‘Short communication: correlation, path analysis, and heritability of phenotypic characters of bread wheat F2 populations’, Biodiversitas, 19(6), pp. 2344–2352. doi: 10.13057/biodiv/d190644.