Interaction of Genotype and Environment on the Productivity of 12 Genotypes of Rice (Oryza sativa L.) using AMMI Analysis

Authors

  • Indra Setiawan Lampung State Polytechnic
  • Dulbari Dulbari Lampung State Polytechnic
  • Jainudin Kartahadimaja Lampung State Polytechnic

DOI:

https://doi.org/10.51699/ijbea.v3i3.50

Keywords:

Adaptation, AMMI, Genotype, Stability

Abstract

Rice is the main food crop for most of the world's population. This research aims to obtain information on the influence of genotype interactions with the environment on potential grain yield characteristics and to obtain genotypes that have stability and adaptability to suboptimal environments. The research was carried out in March–July 2023 at Polinela Organic Farm. The experiment used a completely randomized group design (RKTS). Observations were made on the grain yield of 12 rice genotypes grown in three different environments. Statistical analysis using PBSTAT-GE software. There are three genotypes that have good stability based on eight stability analyses, namely Sertani 13 (G5), Inpari 30 (G12), and Trisakti (G6). Sertani 13 (G5) and Inpari 24 (G2) are genotypes with extensive adaptation. Genotypes based on specific environments are Baroma (G8), PTP 01 (G3), and Inpara 8 (G11), which adapt well to organic environments. Sertani 13 (G5) is adaptive to non-organic environments, and Mentik Susu (G4) is adaptive to aquaponic environments. The highest average production obtained based on the environment is non-organic, with an average yield of 5.95 tons/ha. Baroma (G8) is the genotype with the highest average, namely 6.85 tons/ha.

References

Alwala, S., Kwolek, T., McPherson, M., Pellow, J., & Meyer, D. (2010). A comprehensive comparison between Eberhart and Russell joint regression and GGE biplot analyzes to identify stable and high yielding maize hybrids. Field Crops Research , 119 , 225–230. https://doi.org/10.1016/j.fcr.2010.07.010

Bozo ǧ lu, H., & Gülümser, A. (2000). Determination of genotype × environment interactions of some agronomic characters in dry bean (Phaseolus vulgaris L.). Turkish Journal of Agriculture and Forestry , 24 (2), 211–220. https://doi.org/10.3906/tar-98218

Hadi, AF, & Sa'diyah, H. (2004). AMMI model for genotype x location interaction analysis. Journal of Basic Sciences , 5 (1), 33–41.

Mut, Z., Gülümser, A., & Sirat, A. (2010). Comparison of stability statistics for yield in barley (Hordeum vulgare L.). African Journal of Biotechnology , 9 (11), 1610–1618. https://doi.org/10.5897/ajb10.1404

Sitaresmi, T., Willy, S., Gunarsih, C., Nafisah, N., Nugraha, Y., Sasmita, P., & Daradjat, A. . (2019). Comprehensive Stability Analysis of Rice Genotypes Through Multi-Location Yield Trials Using Pbstat-Ge. Sabrao journal of breeding and genetics , 51 (4), 355–372. https://data.cimmyt.org

Suwarto, & Nasrullah. (2011). Genotype × Environment Interaction for Iron Concentration of Rice in Central Java of Indonesia. Rice Science , 18 (1), 75–78. https://doi.org/10.1016/S1672-6308(11)60011-5

Yan, W., & Kang, M. S. (2002). GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists . CRC press.

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Published

2024-07-16

How to Cite

Setiawan , I., Dulbari, D., & Kartahadimaja , J. (2024). Interaction of Genotype and Environment on the Productivity of 12 Genotypes of Rice (Oryza sativa L.) using AMMI Analysis. International Journal of Biological Engineering and Agriculture , 3(3), 337–346. https://doi.org/10.51699/ijbea.v3i3.50

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