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Genotype × environment interaction insights for yield and yield components in castor via AMMI and GGE biplot models
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  • Published: 20 April 2026

Genotype × environment interaction insights for yield and yield components in castor via AMMI and GGE biplot models

  • K. Sadaiah  ORCID: orcid.org/0000-0002-1199-56191,
  • G. Eswara Reddy1,
  • K. Parimala2,
  • A. Saritha3,
  • G. Madhuri1,
  • V. Divya Rani1,
  • N. Nalini1,
  • T. Rajeshwar Reddy2,
  • S. Vanisri4,
  • M. Sreedhar1 &
  • …
  • L. Krishna1 

Scientific Reports (2026) Cite this article

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Subjects

  • Ecology
  • Genetics
  • Plant sciences

Abstract

Despite its industrial potential, productivity in castor remains constrained by genotype × environment interactions (GEI) which obscure the true genetic potential of hybrids across variable production ecologies. The present investigation sought to elucidate the magnitude and pattern of GEI and to identify stable, high-performing hybrids for yield and yield-contributing traits across diverse agro-climatic conditions of Telangana, India. Eight elite castor hybrids were evaluated across multi-environment trials using AMMI (Additive Main Effects and Multiplicative Interaction) and GGE (Genotype and Genotype × Environment) biplot models to dissect stability, adaptability and environmental representativeness. Highly significant GEI effects were detected for seed yield, days to 50% flowering, number of nodes and hundred-seed weight underscoring the differential response of genotypes across environments. The AMMI biplot effectively captured interaction patterns, identifying Palem (E1) location as the most representative and least interactive environment for yield performance. “Which-won-where” analysis of the GGE biplot delineated mega-environment groupings, with PCH-596 excelling under Tandur (E2) and Tornala (E3) locations while ICH-5 demonstrated superior adaptability to E1. Yield Stability Index (YSI) and GGE ranking analyses consistently recognized PCH-596 (G2) and ICH-5 (G6) as the most stable and high-yielding hybrids across the environments. The integration of AMMI and GGE biplot methodologies proved highly effective in unravelling complex GEI patterns, facilitating the identification of genotypes with broad and specific adaptability. Further, Multi-Trait Stability Index (MTSI) has proven ICH-1160 (G3) as the most stable genotype across the environments. These findings provide a quantitative basis for environment-specific hybrid recommendations and contribute to accelerating genetic gains in castor breeding programs targeting enhanced productivity and resilience.

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Data availability

Data will be made available on request.

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Funding

Authors would like thank Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, Telangana, India – 500 030 for financial support.

Author information

Authors and Affiliations

  1. Regional Agricultural Research Station, PJTAU, Palem, Nagarkurnool District, Telangana, 509 215, India

    K. Sadaiah, G. Eswara Reddy, G. Madhuri, V. Divya Rani, N. Nalini, M. Sreedhar & L. Krishna

  2. Agricultural Research Station, PJTAU, Tandur, Vikarabad District, Telangana, 501 141, India

    K. Parimala & T. Rajeshwar Reddy

  3. Agricultural Research Station, PJTAU, Tornala, Siddipet District, Telangana, 502 114, India

    A. Saritha

  4. Institute of Biotechnology, PJTAU, Rajendranagar, Hyderabad, Telangana, 500 030, India

    S. Vanisri

Authors
  1. K. Sadaiah
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Contributions

Planning and conducting the experiment and contributed significantly to writing the manuscripts [K. Sadaiah and G. Eswara Reddy], Conducted the experiment & data collection [K. Parimala, A. Saritha and T. Rajeshwar Reddy], Crop management and preparation of manuscript [G. Madhuri, V. Divya Rani and N. Nalini], Interpretation of data, review & editing of manuscript [S. Vanisri and M. Sreedhar], Supervision and administrative support [L. Krishna].

Corresponding author

Correspondence to K. Sadaiah.

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The authors declare no competing interests.

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Cite this article

Sadaiah, K., Reddy, G.E., Parimala, K. et al. Genotype × environment interaction insights for yield and yield components in castor via AMMI and GGE biplot models. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44030-5

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  • Received: 29 November 2025

  • Accepted: 09 March 2026

  • Published: 20 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-44030-5

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Keywords

  • Castor
  • Genotype × environment interaction
  • AMMI
  • GGE biplot
  • MTSI
  • Yield
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