Open Access

Multi-Environment Yield Stability and Performance Assessment of Dual-Purpose Barley Genotypes Using Integrated Ammi, Blup, and Non-Parametric Statistical Frameworks

PDF

Dr. Budi Santoso ¹ , Prof. Sari Wulandari ¹ ,

⁴ Department of Scientific Policy Analysis Indonesian Institute of Knowledge Systems, Jakarta, Indonesia

⁴ University of Technology and Innovation, Yogyakarta, Indonesia

Abstract

The evaluation of genotype × environment interaction (GEI) is a fundamental requirement in crop improvement programs, particularly for dual-purpose barley where both forage and grain productivity must be optimized under variable agro-ecological conditions. This study presents an integrated analytical framework combining Additive Main Effects and Multiplicative Interaction (AMMI), Best Linear Unbiased Prediction (BLUP), and non-parametric stability measures to assess yield performance and stability of barley genotypes across multi-environment trials. The objective is to identify high-yielding and stable genotypes suitable for diverse production environments by leveraging complementary statistical methodologies.

Existing literature highlights the importance of integrating parametric and non-parametric approaches for robust stability assessment, as demonstrated in barley and other cereal crops (Mehraban et al., 2019; PourAboughadareh et al., 2022). Comparative frameworks such as AMMI and BLUP have been widely used for improving selection accuracy under GEI complexity (Gonçalves et al., 2020). Furthermore, simulation-based and online computational tools for stability analysis enhance interpretability and decision-making in breeding programs (Pour-Aboughadareh et al., 2019).

The integrated framework in this study synthesizes variance decomposition, multiplicative interaction modeling, and rank-based stability indices to improve selection efficiency. Results indicate that combining AMMI, BLUP, and non-parametric metrics improves the reliability of genotype classification under heterogeneous environmental conditions. The study contributes to precision breeding strategies for barley improvement programs targeting yield stability under climate variability.

Keywords

Barley genotypes, genotype × environment interaction, AMMI model, BLUP analysis

References

Ahakpaz F., Abdi H., Neyestani E., Hesami A., Mohammadi B., Nader Mahmoudi K., Abedi-Asl G., JazayeriNoshabadi M.R., Ahakpaz F., Alipour H.(2021). Genotype-by-environment interaction analysis for grain yield of barley genotypes under dryland conditions and the role of monthly rainfall.Agric Water Manag 245:10665

Anuradha N., Patro T.S.S.K., Singamsetti A., Sandhya Rani Y., Triveni U., NirmalaKumari A., Govanakoppa N., Lakshmi Pathy T. and Tonapi V.A.(2022). Comparative Study of AMMI- and BLUPBased Simultaneous Selection for Grain Yield and Stability of Finger Millet [Eleusinecoracana (L.) Gaertn.]Genotypes. Front. Plant Sci. 12:786839.

Bocianowski J., Tratwal A., NowosadK .(2021). Genotype by environment interaction for main winter triticale varieties characteristics at two levels of technology using additive main effects and multiplicative interaction model.Euphytica 217:26

George N., Lundy M .(2019). Quantifying genotype x Environment effects in longterm common wheat yield trials from an agroecologically diverse production region. Crop Science 59:1960–1972

Gerrano A.S., Rensburg W.S.J.V., Mathew I., Shayanowako A.I.T., Bairu M.W., Venter S.L., Swart W., Mofokeng A., Mellem J., Labuschagne M.(2020). Genotype and genotype x environment interaction effects on the grain yield performance of cowpea genotypes in the dry land farming system in South Africa. Euphytica 216:80

Gonçalves G. de M. C., Gomes R. L. F., Lopes Â. C. de A. and Vieira P. Fe. de M. J. (2020). Adaptability and yield stability of soybean genotypes by REML/BLUP and GGE Biplot. Crop Breeding and Applied Biotechnology, 20(2): e282920217.

Mehraban R. A., Hossein-Pour T., Koohkan E., Ghasemi S., Moradkhani H., Siddique K.H.(2019). Integrating different stability models to investigate genotype × environment interactions and identify stable and high-yielding barley genotypes. Euphytica 215:63

PourAboughadareh, A., Ali B., Ali K. S., Mehdi J., Akbar M., Ahmad G., Kamal S.H., Hassan Z., PoodinehOmid andMasoome, K. (2022). Dissection of genotypebyenvironment interaction and yield stability analysis in barley using AMMI model and stability statistics. Bulletin of the National Research Centre 46:19

Pour-Aboughadareh, A., Yousefian M., Moradkhani H., Poczai P., and Siddique K.H.(2019). STABILITYSOFT: A new online program to calculate parametric and non- parametric stability statistics for crop traits. Applications in Plant Sciences 7(1): e1211

Silva E. M. da, Nunes E. W. L. P., Costa J. M. da, Ricarte A. de O., Nunes G. H. de S. and Aragão Fernando Antonio Souza de .(2019). Genotype x environment interaction, adaptability and stability of ‘Piel de Sapo’ melon hybrids through mixed models Crop Breeding and Applied Biotechnology, 19(4): 402-411.

Sousa, A.M.C.B., Silva V.B., Lopes A.C.A., Ferreira-Gomes R.L. and CarvalhoL.C.B.(2020). Prediction of grain yield, adaptability, and stability in landrace varieties of lima bean (Phaseoluslunatus L.) Crop Breeding

Most read articles by the same author(s)

<< < 1 2 3 > >>

Critique Open Research & Review

Multi-Environment Yield Stability and Performance Assessment of Dual-Purpose Barley Genotypes Using Integrated Ammi, Blup, and Non-Parametric Statistical Frameworks

Abstract

Keywords

References

Most read articles by the same author(s)

Similar Articles