Genotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysis

Feed scarcity during the dry season is common in Ethiopia. The potential of existing indigenous grasses can be harnessed and optimized for inclusion in livestock diets. The objective of this study was to evaluate the performance, stability, and genotype × environment interaction (GEI) for dry matter yield (DMY) and crude protein yield (CPY) and key parameters correlations of four panic grass: Chano (Panicum maximum Jack (PMJ), Panicum virgatum (PV), Gardula (Dichanthelium latifolium (DL), and Degungiziya (Panicum maximum) as standard check (DG(SC))) genotypes across seven diverse environments. The experiment was conducted at Argubatenao (AT), Chanomile (CM), Humbo (HM), and Lemu (LM) in the South and Central Ethiopia region during 2022 and 2023 (seven environments: AT2022, AT2023, CM2022, CM2023, HM2022, HM2023, and LM2023). Experimental field was laid out in a randomized complete block design with three replicates. Data was analyzed using Additive Main Effect and Multiplicative Interaction (AMMI) and Genotype and Genotype × Environment (GGE) biplot analyses with Pearson’s correlation analysis. DMY and CPY including additional forage quality traits of native panicum grasses, and their responses in different environments, were analyzed. The mean DMY performance of the genotypes ranged from 7.75 to 13.99 t/ha, while environmental variation was ranged from 1.37 to 15.42 t/ha. Genotype PMJ outperformed all other genotypes across all testing environments, showing a yield advantage of 21.5% over the mean DMY and 44.6% over check variety (DG). AMMI and GGE biplots provided high yielding genotype (PMJ) with wider adaptations in mega environments of AT2022, AT2023, CM2022, CM2023, and HM2022. The correlation analysis also revealed a strong positive relationship of DMY and CPY with tiller number, plant height, and leaf width, while DMY showed a negative association with IVOMD. DL demonstrated moderate stability across all environments for CP%, IVOMD, and ME. Hence, cultivation of PMJ and DL recommended across suitable environments and variety release in discriminative environments. Further research should include a larger pool of genotypes and more detailed environments to refine selection accuracy and animal testing and molecular or genomic tools could be integrated to strengthen breeding efforts.

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Journal
Discover Sustainability
Published
2026-01-13
DOI
https://doi.org/10.1007/s43621-025-02459-0
Primary Topic
Genetics and Plant Breeding
Type
article
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article

Genotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysis

Jane Wamatu, Toshihiko Yada, Getinet Kebede Kalsa, Tarekegn Yoseph Samago et al.
Discover Sustainability
Genetics and Plant Breeding
article

Genotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysis

Jane Wamatu, Toshihiko Yada, Getinet Kebede Kalsa, Tarekegn Yoseph Samago, Milkias Fanta Heliso, Otoro Olkie Teko, Derrebe Kassa Hibebo, Muluken Zeleke Ekule, Tessema Tesfaye Atumo
article en

Abstract

Feed scarcity during the dry season is common in Ethiopia. The potential of existing indigenous grasses can be harnessed and optimized for inclusion in livestock diets. The objective of this study was to evaluate the performance, stability, and genotype × environment interaction (GEI) for dry matter yield (DMY) and crude protein yield (CPY) and key parameters correlations of four panic grass: Chano (Panicum maximum Jack (PMJ), Panicum virgatum (PV), Gardula (Dichanthelium latifolium (DL), and Degungiziya (Panicum maximum) as standard check (DG(SC))) genotypes across seven diverse environments. The experiment was conducted at Argubatenao (AT), Chanomile (CM), Humbo (HM), and Lemu (LM) in the South and Central Ethiopia region during 2022 and 2023 (seven environments: AT2022, AT2023, CM2022, CM2023, HM2022, HM2023, and LM2023). Experimental field was laid out in a randomized complete block design with three replicates. Data was analyzed using Additive Main Effect and Multiplicative Interaction (AMMI) and Genotype and Genotype × Environment (GGE) biplot analyses with Pearson’s correlation analysis. DMY and CPY including additional forage quality traits of native panicum grasses, and their responses in different environments, were analyzed. The mean DMY performance of the genotypes ranged from 7.75 to 13.99 t/ha, while environmental variation was ranged from 1.37 to 15.42 t/ha. Genotype PMJ outperformed all other genotypes across all testing environments, showing a yield advantage of 21.5% over the mean DMY and 44.6% over check variety (DG). AMMI and GGE biplots provided high yielding genotype (PMJ) with wider adaptations in mega environments of AT2022, AT2023, CM2022, CM2023, and HM2022. The correlation analysis also revealed a strong positive relationship of DMY and CPY with tiller number, plant height, and leaf width, while DMY showed a negative association with IVOMD. DL demonstrated moderate stability across all environments for CP%, IVOMD, and ME. Hence, cultivation of PMJ and DL recommended across suitable environments and variety release in discriminative environments. Further research should include a larger pool of genotypes and more detailed environments to refine selection accuracy and animal testing and molecular or genomic tools could be integrated to strengthen breeding efforts.

Discover SustainabilityVol. 7(1)
Hawassa University (ET), Dilla University (ET), Arba Minch University (ET), Ethiopian Institute of Agricultural Research (ET)
Life in Land
Openalex Percentile: Top 90%
Genetics and Plant Breeding
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