Yield Performance and Stability of White Cumin (Trachyspermum ammi L.) Genotypes under Multi Environmental Condition

The study was conducted to estimate the effects of genotype, environment, and their interaction on yield and to assess the stability of white cumin genotypes for yield across different testing environments. Nine white cumin genotypes were evaluated using RCBD with three replications at four locations in Ethiopia. The result of combined analysis of variance showed highly significant (p<0.01) differences among genotypes for all traits, the genotype × environment interaction showed highly significant differences for all traits except the number of umbels plant-1. The variances accounted for by the environment, genotypes, and interaction were 87.57%, 1.74%, and 10.66%, respectively. Kulumsa-2020 was the highest yielding (1617.98 kg ha-1), environment; Robe Arsi-2021 was the lowest yielding (165.63 kg ha-1), environment. The higher mean seed yield was recorded from G1 (2,160.4 kg ha-1) at environment 1 (E1), while the smallest mean seed yield was obtained from G8 (80.2 kg ha-1) at environment 2 (E2). The GGE biplot analysis explained 74.39% (IPC1=51.91and IPC2 =22.48%) of G+GEI and divided the eleven environments into three major groups: Group 1 includes E3, E7, E9 and E11;Group 2 were E1,E2,E5 and E10 ; while E4,E6 and E8, were in Group 3. The AMMI analysis of variance for seed yield showed a highly significant (p<0.01) difference among genotypes, environments, and genotype × environment. The environmental effect accounted for 64.03% of the total variation, whereas the genotype × environment and genotype effect accounted for about 1.65% and 10.27% of total sum squares respectively. The first IPCA captured about 50.4% of genotype × environmental interaction sum square, while the second IPCA explained about 25.2%. The two IPCs cumulatively explained 75.6% of genotype × environmental interaction sum square. Environments within the same group gave redundant information about the genotypes and were more correlated. The vertex genotypes G1, G3, G5, G8, and G9 are displayed in the corner of the polygon. G5, G1, and G8 are the most unstable genotypes, whereas G3, G4, and G6 are the most desired and closest to the center of the best genotypes. Environment (E5) was identified as an ideal environment and powerful to discriminate genotypes while environment E8 and E11 was the list discriminating environment. The result gives more information on the stability and genotype × environment interactions; therefore, special considerations should be given for those selected genotypes to future breeding programs in order to develop wide adaptive and yielding genotypes.

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Journal
Asian Journal of Agricultural and Horticultural Research
Published
2025-03-27
DOI
https://doi.org/10.9734/ajahr/2025/v12i2371
Primary Topic
Nigella sativa pharmacological applications
Type
article
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article

Yield Performance and Stability of White Cumin (Trachyspermum ammi L.) Genotypes under Multi Environmental Condition

Gizaw Wegayehu, Nimona Fufa, Dasta Tsagaye, Kedir Jaleto et al.
Asian Journal of Agricultural and Horticultural Research
Nigella sativa pharmacological applications
article

Yield Performance and Stability of White Cumin (Trachyspermum ammi L.) Genotypes under Multi Environmental Condition

Gizaw Wegayehu, Nimona Fufa, Dasta Tsagaye, Kedir Jaleto, Demis Fikre
article en

Abstract

The study was conducted to estimate the effects of genotype, environment, and their interaction on yield and to assess the stability of white cumin genotypes for yield across different testing environments. Nine white cumin genotypes were evaluated using RCBD with three replications at four locations in Ethiopia. The result of combined analysis of variance showed highly significant (p<0.01) differences among genotypes for all traits, the genotype × environment interaction showed highly significant differences for all traits except the number of umbels plant-1. The variances accounted for by the environment, genotypes, and interaction were 87.57%, 1.74%, and 10.66%, respectively. Kulumsa-2020 was the highest yielding (1617.98 kg ha-1), environment; Robe Arsi-2021 was the lowest yielding (165.63 kg ha-1), environment. The higher mean seed yield was recorded from G1 (2,160.4 kg ha-1) at environment 1 (E1), while the smallest mean seed yield was obtained from G8 (80.2 kg ha-1) at environment 2 (E2). The GGE biplot analysis explained 74.39% (IPC1=51.91and IPC2 =22.48%) of G+GEI and divided the eleven environments into three major groups: Group 1 includes E3, E7, E9 and E11;Group 2 were E1,E2,E5 and E10 ; while E4,E6 and E8, were in Group 3. The AMMI analysis of variance for seed yield showed a highly significant (p<0.01) difference among genotypes, environments, and genotype × environment. The environmental effect accounted for 64.03% of the total variation, whereas the genotype × environment and genotype effect accounted for about 1.65% and 10.27% of total sum squares respectively. The first IPCA captured about 50.4% of genotype × environmental interaction sum square, while the second IPCA explained about 25.2%. The two IPCs cumulatively explained 75.6% of genotype × environmental interaction sum square. Environments within the same group gave redundant information about the genotypes and were more correlated. The vertex genotypes G1, G3, G5, G8, and G9 are displayed in the corner of the polygon. G5, G1, and G8 are the most unstable genotypes, whereas G3, G4, and G6 are the most desired and closest to the center of the best genotypes. Environment (E5) was identified as an ideal environment and powerful to discriminate genotypes while environment E8 and E11 was the list discriminating environment. The result gives more information on the stability and genotype × environment interactions; therefore, special considerations should be given for those selected genotypes to future breeding programs in order to develop wide adaptive and yielding genotypes.

Asian Journal of Agricultural and Horticultural ResearchVol. 12(2)
Ethiopian Institute of Agricultural Research (ET)
Openalex Percentile: Top 91%
Nigella sativa pharmacological applications
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