Academic Journal
GGE and AMMI biplot analyses of soybean ( Glycine max L. Merr) for yield and its components
| Title: | GGE and AMMI biplot analyses of soybean ( Glycine max L. Merr) for yield and its components |
|---|---|
| Authors: | Vincent Ezin, Mohamed Salim Moussa, Fatimata Bachabi, Ulrich Herbert Gbemenou, Adam Ahanchede |
| Source: | CABI Agriculture and Bioscience. |
| Publisher Information: | CABI Publishing, 2025. |
| Publication Year: | 2025 |
| Description: | Soybean is an important leguminous crop that is mostly produced in the world due to its high protein content. However, soybean production in Benin has been hampered by low yields of around 1 ton per hectare, which is caused by many factors, including abiotic and biotic issues. The objective of this research was to evaluate the response of 28 soybean genotypes under four environments, in order to identify the best genotypes. The study was conducted at two sites in Benin: IITA-Benin (South) and Pénéssoulou in Bassila district (North) in 2 years. An alpha lattice design with 3 replications was used, and 17 quantitative variables were collected at both sites. Analysis of variance showed a highly significant difference (p < 0.001) in all variables at the level of genotype-environment interaction. The genotypes G2, G27, G18, G28, G22, and G17 are the most stable in terms of yield, and the closest to the ideal genotypes. In Environments 1 and 3, the accessions demonstrated higher yields, with G2 recording the highest yield (over 4t/ha), compared to Environments 2 and 4. We advocate for the utilization of the above high-yielding genotypes by producers, as well as for their incorporation as breeding materials to enhance soybean improvement. |
| Document Type: | Article |
| Language: | English |
| ISSN: | 2662-4044 |
| DOI: | 10.1079/ab.2025.0036 |
| Accession Number: | edsair.doi...........a6209490fe0c23190d308af0df29d6ea |
| Database: | OpenAIRE |
| FullText | Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: GGE and AMMI biplot analyses of soybean ( Glycine max L. Merr) for yield and its components – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Vincent+Ezin%22">Vincent Ezin</searchLink><br /><searchLink fieldCode="AR" term="%22Mohamed+Salim+Moussa%22">Mohamed Salim Moussa</searchLink><br /><searchLink fieldCode="AR" term="%22Fatimata+Bachabi%22">Fatimata Bachabi</searchLink><br /><searchLink fieldCode="AR" term="%22Ulrich+Herbert+Gbemenou%22">Ulrich Herbert Gbemenou</searchLink><br /><searchLink fieldCode="AR" term="%22Adam+Ahanchede%22">Adam Ahanchede</searchLink> – Name: TitleSource Label: Source Group: Src Data: <i>CABI Agriculture and Bioscience</i>. – Name: Publisher Label: Publisher Information Group: PubInfo Data: CABI Publishing, 2025. – Name: DatePubCY Label: Publication Year Group: Date Data: 2025 – Name: Abstract Label: Description Group: Ab Data: Soybean is an important leguminous crop that is mostly produced in the world due to its high protein content. However, soybean production in Benin has been hampered by low yields of around 1 ton per hectare, which is caused by many factors, including abiotic and biotic issues. The objective of this research was to evaluate the response of 28 soybean genotypes under four environments, in order to identify the best genotypes. The study was conducted at two sites in Benin: IITA-Benin (South) and Pénéssoulou in Bassila district (North) in 2 years. An alpha lattice design with 3 replications was used, and 17 quantitative variables were collected at both sites. Analysis of variance showed a highly significant difference (p < 0.001) in all variables at the level of genotype-environment interaction. The genotypes G2, G27, G18, G28, G22, and G17 are the most stable in terms of yield, and the closest to the ideal genotypes. In Environments 1 and 3, the accessions demonstrated higher yields, with G2 recording the highest yield (over 4t/ha), compared to Environments 2 and 4. We advocate for the utilization of the above high-yielding genotypes by producers, as well as for their incorporation as breeding materials to enhance soybean improvement. – Name: TypeDocument Label: Document Type Group: TypDoc Data: Article – Name: Language Label: Language Group: Lang Data: English – Name: ISSN Label: ISSN Group: ISSN Data: 2662-4044 – Name: DOI Label: DOI Group: ID Data: 10.1079/ab.2025.0036 – Name: AN Label: Accession Number Group: ID Data: edsair.doi...........a6209490fe0c23190d308af0df29d6ea |
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