Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components
In the semi-arid region of Paraíba, cowpea has low productivity due to irregular rainfall and poor use of production technologies. An extensive study aimed at selecting more productive cultivars was conducted using biometric models. This first work had the following objectives: i. Quantify direct a...
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| Format: | Article |
| Language: | English |
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Facultad de Ciencias Agrarias. Universidad Nacional de Cuyo
2023-07-01
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| Series: | Revista de la Facultad de Ciencias Agrarias |
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| Online Access: | https://revistas.uncu.edu.ar/ojs/index.php/RFCA/article/view/5152 |
| _version_ | 1797771071032655872 |
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| author | Francisco Cássio Gomes Alvino Rodolfo Rodrigo de Almeida Lacerda Leonardo de Sousa Alves Lauter Silva Souto Rômulo Gil de Luna Marcelo Cleon de Castro Silva Jussara Silva Dantas Jabob Silva Souto Diogo Gonçalves Neder João de Andrade Dutra Filho Anielson dos Santos Souza |
| author_facet | Francisco Cássio Gomes Alvino Rodolfo Rodrigo de Almeida Lacerda Leonardo de Sousa Alves Lauter Silva Souto Rômulo Gil de Luna Marcelo Cleon de Castro Silva Jussara Silva Dantas Jabob Silva Souto Diogo Gonçalves Neder João de Andrade Dutra Filho Anielson dos Santos Souza |
| author_sort | Francisco Cássio Gomes Alvino |
| collection | DOAJ |
| description |
In the semi-arid region of Paraíba, cowpea has low productivity due to irregular rainfall and poor use of production technologies. An extensive study aimed at selecting more productive cultivars was conducted using biometric models. This first work had the following objectives: i. Quantify direct and indirect effects of primary and secondary components on grain production; ii. Identify variables with greater potential for cultivar selection in the semiarid region of Paraíba and iii. Determine the most appropriate selection strategies for the evaluated variables. The experiment was conducted in an experimental field. The influence of 6 primary and 6 secondary production components was evaluated on grain yield. Data were subjected to ANOVA. Genetic parameters, correlations and path analysis were estimated. Given the strong direct phenotypic and genotypic effects, pod yield results the most promising variable for higher grain yield selection. Direct and simultaneous selections are the most suitable strategies for the set of evaluated variables. However, further studies on selection indices are necessary to maximize genetic gains.
Highlights
• Variables with greater potential were identified for the selection of superior cultivars of cowpea in the semiarid region of Paraíba.
• The pod yield variable (PP) seems promising for cultivar selection considering higher grain yield (GY).
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| first_indexed | 2024-03-12T21:32:12Z |
| format | Article |
| id | doaj.art-0fb9ec13957445dd99c0d884942fff82 |
| institution | Directory Open Access Journal |
| issn | 0370-4661 1853-8665 |
| language | English |
| last_indexed | 2024-03-12T21:32:12Z |
| publishDate | 2023-07-01 |
| publisher | Facultad de Ciencias Agrarias. Universidad Nacional de Cuyo |
| record_format | Article |
| series | Revista de la Facultad de Ciencias Agrarias |
| spelling | doaj.art-0fb9ec13957445dd99c0d884942fff822023-07-27T17:19:53ZengFacultad de Ciencias Agrarias. Universidad Nacional de CuyoRevista de la Facultad de Ciencias Agrarias0370-46611853-86652023-07-0155110.48162/rev.39.102Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production componentsFrancisco Cássio Gomes Alvino0Rodolfo Rodrigo de Almeida Lacerda1Leonardo de Sousa Alves2Lauter Silva Souto3Rômulo Gil de Luna4Marcelo Cleon de Castro Silva5Jussara Silva Dantas6Jabob Silva Souto7Diogo Gonçalves Neder8João de Andrade Dutra Filho9Anielson dos Santos Souza 10Federal University of Viçosa. Department of Agricultural Engineering. Av. Peter Henry Rolfs s/n. Campus Universitário. CEP: 36570-900. Viçosa. Paraíba. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. BrazilFederal Rural University of the Semiarid. Department of Plant Sciences. Rua Francisco Mota 572. Pres. Costa e Silva. CEP: 59625-900 Mossoró. Rio Grande do Norte. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. BrazilFederal University of Campina Grande. Forestry Engineering Academic Unit. University Avenue s/n. Santa Cecília 58700970. Patos. Paraíba. BrazilCampina Grande State University. Rua Baraúnas, 351. CEP: 58429-500. Campina Grande. Paraíba. Brazil.Federal University of Pernambuco. Vitoria Academic Center/ Biological Science Nucleus. Rua Alto do Reservatório. s/n Bela Vista. CEP: 55608-680. Vitória de Santo Antão. Pernambuco. BrazilFederal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. Brazil In the semi-arid region of Paraíba, cowpea has low productivity due to irregular rainfall and poor use of production technologies. An extensive study aimed at selecting more productive cultivars was conducted using biometric models. This first work had the following objectives: i. Quantify direct and indirect effects of primary and secondary components on grain production; ii. Identify variables with greater potential for cultivar selection in the semiarid region of Paraíba and iii. Determine the most appropriate selection strategies for the evaluated variables. The experiment was conducted in an experimental field. The influence of 6 primary and 6 secondary production components was evaluated on grain yield. Data were subjected to ANOVA. Genetic parameters, correlations and path analysis were estimated. Given the strong direct phenotypic and genotypic effects, pod yield results the most promising variable for higher grain yield selection. Direct and simultaneous selections are the most suitable strategies for the set of evaluated variables. However, further studies on selection indices are necessary to maximize genetic gains. Highlights • Variables with greater potential were identified for the selection of superior cultivars of cowpea in the semiarid region of Paraíba. • The pod yield variable (PP) seems promising for cultivar selection considering higher grain yield (GY). https://revistas.uncu.edu.ar/ojs/index.php/RFCA/article/view/5152Path analysisGenetic improvementSelectionProductivityRelationships among charactersVigna unguiculata (L.) Walp. |
| spellingShingle | Francisco Cássio Gomes Alvino Rodolfo Rodrigo de Almeida Lacerda Leonardo de Sousa Alves Lauter Silva Souto Rômulo Gil de Luna Marcelo Cleon de Castro Silva Jussara Silva Dantas Jabob Silva Souto Diogo Gonçalves Neder João de Andrade Dutra Filho Anielson dos Santos Souza Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components Revista de la Facultad de Ciencias Agrarias Path analysis Genetic improvement Selection Productivity Relationships among characters Vigna unguiculata (L.) Walp. |
| title | Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components |
| title_full | Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components |
| title_fullStr | Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components |
| title_full_unstemmed | Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components |
| title_short | Biometric genetics in cowpea beans (Vigna unguiculata (L.) Walp) I: phenotypic and genotypic relations among production components |
| title_sort | biometric genetics in cowpea beans vigna unguiculata l walp i phenotypic and genotypic relations among production components |
| topic | Path analysis Genetic improvement Selection Productivity Relationships among characters Vigna unguiculata (L.) Walp. |
| url | https://revistas.uncu.edu.ar/ojs/index.php/RFCA/article/view/5152 |
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