Eduardo Luiz Goulart Knebel, I. Carvalho, Murilo Vieira Loro, G. H. Demari, Rafael Soares Ourique, João Pedro Dalla Roza
{"title":"南巴西大德州大豆品种战略定位","authors":"Eduardo Luiz Goulart Knebel, I. Carvalho, Murilo Vieira Loro, G. H. Demari, Rafael Soares Ourique, João Pedro Dalla Roza","doi":"10.18188/sap.v20i4.29136","DOIUrl":null,"url":null,"abstract":"This work aims to highlight the best soybean genotypes for specific environments in the Northwest Region of the State of Rio Grande do Sul. The experiment was carried out in the 2018/19 crop season in fifteen cultivation environments in the Northwest region of the state of Rio Grande do Sul, using 52 soybean genotypes in 15 growing environments. The experimental design used was lattice with treatments (growing environments) arranged in three replications. In each useful area of the experimental unit, the grain productivity of the genotypes was evaluated. Then, the Restricted Maximum Likelihood (REML) method was applied to estimate the variance components and genetic parameters. The following variance components were estimated: Genetic variation (Vg) and phenotypic variation (Vp). The genetic parameters estimated were: broad sense heritability (H²), coefficient of genotypic variation (CVg), coefficient of residual variation (CVe), ratio between genetic and residual coefficient (CVr) and selective accuracy (Ac). The phenotypic expression of grain yield is determined by 17% due to genetic effects and 83% by the environment. The NS 6909 RR IPRO, NS 5445 IPRO, DM 5958 IPRO and DM 6563 IPRO genotypes showed greater genetic gains for grain yield. The environments Doutor Maurício Cardoso (RS), Nova Ramada (RS) and Independência (RS) are characterized as favorable environments.","PeriodicalId":30289,"journal":{"name":"Scientia Agraria Paranaensis","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Strategic positioning of soybean cultivars in the state of Rio Grande do Sul\",\"authors\":\"Eduardo Luiz Goulart Knebel, I. Carvalho, Murilo Vieira Loro, G. H. Demari, Rafael Soares Ourique, João Pedro Dalla Roza\",\"doi\":\"10.18188/sap.v20i4.29136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work aims to highlight the best soybean genotypes for specific environments in the Northwest Region of the State of Rio Grande do Sul. The experiment was carried out in the 2018/19 crop season in fifteen cultivation environments in the Northwest region of the state of Rio Grande do Sul, using 52 soybean genotypes in 15 growing environments. The experimental design used was lattice with treatments (growing environments) arranged in three replications. In each useful area of the experimental unit, the grain productivity of the genotypes was evaluated. Then, the Restricted Maximum Likelihood (REML) method was applied to estimate the variance components and genetic parameters. The following variance components were estimated: Genetic variation (Vg) and phenotypic variation (Vp). The genetic parameters estimated were: broad sense heritability (H²), coefficient of genotypic variation (CVg), coefficient of residual variation (CVe), ratio between genetic and residual coefficient (CVr) and selective accuracy (Ac). The phenotypic expression of grain yield is determined by 17% due to genetic effects and 83% by the environment. The NS 6909 RR IPRO, NS 5445 IPRO, DM 5958 IPRO and DM 6563 IPRO genotypes showed greater genetic gains for grain yield. The environments Doutor Maurício Cardoso (RS), Nova Ramada (RS) and Independência (RS) are characterized as favorable environments.\",\"PeriodicalId\":30289,\"journal\":{\"name\":\"Scientia Agraria Paranaensis\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientia Agraria Paranaensis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18188/sap.v20i4.29136\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientia Agraria Paranaensis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18188/sap.v20i4.29136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Strategic positioning of soybean cultivars in the state of Rio Grande do Sul
This work aims to highlight the best soybean genotypes for specific environments in the Northwest Region of the State of Rio Grande do Sul. The experiment was carried out in the 2018/19 crop season in fifteen cultivation environments in the Northwest region of the state of Rio Grande do Sul, using 52 soybean genotypes in 15 growing environments. The experimental design used was lattice with treatments (growing environments) arranged in three replications. In each useful area of the experimental unit, the grain productivity of the genotypes was evaluated. Then, the Restricted Maximum Likelihood (REML) method was applied to estimate the variance components and genetic parameters. The following variance components were estimated: Genetic variation (Vg) and phenotypic variation (Vp). The genetic parameters estimated were: broad sense heritability (H²), coefficient of genotypic variation (CVg), coefficient of residual variation (CVe), ratio between genetic and residual coefficient (CVr) and selective accuracy (Ac). The phenotypic expression of grain yield is determined by 17% due to genetic effects and 83% by the environment. The NS 6909 RR IPRO, NS 5445 IPRO, DM 5958 IPRO and DM 6563 IPRO genotypes showed greater genetic gains for grain yield. The environments Doutor Maurício Cardoso (RS), Nova Ramada (RS) and Independência (RS) are characterized as favorable environments.