Automated Author ProfileRodrigues, Erina Vitório
Rodrigues, Erina Vitório
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
ABSTRACT The mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass ( Cenchrus purpureus (Schumach.) Morrone ) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.
Authors
- Vidal, Ana Kesia Faria ;
- Daher, Rogério Figueiredo ;
- Ambrósio, Moises ;
- Santana, Josefa Grasiela Silva ;
- Freitas, Rafael Souza ;
- Gravina, Geraldo de Amaral ;
- Rodrigues, Erina Vitório ;
- Stida, Wanessa Francesconi ;
- Souza, Alexandre Gomes de ;
- Leite, Cleudiane Lopes ;
- Farias, João Esdras Calaça ;
- Rangel, Leandro Heitor ;
- Pereira, Antônio Vander
ABSTRACT The mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass ( Cenchrus purpureus (Schumach.) Morrone ) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.
Authors
- Vidal, Ana Kesia Faria ;
- Daher, Rogério Figueiredo ;
- Ambrósio, Moises ;
- Santana, Josefa Grasiela Silva ;
- Freitas, Rafael Souza ;
- Gravina, Geraldo de Amaral ;
- Rodrigues, Erina Vitório ;
- Stida, Wanessa Francesconi ;
- Souza, Alexandre Gomes de ;
- Leite, Cleudiane Lopes ;
- Farias, João Esdras Calaça ;
- Rangel, Leandro Heitor ;
- Pereira, Antônio Vander