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Genomic selection for genotype performance and environmental stability in Coffea canephora. Author(s): ADUNOLA, P.; FERRÃO, M. A. G.; FERRÃO, R. G.; FONSECA, A. F. A. da; VOLPI, P. S.; COMÉRIO, M.; VERDIN FILHO, A. C.; MUNOZ, P. R.; FERRÃO, L. F. V. Coffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to incre... ... Repository: BDPA Publication year: 2023
Analysis of climatic risk favorability of grapevine fungal disease occurrence for Santa Teresa, Espírito Santo State, Brazil. Author(s): RODRIGUES, L. A.; OLIVEIRA, E. C. de; ALVES, M. E. B.; SALES, R. A.; CUNHA JUNIOR, J. de O.; POSSE, R. P.; CARVALHO JÚNIOR, S. M. de; QUARTEZANI, W. Z.; BERILLI, S. da S.; HELL, L. R. The State of Espírito Santo, Brazil, has micro-regions with different climatic and soil conditions, which promote grapevine cultivation vine in several municipalities. However, the grape production pr... ... Repository: BDPA Publication year: 2019
Genomic Selection with Allele Dosage in Panicum maximum Jacq. Author(s): LARA, L. A. de C.; SANTOS, M. F.; JANK, L.; CHIARI, L.; VILELA, M. de M.; AMADEU, R. R.; SANTOS, J. P. R. dos; SILVA, F. G. da; ZENG, Z.-B.; GARCIA, A. A. F. Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotypi... ... Repository: BDPA Publication year: 2019
Index selection can improve the selection efficiency in a rice recurrent selection population. Author(s): GUIMARÃES, P. H. R.; MELO, P. G. S.; CORDEIRO, A. C. C.; TORGA, P. P.; RANGEL, P. H. N.; CASTRO, A. P. de To attain success with selection process, the breeders need to understand the genetic variability into each population developed by breeding program. In this purpose, breeders need to estimate the var... ... Repository: BDPA Publication year: 2021
Climate drivers affecting upland rice yield in the central region of Brazil. Author(s): HEINEMANN, A. B.; STONE, L. F.; SILVA, G. C. C.; MATTA, D. H. da; JUSTINO, L. F.; SILVA, S. C. da The upland rice production is primarily concentrated in a vast area of central Brazil. Given the region’s environmental variability, the performance of rice cultivars can differ significantly. This st... ... Repository: BDPA Publication year: 2024
Cassava yield traits predicted by genomic selection methods. Author(s): ANDRADE, L. R. B. de; SOUSA, M. B. e; OLIVEIRA, E. J. de; RESENDE, M. D. V. de; AZEVEDO, C. F. Genomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and co... ... Repository: BDPA Publication year: 2019
Molecular cloning and AlphaFold modeling of Thyrotropin (ag-TSH) from the amazonian fish pirarucu (Arapaima gigas). Author(s): FREIRE, R. P.; HERNANDEZ-GONZALEZ, J. E.; LIMA, E. R.; SUZUKI, M. F.; OLIVEIRA, J. E. de; TORATI, L. S.; BARTOLINI, P.; SOARES, C. R. J. Arapaima gigas, known as Pirarucu in Brazil, is one of the largest freshwater fish in the world. Some individuals could reach 3m in length and weight up to 200kg. Due to extinction risks and its econo... ... Repository: BDPA Publication year: 2023
An approach based on text mining for knowledge acquisition in diagnostic systems. Author(s): MASSRUHÁ, S. M. F. S.; MARCHI, R.; SILVA, L. M. CUNHA da; SOUZA, K. X. S. de; OLIVEIRA, L. H. M. de; OLIVEIRA, S. R. de M.; MORANDI, M. A. B. Repository: BDPA Publication year: 2007
Triple categorical regression for genomic selection: application to cassava breeding. Author(s): LIMA, L. P.; AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; OLIVEIRA, E. J. de Genome-wide selection (GWS) is currently a technique of great importance in plant breeding, since it improves efficiency of genetic evaluations by increasing genetic gains. The process is based on gen... ... Repository: BDPA Publication year: 2019
Binding affinity prediction using a nonparametric regression model based on physicochemical and structural descriptors of the nano-environment for protein-ligand interactions. Author(s): BORRO, L.; YANO, I. H.; MAZONI, I.; NESHICH, G. We propose a new empirical scoring function for binding affinity prediction modeled based on physicochemical and structural descriptors that characterize the nano-environment that encompass both ligan... ... Repository: BDPA Publication year: 2016

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