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Found 17 results
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2016
F. R. F. Teixeira, Nascimento, M., Nascimento, A. C. C., Silva, F. Fe, Cruz, C. D., Azevedo, C. F., Paixão, D. M., Barroso, L. M. A., Verardo, L. L., de Resende, M. D. V., Guimarães, S. E. F., Lopes, P. S., Teixeira, F. R. F., Nascimento, M., Nascimento, A. C. C., Silva, F. Fe, Cruz, C. D., Azevedo, C. F., Paixão, D. M., Barroso, L. M. A., Verardo, L. L., de Resende, M. D. V., Guimarães, S. E. F., and Lopes, P. S., Factor analysis applied to genome prediction for high-dimensional phenotypes in pigs, vol. 15, p. -, 2016.
F. R. F. Teixeira, Nascimento, M., Nascimento, A. C. C., Silva, F. Fe, Cruz, C. D., Azevedo, C. F., Paixão, D. M., Barroso, L. M. A., Verardo, L. L., de Resende, M. D. V., Guimarães, S. E. F., Lopes, P. S., Teixeira, F. R. F., Nascimento, M., Nascimento, A. C. C., Silva, F. Fe, Cruz, C. D., Azevedo, C. F., Paixão, D. M., Barroso, L. M. A., Verardo, L. L., de Resende, M. D. V., Guimarães, S. E. F., and Lopes, P. S., Factor analysis applied to genome prediction for high-dimensional phenotypes in pigs, vol. 15, p. -, 2016.
I. B. Gois, Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., and Machado, M. A., Genome wide selection in Citrus breeding, vol. 15, no. 4, p. -, 2016.
Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and Capes (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) for the research fellowship of the first author. Research supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Processes #2007/08435-5 and #2011/18605-0) and Instituto Nacional de Ciência e Tecnologia (INCT) de Genômica para Melhoramento de Citros (Process #573848/2008-4). REFERENCES Asins MJ, Fernandez-Ribacoba J, Bernet GP, Gadea J, et al (2012). The position of the major QTL for Citrus tristeza virus resistance is conserved among Citrus grandis, C. aurantium and Poncirus trifoliata. Mol. Breed. 29: 575-587. http://dx.doi.org/10.1007/s11032-011-9574-x Cavalcanti JJV, Resende MDV, Santos FHC, Pinheiro CR, et al (2012). Predição simultânea dos efeitos de marcadores moleculares e seleção genômica ampla em cajueiro. Rev. Bras. Frutic. 34: 840-846. http://dx.doi.org/10.1590/S0100-29452012000300025 Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA, et al (2010). The impact of genetic architecture on genome-wide evaluation methods. Genetics 185: 1021-1031. http://dx.doi.org/10.1534/genetics.110.116855 Daetwyler HD, Calus MPL, Pong-Wong R, de Los Campos G, et al (2013). Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking. Genetics 193: 347-365. http://dx.doi.org/10.1534/genetics.112.147983 Endelman JB, et al (2011). Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4: 250-255. http://dx.doi.org/10.3835/plantgenome2011.08.0024 Gmitter Junior FG, Chen C, Machado MA, Souza AA, et al (2012). Citrus genomics. Tree Genet. Genomes 8: 611-626. http://dx.doi.org/10.1007/s11295-012-0499-2 Goddard ME, Hayes BJ, Meuwissen THE, et al (2011). Using the genomic relationship matrix to predict the accuracy of genomic selection. J. Anim. Breed. Genet. 128: 409-421. http://dx.doi.org/10.1111/j.1439-0388.2011.00964.x Grattapaglia D, Resende MDV, et al (2011). Genomic selection in forest tree breeding. Tree Genet. Genomes 7: 241-255. http://dx.doi.org/10.1007/s11295-010-0328-4 Gussen O, Uzun A, Seday U, Kafa G, et al (2011). QTL analysis and regression model for estimating fruit setting in young Citrus trees based on molecular markers. Sci. Hortic. (Amsterdam) 130: 418-424. http://dx.doi.org/10.1016/j.scienta.2011.07.010 Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME, et al (2009). Invited review: Genomic selection in dairy cattle: progress and challenges. J. Dairy Sci. 92: 433-443. http://dx.doi.org/10.3168/jds.2008-1646 Heffner EL, Sorrells ME, Jannink JL, et al (2009). Genomic selection for crop improvement. Crop Sci. 49: 1-12. http://dx.doi.org/10.2135/cropsci2008.08.0512 Henderson CR (1973). Maximum likelihood estimation of variance components. Unpublished manuscripts, Animal Science Dept., Cornell University. Ito TM, Polido PB, Rampim MC, Kaschuk G, et al (2014). Genome-wide identification and phylogenetic analysis of the AP2/ERF gene superfamily in sweet orange (Citrus sinensis). Genet. Mol. Res. 13: 7839-7851. http://dx.doi.org/10.4238/2014.September.26.22 Iwata H, Hayashi T, Terakami S, Takada N, et al (2013). Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia. Breed. Sci. 63: 125-140. http://dx.doi.org/10.1270/jsbbs.63.125 Jaccoud D, Peng K, Feinstein D, Kilian A, et al (2001). Diversity arrays: a solid state technology for sequence information independent genotyping. Nucleic Acids Res. 29: E25. http://dx.doi.org/10.1093/nar/29.4.e25 Jarrell DC, Roose ML, Traugh SN, Kupper RS, et al (1992). A genetic map of citrus based on the segregation of isozymes and RFLPs in an intergeneric cross. Theor. Appl. Genet. 84: 49-56. http://dx.doi.org/10.1007/BF00223980 Kemper KE, Goddard ME, et al (2012). Understanding and predicting complex traits: knowledge from cattle. Hum. Mol. Genet. 21 (R1): R45-R51. http://dx.doi.org/10.1093/hmg/dds332 Kumar S, Bink MCAM, Volz RK, Bus VGM, et al (2012). Towards genomic selection in apple (Malus × domestica Borkh.) breeding programmes: Prospects, challenges and strategies. Tree Genet. Genomes 8: 1-14. http://dx.doi.org/10.1007/s11295-011-0425-z Lande R, Thompson R, et al (1990). Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124: 743-756. Legarra A, Robert-Granié C, Manfredi E, Elsen JM, et al (2008). Performance of genomic selection in mice. Genetics 180: 611-618. http://dx.doi.org/10.1534/genetics.108.088575 Machado MA, Cristofani-Yaly M, Bastianel M, et al (2011). Breeding, genetic and genomic of citrus for disease resistance. Rev. Bras. Frutic. 33: 158-172. http://dx.doi.org/10.1590/S0100-29452011000500019 Meuwissen THE, Hayes BJ, Goddard ME, et al (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819-1829. Misztal I, Legarra A, Aguilar I, et al (2009). Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci. 92: 4648-4655. http://dx.doi.org/10.3168/jds.2009-2064 Patterson HD, Thompson R, et al (1971). Recovery of inter-block information when block sizes are unequal. Biometrika 58: 545-554. http://dx.doi.org/10.1093/biomet/58.3.545 R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Resende MDV (2002). Genética Biométrica e estatística no melhoramento de plantas perenes. Brasília: Embrapa Informação tecnológica. Resende MDV, Duarte JB, et al (2007). Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesqui. Agropecu. Trop. 37: 182-194. Resende MDV, Lopes OS, Silva RL, Pires IE, et al (2008). Seleção genômica ampla (GWS) e maximização da eficiência do melhoramento genético. Pesq. Flor. Bra. 56: 63-77. Resende MDV, Resende MFRJrSansaloniCP, Petroli CD, et al (2012). Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. New Phytol. 194: 116-128. http://dx.doi.org/10.1111/j.1469-8137.2011.04038.x Resende MDV, Silva FF, Resende MFR, Junior. and Azevedo CF (2014). Genome-wide selection. In: Biotechnology and Plant Breeding (Borem A and Fritsche-Neto R, eds.). Elsevier. Resende MFJrMuñozP, Resende MDV, Garrick DJ, et al (2012). Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190: 1503-1510. http://dx.doi.org/10.1534/genetics.111.137026 Siviero A, Cristofani M, Boava LP, Machado MA, et al (2002). Mapeamento de QTLs associados à produção de frutos e sementes em híbridos de Citrus sunki vs Poncirus trifoliata. Rev. Bras. Frutic. 24: 741-743. http://dx.doi.org/10.1590/S0100-29452002000300045 Siviero A, Cristofani M, Furtado EL, Garcia AAF, et al (2006). Identification of QTLs associated with citrus resistance to Phytophthora gummosis. J. Appl. Genet. 47: 23-28. http://dx.doi.org/10.1007/BF03194595 Talon M and Gmitter Junior FG (2008). Citrus genomics. Intern. J. Plant Genomics: 1-17. Viana AP and Resende MDV (2014). Seleção Genômica Ampla (GWS). In: Genética Quantitativa no Melhoramento de Fruteiras (Viana AP, Resende MDV, eds.). Interciência, Rio de Janeiro. Viana AP, Resende MDV, Riaz S, Walker MA, et al (2016). Genome selection in fruit breeding: application to table grapes. Sci. Agric. 73: 142-149. http://dx.doi.org/10.1590/0103-9016-2014-0323 Wong CK, Bernardo R, et al (2008). Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theor. Appl. Genet. 116: 815-824. http://dx.doi.org/10.1007/s00122-008-0715-5 Zapata-Velenzuela J, Whetten RW, Neale D, Mckeand S, et al (2013). Genomic estimated breeding values using genomic relationship matrices in a cloned population of Loblolly Pine. Genes Genom. Genet 3: 909-916. Zhao Y, Gowda M, Liu W, Wurschum T, et al (2013). Choice of shrinkage parameter and prediction of genomic breeding values in elite maize breeding populations. Plant Breed. 132: 99-106. http://dx.doi.org/10.1111/pbr.12008 Zhong S, Dekkers JCM, Fernando RL, Jannink JL, et al (2009). Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study. Genetics 182: 355-364. http://dx.doi.org/10.1534/genetics.108.098277
I. B. Gois, Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., and Machado, M. A., Genome wide selection in Citrus breeding, vol. 15, no. 4, p. -, 2016.
Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and Capes (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) for the research fellowship of the first author. Research supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Processes #2007/08435-5 and #2011/18605-0) and Instituto Nacional de Ciência e Tecnologia (INCT) de Genômica para Melhoramento de Citros (Process #573848/2008-4). REFERENCES Asins MJ, Fernandez-Ribacoba J, Bernet GP, Gadea J, et al (2012). The position of the major QTL for Citrus tristeza virus resistance is conserved among Citrus grandis, C. aurantium and Poncirus trifoliata. Mol. Breed. 29: 575-587. http://dx.doi.org/10.1007/s11032-011-9574-x Cavalcanti JJV, Resende MDV, Santos FHC, Pinheiro CR, et al (2012). Predição simultânea dos efeitos de marcadores moleculares e seleção genômica ampla em cajueiro. Rev. Bras. Frutic. 34: 840-846. http://dx.doi.org/10.1590/S0100-29452012000300025 Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA, et al (2010). The impact of genetic architecture on genome-wide evaluation methods. Genetics 185: 1021-1031. http://dx.doi.org/10.1534/genetics.110.116855 Daetwyler HD, Calus MPL, Pong-Wong R, de Los Campos G, et al (2013). Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking. Genetics 193: 347-365. http://dx.doi.org/10.1534/genetics.112.147983 Endelman JB, et al (2011). Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4: 250-255. http://dx.doi.org/10.3835/plantgenome2011.08.0024 Gmitter Junior FG, Chen C, Machado MA, Souza AA, et al (2012). Citrus genomics. Tree Genet. Genomes 8: 611-626. http://dx.doi.org/10.1007/s11295-012-0499-2 Goddard ME, Hayes BJ, Meuwissen THE, et al (2011). Using the genomic relationship matrix to predict the accuracy of genomic selection. J. Anim. Breed. Genet. 128: 409-421. http://dx.doi.org/10.1111/j.1439-0388.2011.00964.x Grattapaglia D, Resende MDV, et al (2011). Genomic selection in forest tree breeding. Tree Genet. Genomes 7: 241-255. http://dx.doi.org/10.1007/s11295-010-0328-4 Gussen O, Uzun A, Seday U, Kafa G, et al (2011). QTL analysis and regression model for estimating fruit setting in young Citrus trees based on molecular markers. Sci. Hortic. (Amsterdam) 130: 418-424. http://dx.doi.org/10.1016/j.scienta.2011.07.010 Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME, et al (2009). Invited review: Genomic selection in dairy cattle: progress and challenges. J. Dairy Sci. 92: 433-443. http://dx.doi.org/10.3168/jds.2008-1646 Heffner EL, Sorrells ME, Jannink JL, et al (2009). Genomic selection for crop improvement. Crop Sci. 49: 1-12. http://dx.doi.org/10.2135/cropsci2008.08.0512 Henderson CR (1973). Maximum likelihood estimation of variance components. Unpublished manuscripts, Animal Science Dept., Cornell University. Ito TM, Polido PB, Rampim MC, Kaschuk G, et al (2014). Genome-wide identification and phylogenetic analysis of the AP2/ERF gene superfamily in sweet orange (Citrus sinensis). Genet. Mol. Res. 13: 7839-7851. http://dx.doi.org/10.4238/2014.September.26.22 Iwata H, Hayashi T, Terakami S, Takada N, et al (2013). Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia. Breed. Sci. 63: 125-140. http://dx.doi.org/10.1270/jsbbs.63.125 Jaccoud D, Peng K, Feinstein D, Kilian A, et al (2001). Diversity arrays: a solid state technology for sequence information independent genotyping. Nucleic Acids Res. 29: E25. http://dx.doi.org/10.1093/nar/29.4.e25 Jarrell DC, Roose ML, Traugh SN, Kupper RS, et al (1992). A genetic map of citrus based on the segregation of isozymes and RFLPs in an intergeneric cross. Theor. Appl. Genet. 84: 49-56. http://dx.doi.org/10.1007/BF00223980 Kemper KE, Goddard ME, et al (2012). Understanding and predicting complex traits: knowledge from cattle. Hum. Mol. Genet. 21 (R1): R45-R51. http://dx.doi.org/10.1093/hmg/dds332 Kumar S, Bink MCAM, Volz RK, Bus VGM, et al (2012). Towards genomic selection in apple (Malus × domestica Borkh.) breeding programmes: Prospects, challenges and strategies. Tree Genet. Genomes 8: 1-14. http://dx.doi.org/10.1007/s11295-011-0425-z Lande R, Thompson R, et al (1990). Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124: 743-756. Legarra A, Robert-Granié C, Manfredi E, Elsen JM, et al (2008). Performance of genomic selection in mice. Genetics 180: 611-618. http://dx.doi.org/10.1534/genetics.108.088575 Machado MA, Cristofani-Yaly M, Bastianel M, et al (2011). Breeding, genetic and genomic of citrus for disease resistance. Rev. Bras. Frutic. 33: 158-172. http://dx.doi.org/10.1590/S0100-29452011000500019 Meuwissen THE, Hayes BJ, Goddard ME, et al (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819-1829. Misztal I, Legarra A, Aguilar I, et al (2009). Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci. 92: 4648-4655. http://dx.doi.org/10.3168/jds.2009-2064 Patterson HD, Thompson R, et al (1971). Recovery of inter-block information when block sizes are unequal. Biometrika 58: 545-554. http://dx.doi.org/10.1093/biomet/58.3.545 R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Resende MDV (2002). Genética Biométrica e estatística no melhoramento de plantas perenes. Brasília: Embrapa Informação tecnológica. Resende MDV, Duarte JB, et al (2007). Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesqui. Agropecu. Trop. 37: 182-194. Resende MDV, Lopes OS, Silva RL, Pires IE, et al (2008). Seleção genômica ampla (GWS) e maximização da eficiência do melhoramento genético. Pesq. Flor. Bra. 56: 63-77. Resende MDV, Resende MFRJrSansaloniCP, Petroli CD, et al (2012). Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. New Phytol. 194: 116-128. http://dx.doi.org/10.1111/j.1469-8137.2011.04038.x Resende MDV, Silva FF, Resende MFR, Junior. and Azevedo CF (2014). Genome-wide selection. In: Biotechnology and Plant Breeding (Borem A and Fritsche-Neto R, eds.). Elsevier. Resende MFJrMuñozP, Resende MDV, Garrick DJ, et al (2012). Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190: 1503-1510. http://dx.doi.org/10.1534/genetics.111.137026 Siviero A, Cristofani M, Boava LP, Machado MA, et al (2002). Mapeamento de QTLs associados à produção de frutos e sementes em híbridos de Citrus sunki vs Poncirus trifoliata. Rev. Bras. Frutic. 24: 741-743. http://dx.doi.org/10.1590/S0100-29452002000300045 Siviero A, Cristofani M, Furtado EL, Garcia AAF, et al (2006). Identification of QTLs associated with citrus resistance to Phytophthora gummosis. J. Appl. Genet. 47: 23-28. http://dx.doi.org/10.1007/BF03194595 Talon M and Gmitter Junior FG (2008). Citrus genomics. Intern. J. Plant Genomics: 1-17. Viana AP and Resende MDV (2014). Seleção Genômica Ampla (GWS). In: Genética Quantitativa no Melhoramento de Fruteiras (Viana AP, Resende MDV, eds.). Interciência, Rio de Janeiro. Viana AP, Resende MDV, Riaz S, Walker MA, et al (2016). Genome selection in fruit breeding: application to table grapes. Sci. Agric. 73: 142-149. http://dx.doi.org/10.1590/0103-9016-2014-0323 Wong CK, Bernardo R, et al (2008). Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theor. Appl. Genet. 116: 815-824. http://dx.doi.org/10.1007/s00122-008-0715-5 Zapata-Velenzuela J, Whetten RW, Neale D, Mckeand S, et al (2013). Genomic estimated breeding values using genomic relationship matrices in a cloned population of Loblolly Pine. Genes Genom. Genet 3: 909-916. Zhao Y, Gowda M, Liu W, Wurschum T, et al (2013). Choice of shrinkage parameter and prediction of genomic breeding values in elite maize breeding populations. Plant Breed. 132: 99-106. http://dx.doi.org/10.1111/pbr.12008 Zhong S, Dekkers JCM, Fernando RL, Jannink JL, et al (2009). Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study. Genetics 182: 355-364. http://dx.doi.org/10.1534/genetics.108.098277
I. B. Gois, Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., Machado, M. A., Gois, I. B., Borém, A., Cristofani-Yaly, M., de Resende, M. D. V., Azevedo, C. F., Bastianel, M., Novelli, V. M., and Machado, M. A., Genome wide selection in Citrus breeding, vol. 15, no. 4, p. -, 2016.
Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and Capes (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) for the research fellowship of the first author. Research supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Processes #2007/08435-5 and #2011/18605-0) and Instituto Nacional de Ciência e Tecnologia (INCT) de Genômica para Melhoramento de Citros (Process #573848/2008-4). REFERENCES Asins MJ, Fernandez-Ribacoba J, Bernet GP, Gadea J, et al (2012). The position of the major QTL for Citrus tristeza virus resistance is conserved among Citrus grandis, C. aurantium and Poncirus trifoliata. Mol. Breed. 29: 575-587. http://dx.doi.org/10.1007/s11032-011-9574-x Cavalcanti JJV, Resende MDV, Santos FHC, Pinheiro CR, et al (2012). Predição simultânea dos efeitos de marcadores moleculares e seleção genômica ampla em cajueiro. Rev. Bras. Frutic. 34: 840-846. http://dx.doi.org/10.1590/S0100-29452012000300025 Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA, et al (2010). The impact of genetic architecture on genome-wide evaluation methods. Genetics 185: 1021-1031. http://dx.doi.org/10.1534/genetics.110.116855 Daetwyler HD, Calus MPL, Pong-Wong R, de Los Campos G, et al (2013). Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking. Genetics 193: 347-365. http://dx.doi.org/10.1534/genetics.112.147983 Endelman JB, et al (2011). Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4: 250-255. http://dx.doi.org/10.3835/plantgenome2011.08.0024 Gmitter Junior FG, Chen C, Machado MA, Souza AA, et al (2012). Citrus genomics. Tree Genet. Genomes 8: 611-626. http://dx.doi.org/10.1007/s11295-012-0499-2 Goddard ME, Hayes BJ, Meuwissen THE, et al (2011). Using the genomic relationship matrix to predict the accuracy of genomic selection. J. Anim. Breed. Genet. 128: 409-421. http://dx.doi.org/10.1111/j.1439-0388.2011.00964.x Grattapaglia D, Resende MDV, et al (2011). Genomic selection in forest tree breeding. Tree Genet. Genomes 7: 241-255. http://dx.doi.org/10.1007/s11295-010-0328-4 Gussen O, Uzun A, Seday U, Kafa G, et al (2011). QTL analysis and regression model for estimating fruit setting in young Citrus trees based on molecular markers. Sci. Hortic. (Amsterdam) 130: 418-424. http://dx.doi.org/10.1016/j.scienta.2011.07.010 Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME, et al (2009). Invited review: Genomic selection in dairy cattle: progress and challenges. J. Dairy Sci. 92: 433-443. http://dx.doi.org/10.3168/jds.2008-1646 Heffner EL, Sorrells ME, Jannink JL, et al (2009). Genomic selection for crop improvement. Crop Sci. 49: 1-12. http://dx.doi.org/10.2135/cropsci2008.08.0512 Henderson CR (1973). Maximum likelihood estimation of variance components. Unpublished manuscripts, Animal Science Dept., Cornell University. Ito TM, Polido PB, Rampim MC, Kaschuk G, et al (2014). Genome-wide identification and phylogenetic analysis of the AP2/ERF gene superfamily in sweet orange (Citrus sinensis). Genet. Mol. Res. 13: 7839-7851. http://dx.doi.org/10.4238/2014.September.26.22 Iwata H, Hayashi T, Terakami S, Takada N, et al (2013). Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia. Breed. Sci. 63: 125-140. http://dx.doi.org/10.1270/jsbbs.63.125 Jaccoud D, Peng K, Feinstein D, Kilian A, et al (2001). Diversity arrays: a solid state technology for sequence information independent genotyping. Nucleic Acids Res. 29: E25. http://dx.doi.org/10.1093/nar/29.4.e25 Jarrell DC, Roose ML, Traugh SN, Kupper RS, et al (1992). A genetic map of citrus based on the segregation of isozymes and RFLPs in an intergeneric cross. Theor. Appl. 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V. S. Santos, S. Filho, M., Resende, M. D. V., Azevedo, C. F., Lopes, P. S., Guimarães, S. E. F., and Silva, F. F., Genomic prediction for additive and dominance effects of censored traits in pigs, vol. 15, no. 4, p. -, 2016.
Conflicts of interestThe authors declare no conflict of interest.ACKNOWLEDGMENTSThe first author would like to thank the CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) for a Sandwich Doctorate scholarship (grant #BEX 9415/14-9). Research supported by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais). REFERENCESAzevedo CF, de Resende MD, E Silva FF, Viana JMS, et al (2015). Ridge, Lasso and Bayesian additive-dominance genomic models. BMC Genet. 16: 105. http://dx.doi.org/10.1186/s12863-015-0264-2 Band GO, Guimarães SEF, Lopes PS, Peixoto JDO, et al (2005). Relationship between the Porcine Stress Syndrome gene and carcass and performance traits in F2 pigs resulting from divergent crosses. Genet. Mol. Biol. 28: 92-96. http://dx.doi.org/10.1590/S1415-47572005000100016 Costa EV, Diniz DB, Veroneze R, Resende MD, et al (2015). 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Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), Inferência Bayesiana, Regressão Aleatória, Seleção Genômica, QTL-GWAS, Estatística Espacial e Temporal, Competição, Sobrevivência. Editora Suprema, Viçosa. Santos VS, Martins Filho S, Resende MDV, Azevedo CF, et al (2015). Genomic selection for slaughter age in pigs using the Cox frailty model. Genet. Mol. Res. 14: 12616-12627. http://dx.doi.org/10.4238/2015.October.19.5 Schaeffer L (2013). Survival. In: History of genetic evaluation methods in dairy cattle (Grosu H, Schaeffer L, Oltenacu PA, et al., eds.) 279-298. Available at [https://xa.yimg.com/kq/groups/18395782/1926111600/name/FINAL_BOOK_29.04.2013.pdf]. Accessed 12 April, 2016 Schneider MdelP, Strandberg E, Ducrocq V, Roth A, et al (2005). Survival analysis applied to genetic evaluation for female fertility in dairy cattle. J. 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C. F. Azevedo, Resende, M. D. V., Silva, F. F., Viana, J. M. S., Valente, M. S. F., Resende, Jr, M. F. R., Oliveira, E. J., Azevedo, C. F., Resende, M. D. V., Silva, F. F., Viana, J. M. S., Valente, M. S. F., Resende, Jr, M. F. R., and Oliveira, E. J., New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program, vol. 15, p. -, 2016.
C. F. Azevedo, Resende, M. D. V., Silva, F. F., Viana, J. M. S., Valente, M. S. F., Resende, Jr, M. F. R., Oliveira, E. J., Azevedo, C. F., Resende, M. D. V., Silva, F. F., Viana, J. M. S., Valente, M. S. F., Resende, Jr, M. F. R., and Oliveira, E. J., New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program, vol. 15, p. -, 2016.
L. M. A. Barroso, Teodoro, P. E., Nascimento, M., Torres, F. E., Nascimento, A. C. C., Azevedo, C. F., Teixeira, F. R. F., Barroso, L. M. A., Teodoro, P. E., Nascimento, M., Torres, F. E., Nascimento, A. C. C., Azevedo, C. F., and Teixeira, F. R. F., Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability, vol. 15, no. 4, p. -, 2016.
Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS We thank Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support. REFERENCES Almeida WS, Fernandes FRB, Teófilo EM, Bertini CHCM, et al (2012). Adaptability and stability of grain yield in cowpea under different biometrics. Rev. Bras. Agr. 18: 221-228. Banzatto DA and Kronka SN (2006). Experimentação agrícola. FUNEP, Jaboticabal. Barros MA, Rocha MM, Gomes RLF, Silva KJD, et al (2013). Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesq. Agropec. Bras. 48: 403-410. http://dx.doi.org/10.1590/S0100-204X2013000400008 Barroso LMA, Teodoro PE, Nascimento M, Torres FE, et al. (2016). Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genet. Mol. Res. 15: gmr.15017625. Cochran WG, et al (1954). Some methods for strengthening the common χ2 tests. Biometrics 10: 417-451. http://dx.doi.org/10.2307/3001616 Correa AM, Teodoro PE, Gonçalves MC, Barroso LM, et al. (2016). Artificial intelligence in the selection of common bean genotypes with high phenotypic stability. Genet. Mol. Res. 15: gmr.15028230. Cruz CD, et al (2013). GENES- a software package for analysis in experimental statistics and quantitative genetics. Acta Sci. Agron. 35: 271-276. http://dx.doi.org/10.4025/actasciagron.v35i3.21251 Cruz CD, Regazzi AJ and Carneiro PCS (2012). Modelos biométricos aplicados ao melhoramento genético. Imprensa Universitária, Viçosa. Eberhart SA, Russell WA, et al (1966). Stability parameters for comparing varieties. Crop Sci. 6: 36-40. http://dx.doi.org/10.2135/cropsci1966.0011183X000600010011x Finlay KW, Wilkinson GN, et al (1963). The analysis of adaptation in a plant-breeding programme. Crop Pasture Sci. 14: 742-754. http://dx.doi.org/10.1071/AR9630742 Haykin S (2009). Neural networks and learning machines. Prentice Hall, New Jersey. Nascimento M, Peternelli LA, Cruz CD, Nascimento ACC, et al (2013). Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes. Crop Breed. Appl. Biotechnol. 13: 152-156. http://dx.doi.org/10.1590/S1984-70332013000200008 Nunes HF, Filho FRF, Ribeiro VQ, Gomes RLF, et al (2014). Grain yield adaptability and stability of blackeyed cowpea genotypes under rainfed agriculture in Brazil. Afr. J. Agr. 9: 255-261. http://dx.doi.org/10.5897/AJAR212.2204 Oliveira OMS, Silva JF, Ferreira FM, Klehm CS, et al (2013). Associações genotípicas entre componentes de produção e caracteres agronômicos em feijão-caupi. Rev. Cienc. Agron. 44: 851-857. http://dx.doi.org/10.1590/S1806-66902013000400023 R Development Core Team (2011). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available at [https://www.r-project.org/.] Rocha MM, Freire Filho FR, Ribeiro VQ, Carvalho HWL, et al (2007). Adaptabilidade e estabilidade produtiva de genótipos de feijão-caupi de porte semiereto na região Nordeste do Brasil. Pesq. Agropec. Bras. 42: 1283-1289. http://dx.doi.org/10.1590/S0100-204X2007000900010 Santos A, Ceccon G, Rodrigues EV, Teodoro PE, et al (2015). Adaptability and stability of cowpea genotypes to Brazilian Midwest. Afr. J. Agric. Res. 10: 3901-3908. http://dx.doi.org/10.5897/AJAR2015.10165 Santos JAS, Teodoro PE, Correa AM, Soares CMG, et al (2014a). Desempenho agronômico e divergência genética entre genótipos de feijão-caupi cultivados no ecótono Cerrado/Pantanal. Bragantia 73: 377-382. http://dx.doi.org/10.1590/1678-4499.0250 Santos JAS, Soares CMG, Corrêa AM, Teodoro PE, et al (2014b). Agronomic performance and genetic dissimilarity among cowpea [Vigna unguiculata (L.) Walp.] genotypes. Glob. Adv. Res. J. Agr. Sci. 3: 271-277. Teodoro PE, Barroso LMA, Nascimento M, Torres FE, et al (2015a). Redes neurais artificiais para identificar genótipos de feijão-caupi semiprostrado com alta adaptabilidade e estabilidade fenotípicas. Pesq. Agropec. Bras. 50: 1054-1060. http://dx.doi.org/10.1590/S0100-204X2015001100008 Teodoro PE, Nascimento M, Torres FE, Barroso LMA, et al (2015b). Perspectiva baysiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesq. Agropec. Bras. 50: 878-885. http://dx.doi.org/10.1590/S0100-204X2015001000003 Torres FE, Sagrilo E, Teodoro PE, Ribeiro LP, et al (2015a). Número de repetições para avaliação de caracteres em genótipos de feijão-caupi. Bragantia 74: 161-168. http://dx.doi.org/10.1590/1678-4499.0393 Torres FE, Teodoro PE, Sagrilo E, Correa AM, et al (2015b). Interação genótipo x ambiente em genótipos de feijão-caupi semiprostrado via modelos mistos. Bragantia 74: 255-260. http://dx.doi.org/10.1590/1678-4499.0099 Torres FE, Teodoro PE, Rodrigues EV, Santos A, et al. (2016). Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genet. Mol. Res. 15: gmr.15028272.
L. M. A. Barroso, Teodoro, P. E., Nascimento, M., Torres, F. E., Nascimento, A. C. C., Azevedo, C. F., Teixeira, F. R. F., Barroso, L. M. A., Teodoro, P. E., Nascimento, M., Torres, F. E., Nascimento, A. C. C., Azevedo, C. F., and Teixeira, F. R. F., Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability, vol. 15, no. 4, p. -, 2016.
Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS We thank Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support. REFERENCES Almeida WS, Fernandes FRB, Teófilo EM, Bertini CHCM, et al (2012). Adaptability and stability of grain yield in cowpea under different biometrics. Rev. Bras. Agr. 18: 221-228. Banzatto DA and Kronka SN (2006). Experimentação agrícola. FUNEP, Jaboticabal. Barros MA, Rocha MM, Gomes RLF, Silva KJD, et al (2013). Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesq. Agropec. Bras. 48: 403-410. http://dx.doi.org/10.1590/S0100-204X2013000400008 Barroso LMA, Teodoro PE, Nascimento M, Torres FE, et al. (2016). Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genet. Mol. Res. 15: gmr.15017625. Cochran WG, et al (1954). 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