Publications
Found 20 results
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“Genomic breeding value prediction for simple maize hybrid yield using total effects of associated markers, under different imbalance levels and environments”, vol. 15, p. -, 2016.
, “Genomic breeding value prediction for simple maize hybrid yield using total effects of associated markers, under different imbalance levels and environments”, vol. 15, p. -, 2016.
, “Heat-resistant protein expression during germination of maize seeds under water stress”, vol. 15, p. -, 2016.
, “Heat-resistant protein expression during germination of maize seeds under water stress”, vol. 15, p. -, 2016.
, “Genes related to high temperature tolerance during maize seed germination”, vol. 14, pp. 18047-18058, 2015.
, “Genome-wide prediction of maize single-cross performance, considering non-additive genetic effects”, vol. 14, pp. 18471-18484, 2015.
, “Indirect selection for resistance to ear rot and leaf diseases in maize lines using biplots”, vol. 14, pp. 11052-11062, 2015.
, “Verification and characterization of chromosome duplication in haploid maize”, vol. 14, pp. 6999-7007, 2015.
, “Physiological quality and gene expression related to heat-resistant proteins at different stages of development of maize seeds”, vol. 12, pp. 3630-3642, 2013.
, “Production and identification of doubled haploids in tropical maize”, vol. 12, pp. 4230-4242, 2013.
, “Bayesian inference to study genetic control of resistance to gray leaf spot in maize”, vol. 11, pp. 17-29, 2012.
, Brito AH, Von Pinho RG, Souza Filho AX and Altoé TF (2008). Avaliação da severidade da Cercosporiose e rendimento de grãos em híbridos comerciais de milho. Rev. Bras. Milho Sorgo 7: 19-31.
Brooks SP and Gelman A (1998). General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7: 434-455.
http://dx.doi.org/10.2307/1390675
Bubeck DM, Goodman MM, Beavis WD and Grant D (1993). Quantitative trait loci controlling resistance to gray leaf spot in maize. Crop Sci. 33: 838-847.
http://dx.doi.org/10.2135/cropsci1993.0011183X003300040041x
Clements MJ, Dudley JW and White DG (2000). Quantitative trait loci associated with resistance to gray leaf spot of corn. Phytopathology 90: 1018-1025.
http://dx.doi.org/10.1094/PHYTO.2000.90.9.1018
PMid:18944528
Coates ST and White DG (1998). Inheritance of resistance to gray leaf spot in crosses involving selected resistant inbred lines of corn. Phytopathology 88: 972-982.
http://dx.doi.org/10.1094/PHYTO.1998.88.9.972
PMid:18944876
Derera J, Tongoona P, Kevin VP, Vivek B, et al. (2008). Gene action controlling gray leaf spot resistance in Southern African maize germplasm. Crop Sci. 48: 93-98.
http://dx.doi.org/10.2135/cropsci2007.04.0185
Gelman A and Rubin DB (1992). Inference from iterative simulation using multiple sequences. Stat. Sci. 7: 457-472.
http://dx.doi.org/10.1214/ss/1177011136
Gordon GS, Bartsch M, Matties I, Gevers HO, et al. (2004). Linkage of molecular markers to Cercospora zeae-maydis resistance in maize. Crop Sci. 44: 628-636.
http://dx.doi.org/10.2135/cropsci2004.0628
Janss LL, Van Arendonk JA and Brascamp EW (1997). Bayesian statistical analyses for presence of single genes affecting meat quality traits in a crossed pig population. Genetics 145: 395-408.
PMid:9071593 PMCid:1207804
Juliatti FC, Appelt CCNS, Brito CH, Gomes LS, et al. (2004). Controle da feosféria, ferrugem comum e cercosporiose pelo uso da resistência genética, fungicidas e épocas de aplicação na cultura do milho. Biosci. J. 20: 45-54.
Juliatti FC, Pedrosa MG, Silva HD and Silva JVC (2009). Genetic mapping for resistance to gray leaf spot in maize. Euphytica 169: 227-238.
http://dx.doi.org/10.1007/s10681-009-9943-2
Kadarmideen HN and Janss LL (2005). Evidence of a major gene from Bayesian segregation analyses of liability to osteochondral diseases in pigs. Genetics 171: 1195-1206.
http://dx.doi.org/10.1534/genetics.105.040956
PMid:16020792 PMCid:1456822
Mather K and Jinks JL (1971). Biometrical Genetics. Chapman and Hall, London.
Menkir A and Ayodele M (2005). Genetic analysis of resistance to gray leaf spot of midaltitude maize inbred lines. Crop Sci. 45: 163-170.
Pozar G, Butruille D, Silva HD, McCuddin ZP, et al. (2009). Mapping and validation of quantitative trait loci for resistance to Cercospora zeae-maydis infection in tropical maize (Zea mays L.). Theor. Appl. Genet. 118: 553-564.
http://dx.doi.org/10.1007/s00122-008-0920-2
PMid:18989654
Raftery AE and Lewis SM (1992). How Many Iterations in the Gibbs Sampler? In: Bayesian Statistics 4 (Bernardo JM, Berger JO, Dawid AP and Smith AFM, eds.). Oxford University Press, Oxford, 763-773.
Saghai-Maroof MA, Yue YG, Xiang ZX, Stromberg EL, et al. (1996). Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize. Theor. Appl. Genet. 93: 539-546.
http://dx.doi.org/10.1007/BF00417945
SAS Institute (2000). Version 8. SAS Institute Inc., Cary.
Silva MIS, Bearzoti E and Bueno-Filho JSS (2009). Análise bayesiana do modelo de herança monogênica no melhoramento vegetal: um exemplo com abobrinha. Cienc. Agrotecnol. 33: 1463-1468.
http://dx.doi.org/10.1590/S1413-70542009000600002
Von Pinho RG, Ramalho MAP, Resende IC, Silva HP, et al. (2001). Reação de híbridos comerciais de milho às ferrugens polissora e tropical. Pesq. Agropec. Bras. 36: 439-445.
http://dx.doi.org/10.1590/S0100-204X2001000300007
Xu S (2003). Estimating polygenic effects using markers of the entire genome. Genetics 163: 789-801.
PMid:12618414 PMCid:1462468
“Detection limits of the strip test and PCR for genetically modified corn in Brazil”, vol. 11, pp. 2497-2505, 2012.
,
Ahmed FE (2002). Detection of genetically modified organisms in foods. Trends Biotechnol. 20: 215-223.
http://dx.doi.org/10.1016/S0167-7799(01)01920-5
Huang HY and Pan TM (2004). Detection of genetically modified maize MON810 and NK603 by multiplex and real-time polymerase chain reaction methods. J. Agric. Food Chem. 52: 3264-3268.
http://dx.doi.org/10.1021/jf049944o
PMid:15161180
International Seed Testing Association (2009). Position Paper on ISTA's View Regarding the Units for the Reporting of Quantitative Results on Presence of Seeds with Specified Traits in Conventional Seed Lots. ISTA GMO Task Force, Document 08-2009, Glattbrugg, 4.
James C (2009). Global Status of Commercialized Biotech/GM Crops. ISAAA Brief No. 41, Ithaca.
Ramos NP, Brunelli KR, Camargo LEA and Filho JM (2006). Sensibilidade dos microssatelites para determinar a pureza varietal em sementes de milho. Rev. Bras. Sementes 28: 99-105.
http://dx.doi.org/10.1590/S0101-31222006000100014
“Prediction of maize double-cross hybrids using the best linear unbiased prediction with microsatellite marker information”, vol. 10, pp. 25-35, 2011.
,
Balestre M, Von Pinho RG, Souza JC and Machado JC (2008). Potential of maize single-cross hybrids for extraction of inbred lines using the mean components and mixed models with microsatellite marker information. Genet. Mol. Res. 7: 1106-1118.
http://dx.doi.org/10.4238/vol7-4gmr491
PMid:19048489
Balestre M, Von Pinho RG, Souza JC and Oliveira RL (2009). Potential use of molecular markers for prediction of genotypic values in hybrid maize performance. Genet. Mol. Res. 8: 1292-1306.
http://dx.doi.org/10.4238/vol8-4gmr644
PMid:19876871
Balestre M, Von Pinho RG and Souza JC (2010). Prediction of maize single-cross performance by mixed linear models with microsatellite marker information. Genet. Mol. Res. 9: 1054-1068.
http://dx.doi.org/10.4238/vol9-2gmr791
PMid:20568050
Bauer AM, Reetz TC and Leon J (2006). Estimation of breeding values of inbred lines using best linear unbiased prediction (BLUP) and genetic similarities. Crop Sci. 46: 2685-2691.
http://dx.doi.org/10.2135/cropsci2006.01.0019
Bernardo R (1994). Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci. 34: 20-25.
http://dx.doi.org/10.2135/cropsci1994.0011183X003400010003x
Bernardo R (1995). Genetic models for predicting maize single-cross performance in unbalanced yield trial data. Crop Sci. 35: 141-147.
http://dx.doi.org/10.2135/cropsci1995.0011183X003500010026x
Bernardo R (1996). Best linear unbiased prediction of maize single-cross performance. Crop Sci. 36: 50-56.
http://dx.doi.org/10.2135/cropsci1996.0011183X003600010009x
Bickel DR (2002). Robust estimators of the mode and skewness of continuous data. Comput. Stat. Data Anal. 39: 153-163.
http://dx.doi.org/10.1016/S0167-9473(01)00057-3
Bickel DR (2003). Robust and efficient estimation of the mode of continuous data: the mode as a viable measure of central tendency. J. Stat. Comput. Simulat. 73: 899-912.
http://dx.doi.org/10.1080/0094965031000097809
Cruz JC and Pereira Filho IA (2008). Cultivares de Milho Disponíveis no Mercado de Sementes do Brasil para a Safra 2008/2009. Available at [http://www.cnpms.embrapa.br/publicacoes/milho/cultivares.htm]. Accessed November 1, 2009.
Dalenius T (1965). The mode - a neglected statistical parameter. J. R. Stat. Soc. Ser. A 128: 110-117.
http://dx.doi.org/10.2307/2343439
Griffing B (1956). Concept of general and specific combining ability in relation to diallel crossing systems. Aust. J. Biol. Sci. 9: 463-493.
Hamblin J and Zimmermann MJ (1986). Breeding common bean for yield in mixtures. Plant Breed. Rev. 4: 245-272.
Henderson CR (1984). Applications of Liner Models in Animal Breeding. University of Guelph Press, Guelph.
Jenkins MT (1934). Methods of estimating the performance of double crosses in corn. J. Am. Soc. Agron. 26: 199-204.
http://dx.doi.org/10.2134/agronj1934.00021962002600030004x
Lynch M and Ritland K (1999). Estimation of pairwise relatedness with molecular markers. Genetics 152: 1753-1766.
PMid:10430599 PMCid:1460714
SAS Institute (2000). User's Guide. Version 8. SAS Institute Inc, Cary.
Schrag TA, Melchinger AE, Sorensen AP and Frisch M (2006). Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Theor. Appl. Genet. 113: 1037-1047.
http://dx.doi.org/10.1007/s00122-006-0363-6
PMid:16896712
Schrag TA, Mohring J, Maurer HP, Dhillon BS, et al. (2009). Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses. Theor. Appl. Genet. 118: 741-751.
http://dx.doi.org/10.1007/s00122-008-0934-9
PMid:19048224
Troyer AF (2009). Development of Hybrid Corn and the Seed Corn Industry. In: Handbook of Maize: Genetics and Genomics (Bennetzen JL and Hake S, eds.). Springer, New York, 87-114.
Van Vleck LD (1993). Selection Index in Introduction to Mixed Models Methods for Genetic Improvement of Animals. The Green Book Press, Boca Raton.
Vuylsteke M, Kuiper M and Stam P (2000). Chromosomal regions involved in hybrid performance and heterosis: their AFLP(R)-based identification and practical use in prediction models. Heredity 85 (Pt 3): 208-218.
http://dx.doi.org/10.1046/j.1365-2540.2000.00747.x
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Wright DR, Stern HS and Berger J (2000). Comparing traditional and Bayesian analyses of selection experiments in animal breeding. J. Agric. Biol. Environ. Stat. 5: 240-256.
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“Prediction of maize hybrid performance using similarity in state and similarity by descent information”, vol. 9, pp. 2381-2394, 2010.
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Amorim EP, Amorim UBO and Santos JB (2006). Genetic distance based on SSR and grain yield of inter- and intrapopulational maize single cross hybrids. Maydica 51: 507-513.
André CMG (1999). Avaliação da Melhor Predição Linear não Tendenciosa (BLUP) Associada ao Uso de Marcadores Moleculares na Análise Dialélica. Master thesis, Universidade Federal de Lavras, Lavras.
Balestre M, Von Pinho RG, Souza JC and Lima JL (2008a). Comparison of maize similarity and dissimilarity genetic coefficients based on microsatellite markers. Genet. Mol. Res. 7: 695-705.
http://dx.doi.org/10.4238/vol7-3gmr458
PMid:18752197
Balestre M, Von Pinho RG, Souza JC and Machado JC (2008b). Potential of maize single-cross hybrids for extraction of inbred lines using the mean components and mixed models with microsatellite marker information. Genet. Mol. Res. 7: 1106-1118.
http://dx.doi.org/10.4238/vol7-4gmr491
PMid:19048489
Balestre M, Von Pinho RG, Souza JC and Oliveira RL (2009). Potential use of molecular markers for prediction of genotypic values in hybrid maize performance. Genet. Mol. Res. 8: 1292-1306.
http://dx.doi.org/10.4238/vol8-4gmr644
PMid:19876871
Balestre M, Von Pinho RG and Souza JC (2010). Prediction of maize single-cross performance by mixed linear models with microsatellite marker information. Genet. Mol. Res. 9: 1054-1068.
http://dx.doi.org/10.4238/vol9-2gmr791
PMid:20568050
Bernardo R (1993). Estimation of coefficient of coancestry using molecular markers in maize. Theor. Appl. Genet. 85: 1055-1062.
http://dx.doi.org/10.1007/BF00215047
Bernardo R (1994). Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci. 34: 20-25.
http://dx.doi.org/10.2135/cropsci1994.0011183X003400010003x
Bernardo R (1995). Genetic models for predicting maize performance in unbalanced yield trial data. Crop Sci. 35: 141-147.
http://dx.doi.org/10.2135/cropsci1995.0011183X003500010026x
Bernardo R (1996a). Best linear unbiased prediction of maize single-cross performance given erroneous inbred relationships. Crop Sci. 36: 862-866.
http://dx.doi.org/10.2135/cropsci1996.0011183X003600040007x
Bernardo R (1996b). Best linear unbiased prediction of maize single cross performance given erroneous inbred relationships. Crop Sci. 36: 50-56.
http://dx.doi.org/10.2135/cropsci1996.0011183X003600010009x
Bickel DR (2002). Robust estimators of the mode and skewness of continuous data. Comput. Stat. Data Anal. 39: 153-163.
http://dx.doi.org/10.1016/S0167-9473(01)00057-3
Bickel DR (2003). Robust and efficient estimation of the mode of continuous data: the mode as a viable measure of central tendency. J. Stat. Comput. Simulation 73: 899-912.
http://dx.doi.org/10.1080/0094965031000097809
Charcosset A, Bonnisseau B, Touchebeuf O, Burstin J, et al. (1998). Prediction of maize hybrid silage performance using marker data: comparison of several models for specific combining ability. Crop Sci. 38: 38-44.
http://dx.doi.org/10.2135/cropsci1998.0011183X003800010007x
Dalenius T (1965). The mode - a neglected statistical parameter. J. Royal Stat. Society 128: 110-117.
http://dx.doi.org/10.2307/2343439
Dias LA, Picoli EA, Rocha RB and Alfenas AC (2004). A priori choice of hybrid parents in plants. Genet. Mol. Res. 3: 356-368.
PMid:15614727
Griffing BA (1956). Concept of general and specific combining ability in relation to diallel crossing systems. Aust. J. Biol. Sci. 9: 463-493.
Hamblin J and Zimmermann MJ (1986). Breeding common bean for yield in mixtures. Plant Breed. Rev. 4: 245-272.
Henderson CR (1984). Applications of Liner Models in Animal Breeding. University of Guelph, Guelph.
Lynch M and Ritland K (1999). Estimation of pairwise relatedness with molecular markers. Genetics 152: 1753-1766.
PMid:10430599 PMCid:1460714
Melchinger AE (1999). Genetic Diversity and Heterosis. In: The Genetics and Exploitation of Heterosis in Crops (Coors JG and Pandey S, eds.). American Society of Agronomy, Madison.
Nejati-Javaremi A, Smith C and Gibson JP (1997). Effect of total allelic relationship on accuracy of evaluation and response to selection. J. Anim. Sci. 75: 1738-1745.
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Reif JC, Melchinger AE, Xia XC, Warburton ML, et al. (2003a). Use of SSRs for establishing heterotic groups in subtropical maize. Theor. Appl. Genet. 107: 947-957.
http://dx.doi.org/10.1007/s00122-003-1333-x
PMid:12830388
Reif JC, Melchinger AE, Xia XC, Warburton ML, et al. (2003b). Genetic distance based on simple sequence repeats and heterosis in tropical maize populations. Crop Sci. 43: 1275-1282.
http://dx.doi.org/10.2135/cropsci2003.1275
Reif JC, Melchinger AE and Frisch M (2005). Genetical and mathematical properties of similarity and dissimilarity coefficients applied in plant breeding and seed bank management. Crop Sci. 45: 1-7.
http://dx.doi.org/10.2135/cropsci2005.0001
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Schrag TA, Möhring J, Maurer HP, Dhillon BS, et al. (2009). Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses. Theor. Appl. Genet. 118: 741-751.
http://dx.doi.org/10.1007/s00122-008-0934-9
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“Prediction of maize single-cross performance by mixed linear models with microsatellite marker information”, vol. 9, pp. 1054-1068, 2010.
, Amorim EP, Amorim UBO, Dos Santos JB, Pereira De Souza A, et al. (2006). Genetic distance based on SSR and grain yield of inter and intrapopulational maize single cross hybrids. Maydica 51: 507-513.
André CMG (1999). Avaliação da Melhor Predição Linear não Tendenciosa (BLUP) Associada ao Uso de Marcadores Moleculares na Análise Dialélica. Master's thesis, Universidade Federal de Lavras, Lavras.
Balestre M, Machado JC, Lima JL, Souza JC, et al. (2008a). Genetic distance estimates among single cross hybrids and correlation with specific combining ability and yield in corn double cross hybrids. Genet. Mol. Res. 7: 65-73.
http://dx.doi.org/10.4238/vol7-1gmr403
PMid:18273821
Balestre M, Von Pinho RG, Souza JC and Lima JL (2008b). Comparison of maize similarity and dissimilarity genetic coefficients based on microsatellite markers. Genet. Mol. Res. 7: 695-705.
http://dx.doi.org/10.4238/vol7-3gmr458
PMid:18752197
Balestre M, Von Pinho RG, Souza JC and Machado JC (2008c). Potential of maize single-cross hybrids for extraction of inbred lines using the mean components and mixed models with microsatellite marker information. Genet. Mol. Res. 7: 1106-1118.
http://dx.doi.org/10.4238/vol7-4gmr491
PMid:19048489
Bernando R (1994). Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci. 34: 20-25.
http://dx.doi.org/10.2135/cropsci1994.0011183X003400010003x
Bernardo R (1995). Genetic models for predicting maize performance in unbalanced yield trial data. Crop Sci. 35: 141-147.
http://dx.doi.org/10.2135/cropsci1995.0011183X003500010026x
Bernardo R (1996). Best linear unbiased prediction of maize single cross performance. Crop Sci. 36: 50-56.
http://dx.doi.org/10.2135/cropsci1996.0011183X003600010009x
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Dias LA, Picoli EA, Rocha RB and Alfenas AC (2004). A priori choice of hybrid parents in plants. Genet. Mol. Res. 3: 356-368.
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Iemma M (2003). Uso do Melhor Predictor Linear Não Viesado (BLUP) em Análise Diallélica e Predição de Híbridos. Master's thesis, Escola Superior de Agricultura Luiz de Queiroz, Piracicaba.
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Nejati-Javaremi A, Smith C and Gibson JP (1997). Effect of total allelic relationship on accuracy of evaluation and response to selection. J. Anim. Sci. 75: 1738-1745.
PMid:9222829
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Reif JC, Melchinger AE, Xia XC, Warburton ML, et al. (2003). Genetic distance based on simple sequence repeats and heterosis in tropical maize populations. Crop Sci. 43: 1275-1282.
http://dx.doi.org/10.2135/cropsci2003.1275
Reif JC, Melchinger AE and Frisch M (2005). Genetical and mathematical properties of similarity and dissimilarity coefficients applied in plant breeding and seed bank management. Crop Sci. 45: 1-7.
http://dx.doi.org/10.2135/cropsci2005.0001
Ritland K (1996). Estimators for pairwise relatedness and inbreeding coefficients. Genet. Res. 67: 175-186.
http://dx.doi.org/10.1017/S0016672300033620
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SAS Institute (2000). Version 8. SAS Institute Inc., Cary.
Schrag TA, Mohring J, Maurer HP, Dhillon BS, et al. (2009). Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses. Theor. Appl. Genet. 118: 741-751.
http://dx.doi.org/10.1007/s00122-008-0934-9
PMid:19048224
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“Genotypic stability and adaptability in tropical maize based on AMMI and GGE biplot analysis”, vol. 8, pp. 1311-1322, 2009.
, “Potential use of molecular markers for prediction of genotypic values in hybrid maize performance”, vol. 8, pp. 1292-1306, 2009.
, “Comparison of maize similarity and dissimilarity genetic coefficients based on microsatellite markers”, vol. 7, pp. 695-705, 2008.
, “Mapping of quantitative trait locus associated with maize tolerance to high seed drying temperature”, vol. 7, pp. 1319-1326, 2008.
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