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Now showing items 31-40 of 213

Presentation

Importancia da biometria no melhoramento

Toledo, F.H.; Juliana, P.; Crespo-Herrera, L.A.; Crossa, J.; Burgueño, J. (CIMMYT, 2019)

Article

Multivariate bayesian analysis of on-farm trials with multiple-trait and multiple-environment data

Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Vargas-Hernández, M.; Ortíz-Monasterios, I.; Perez-Rodriguez, P.; Burgueño, J.; Crossa, J. (American Society of Agronomy, 2019)

Article

Empirical comparison of tropical maize hybrids selected through genomic and phenotypic selections

Beyene, Y.; Gowda, M.; Olsen, M.; Robbins, K.; Perez-Rodriguez, P.; Alvarado Beltrán, G.; Dreher, K.A.; Yanxin Gao; Mugo, S.N.; Prasanna, B.M.; Crossa, J. (Frontiers, 2019)

Article

Factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics

Mengesha, W.; Menkir, A.; Meseka, S.; Bossey, B.; Afolabi, A.; Burgueño, J.; Crossa, J. (Springer, 2019)

Vitamin A Deficiency (VAD) is a major public health problem in Sub-Saharan Africa affecting 33 million preschool-age children. Enrichment of maize varieties with provitamin A could provide sustainable and affordable solution ...

Article

Efficiency of a constrained linear genomic selection index to predict the net genetic merit in plants

Ceron Rojas, J.J.; Crossa, J. (Genetics Society of America, 2019)

The constrained linear genomic selection index (CLGSI) is a linear combination of genomic estimated breeding values useful for predicting the net genetic merit, which in turn is a linear combination of true unobservable ...

Article

Multi-trait, multi-environment genomic prediction of durum wheat with genomic best linear unbiased predictor and deep learning methods

Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Tuberosa, R.; Maccaferri, M.; Sciara, G.; Ammar, K.; Crossa, J. (Frontiers, 2019)

Although durum wheat (Triticum turgidum var. durum Desf.) is a minor cereal crop representing just 5-7% of the world's total wheat crop, it is a staple food in Mediterranean countries, where it is used to produce pasta, ...

Other

Correction to: factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics (Euphytica, (2019), 215, 11, (180), 10.1007/s10681-019-2505-3)

Mengesha, W.; Menkir, A.; Meseka, S.; Bossey, B.; Afolabi, A.; Burgueño, J.; Crossa, J. (Springer, 2019)

Article

Combined multistage linear genomic selection indices to predict the net genetic merit in plant breeding

Ceron Rojas, J.J.; Crossa, J. (Genetics Society of America, 2020)

Article

Genomic prediction of kernel zinc concentration in multiple maize populations using genotyping-by-sequencing and repeat amplification sequencing markers

Rui Guo; Dhliwayo, T.; Mageto, E.K.; Palacios-Rojas, N.; Lee, M.; Diansi Yu; Yanye Ruan; Ao Zhang; San Vicente, F.M.; Olsen, M.; Crossa, J.; Prasanna, B.M.; Lijun Zhang; Zhang, X. (Frontiers, 2020)

Presentation

Large scale deployment of rAmpSeq genotyping technology in maize genomic selection

Olsen, M.; Robbins, K.; Dreher, K.A.; Ayala, C.; Crossa, J.; Burgueño, J.; Perez-Rodriguez, P.; Alvarado Beltrán, G.; Gowda, M.; Beyene, Y.; Makumbi, D.; Zhang, X.; San Vicente, F.M.; Punna, R.; Buckler, E.; Atanda, A.S.; Gao, S.; Jones, L. (CIMMYT, 2018)

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CIMMYT Publications Repository

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Search

Importancia da biometria no melhoramento

Multivariate bayesian analysis of on-farm trials with multiple-trait and multiple-environment data

Empirical comparison of tropical maize hybrids selected through genomic and phenotypic selections

Factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics

Efficiency of a constrained linear genomic selection index to predict the net genetic merit in plants

Multi-trait, multi-environment genomic prediction of durum wheat with genomic best linear unbiased predictor and deep learning methods

Correction to: factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics (Euphytica, (2019), 215, 11, (180), 10.1007/s10681-019-2505-3)

Combined multistage linear genomic selection indices to predict the net genetic merit in plant breeding

Genomic prediction of kernel zinc concentration in multiple maize populations using genotyping-by-sequencing and repeat amplification sequencing markers

Large scale deployment of rAmpSeq genotyping technology in maize genomic selection

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Importancia da biometria no melhoramento

Multivariate bayesian analysis of on-farm trials with multiple-trait and multiple-environment data

Empirical comparison of tropical maize hybrids selected through genomic and phenotypic selections

Factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics

Efficiency of a constrained linear genomic selection index to predict the net genetic merit in plants

Multi-trait, multi-environment genomic prediction of durum wheat with genomic best linear unbiased predictor and deep learning methods

Correction to: factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics (Euphytica, (2019), 215, 11, (180), 10.1007/s10681-019-2505-3)

Combined multistage linear genomic selection indices to predict the net genetic merit in plant breeding

Genomic prediction of kernel zinc concentration in multiple maize populations using genotyping-by-sequencing and repeat amplification sequencing markers

Large scale deployment of rAmpSeq genotyping technology in maize genomic selection