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Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures

Beyene, Y.; Gakunga, J.; Sehabiague, P.; Meisel, B.; Oikeh, S.O.; Crossa, J.; Mugo, S.N.; Semagn, K.; Amsal Tesfaye Tarekegne; Prasanna, B.M.; Olsen, M. (Springer, 2016)

A marker-assisted recurrent selection (MARS) program was undertaken in sub-Saharan Africa to improve grain yield under drought-stress in 10 biparental tropical maize populations. The objectives of the present study were ...

Article

Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield

Aguate, F.M.; Trachsel, S.; Gonzalez-Perez, L.; Burgueño, J.; Crossa, J.; Balzarini, M.; Gouache, D.; Bogard, M.; De los Campos, G. (Crop Science Society of America (CSSA), 2017)

Hyperspectral cameras can provide reflectance data at hundreds of wavelengths. This information can be used to derive vegetation indices (VIs) that are correlated with agronomic and physiological traits. However, the data ...

Article

Wheat quality improvement at CIMMYT and the use of genomic selection on it

Guzman, C.; Peña, R.; Singh, R.G.; Autrique, E.; Dreisigacker, S.; Crossa, J.; Rutkoski, J.; Poland, J.; Battenfield, S. (Elsevier, 2016)

The International Center for Maize and Wheat Improvement (CIMMYT) leads the Global Wheat Program, whose main objective is to increase the productivity of wheat cropping systems to reduce poverty in developing countries. ...

Article

Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model

Lopez-Cruz, M.; Poland, J.; Jannink, J.L.; De los Campos, G.; Crossa, J.; Singh, R.P.; Dreisigacker, S.; Bonnett, D.; Autrique, E. (Genetics Society of America, 2015)

Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype · environment interaction( G·E). ...

Article

Grain yield and stability of white early maize hybrids in the highland valleys of Mexico

Torres Flores, J.L.; Mendoza García, B.; Prasanna, B.M.; Alvarado, G.; San Vicente, F.M.; Crossa, J. (Crop Science Society of America (CSSA), 2017)

There is great interest in Mexico in reducing imports of grain and becoming self-sufficient in cereal production. Identifying high-yielding and stable maize (Zea mays L.) hybrids from different research institutions could ...

Article

Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones

Saint Pierre, C.; Burgueño, J.; Fuentes Dávila, G.; Figueroa López, P.; Solís Moya, E.; Ireta Moreno, J.; Hernández Muela, V.M.; Zamora Villa, V.; Vikram, P.; Mathews, K.; Sansaloni, C.P.; Sehgal, D.; Jarquin, D.; Wenzl, P.; Sukhwinder-Singh; Crossa, J. (Nature Publishing Group, 2016)

Genomic and pedigree predictions for grain yield and agronomic traits were carried out using high density molecular data on a set of 803 spring wheat lines that were evaluated in 5 sites characterized by several environmental ...

Article

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat

Juliana, P.; Singh, R. P.; Singh, P.K.; Crossa, J.; Huerta-Espino, J.; Caixia Lan; Bhavani, S.; Rutkoski, J.; Poland, J.; Bergstrom, G.C.; Sorrells, M.E. (Springer, 2017)

The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies ...

Article

Single-step genomic and pedigree genotype x environment interaction models for predicting wheat lines in international environments

Perez-Rodriguez, P.; Crossa, J.; Rutkoski, J.; Singh, R. P.; Legarra, A.; Autrique, E.; De los Campos, G.; Burgueño, J.; Dreisigacker, S. (Crop Science Society of America, 2017)

Genomic prediction models have been commonly used in plant breeding but only in reduced datasets comprising a few hundred genotyped individuals. However, pedigree information for an entire breeding population is frequently ...

Article

Genomic prediction in CIMMYT maize and wheat breeding programs

Crossa, J.; Perez, P.; Hickey, J.; Burgueño, J.; Ornella, L.; Ceron-Rojas, J.; Zhang, X.; Dreisigacker, S.; Babu, R.; Li, Y.; Bonnett, D.; Mathews, K. (Springer Nature, 2014)

Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending ...

Article

Evaluation and interpretation of interactions

Crossa, Jose; Vargas Hernández, M.; Cossani, C.M.; Alvarado, G.; Burgueño, J.; Mathews, K.L.; Reynolds, M.P. (American Society of Agronomy, 2013)

Understanding the factors that define a given interaction is important in agricultural, agronomic, and plant breeding research, where agronomic treatments or genotypes are evaluated under several environmental conditions ...

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Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures

Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield

Wheat quality improvement at CIMMYT and the use of genomic selection on it

Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model

Grain yield and stability of white early maize hybrids in the highland valleys of Mexico

Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat

Single-step genomic and pedigree genotype x environment interaction models for predicting wheat lines in international environments

Genomic prediction in CIMMYT maize and wheat breeding programs

Evaluation and interpretation of interactions

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Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures

Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield

Wheat quality improvement at CIMMYT and the use of genomic selection on it

Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model

Grain yield and stability of white early maize hybrids in the highland valleys of Mexico

Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat

Single-step genomic and pedigree genotype x environment interaction models for predicting wheat lines in international environments

Genomic prediction in CIMMYT maize and wheat breeding programs

Evaluation and interpretation of interactions