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Article

Genomic resources in plant breeding for sustainable agriculture

Thudi, M.; Palakurthi, R.; Schnable, J.C.; Annapurna Chitikineni; Dreisigacker, S.; Mace, E.; Rakesh Kumar Srivastava; Satyavathi, C.T.; Odeny, D.A.; Vijay Tiwari; Hon-Ming Lam; Yan-Bin Hong; Singh, V.K.; Guowei Li; Yunbi Xu; Xiao-Ping Chen; Kaila, S.; Nguyen, H.T.; Sivasankar, S.; Jackson, S.A.; Close, T.J.; Wan Shubo; Varshney, R.K. (Elsevier, 2021)

Article

A zero altered Poisson random forest model for genomic-enabled prediction

Montesinos-Lopez, O.A.; Montesinos-López, A.; Mosqueda-Gonzalez, B.A.; Montesinos-Lopez, J.C.; Crossa, J.; Lozano-Ramirez, N.; Singh, P.K.; Valladares-Anguiano, F.A. (Genetics Society of America, 2021)

Article

Genomic prediction of rust resistance in tetraploid wheat under field and controlled environment conditions

Azizinia, S.; Bariana, H.S.; Kolmer, J.A.; Pasam, R.K.; Bhavani, S.; Chhetri, M.; Toor, A.; Miah, H.; Hayden, M.; Pino del Carpio, D.; Bansal, U.; Daetwyler, H.D. (MDPI, 2020)

Article

Incorporating genome-wide association mapping results into genomic prediction models for grain yield and yield stability in CIMMYT spring bread wheat

Sehgal, D.; Rosyara, U.; Mondal, S.; Singh, R.P.; Poland, J.A.; Dreisigacker, S. (Frontiers, 2020)

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

High-throughput phenotyping enabled genetic dissection of crop lodging in wheat

Singh, D.; Xu Wang; Kumar, U.; Liangliang Gao; Muhammad Noor; Imtiaz, M.; Singh, R.P.; Poland, J.A. (Frontiers, 2019)

Novel high-throughput phenotyping (HTP) approaches are needed to advance the understanding of genotype-to-phenotype and accelerate plant breeding. The first generation of HTP has examined simple spectral reflectance traits ...

Article

A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

Montesinos-Lopez, O.A.; Martin-Vallejo, J.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Montesinos-Lopez, A.; Juliana, P.; Singh, R.P. (Genetics Society of America, 2019)

Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...

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

Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches

Mondal, S.; Rutkoski, J.; Velu, G.; Singh, P.K.; Crespo-Herrera, L.A.; Guzman, C.; Bhavani, S.; Caixia Lan; Xinyao He; Singh, R.P. (Frontiers, 2016)

Current trends in population growth and consumption patterns continue to increase the demand for wheat, a key cereal for global food security. Further, multiple abiotic challenges due to climate change and evolving pathogen ...

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Genomic resources in plant breeding for sustainable agriculture

A zero altered Poisson random forest model for genomic-enabled prediction

Genomic prediction of rust resistance in tetraploid wheat under field and controlled environment conditions

Incorporating genome-wide association mapping results into genomic prediction models for grain yield and yield stability in CIMMYT spring bread wheat

Genomic prediction in CIMMYT maize and wheat breeding programs

High-throughput phenotyping enabled genetic dissection of crop lodging in wheat

A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

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

Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches

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Genomic resources in plant breeding for sustainable agriculture

A zero altered Poisson random forest model for genomic-enabled prediction

Genomic prediction of rust resistance in tetraploid wheat under field and controlled environment conditions

Incorporating genome-wide association mapping results into genomic prediction models for grain yield and yield stability in CIMMYT spring bread wheat

Genomic prediction in CIMMYT maize and wheat breeding programs

High-throughput phenotyping enabled genetic dissection of crop lodging in wheat

A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

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

Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches