Novel strategies for genomic prediction of untested single-cross maize hybrids using unbalanced historical data

2019 ◽  
Vol 133 (2) ◽  
pp. 443-455 ◽  
Author(s):  
K. O. G. Dias ◽  
H. P. Piepho ◽  
L. J. M. Guimarães ◽  
P. E. O. Guimarães ◽  
S. N. Parentoni ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Historical Data ◽  
Maize Hybrids ◽  
Single Cross

scholarly journals Genomic Prediction of Hybrid Combinations in the Early Stages of a Maize Hybrid Breeding Pipeline

2016 ◽  
Author(s):  
D.C. Kadam ◽  
S.M. Potts ◽  
M.O. Bohn ◽  
A.E. Lipka ◽  
A.J. Lorenz
Keyword(s):  
Genomic Prediction ◽  
Cross Validation ◽  
Hybrid Breeding ◽  
Maize Breeding ◽  
Cross Prediction ◽  
Maize Hybrids ◽  
Early Stages ◽  
Single Cross ◽  
Hybrid Maize ◽  
Single Cross Hybrids

AbstractPrediction of single-cross hybrid performance has been a major goal of plant breeders since the beginning of hybrid breeding. Genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single cross performance. Most of the studies rather focused on predicting top cross performance using single tester to determine the inbred parent’s worth in hybrid combinations. Moreover, no studies have examined the potential of predicting single crosses made among random progenies derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objective of this study was to evaluate the potential of genomic prediction for identifying superior single crosses early in the breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single-cross hybrids representing the Iowa Stiff Stalk Synthetic/Non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The single cross prediction accuracies estimated using cross-validation ranged from 0.40 to 0.74 for grain yield, 0.68 to 0.91 for plant height and 0.54 to 0.94 for staygreen depending on the number of tested parents of the single crosses. The genomic estimated general and specific combining abilities showed a clear advantage over the use of genomic covariances among single crosses, especially when one or both parents of the single cross were untested in hybrid combinations. Overall, our results suggest that genomic prediction of the performance of single crosses made using random progenies from the early stages of the breeding pipeline holds great potential to re-design hybrid breeding and increase its efficiency.

Modeling copy number variation in the genomic prediction of maize hybrids

2018 ◽  
Vol 132 (1) ◽  
pp. 273-288 ◽  
Author(s):  
Danilo Hottis Lyra ◽  
Giovanni Galli ◽  
Filipe Couto Alves ◽  
Ítalo Stefanine Correia Granato ◽  
Miriam Suzane Vidotti ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Genomic Prediction ◽  
Copy Number ◽  
Maize Hybrids ◽  
Number Variation

Heterosis in relation to genetic divergence in short duration maize (Zea mays L.)

2021 ◽  
pp. 137-142
Author(s):  
Bal Krishna ◽  
Birender Singh ◽  
Shyam Sundar Mandal ◽  
Rashmi Kumari ◽  
Tushar Ranjan
Keyword(s):  
Genetic Distance ◽  
Genetic Divergence ◽  
Zea Mays L ◽  
Correlation Coefficients ◽  
Negative Association ◽  
Coefficient Of Determination ◽  
Maize Hybrids ◽  
Single Cross ◽  
Per Se ◽  
Linear Regressions

Thirteen lines and three testers were used to produce 39 single cross maize hybrids by line Ítester mating design. The genetic divergence among thirteen lines and three tester of maize were estimated by using Mahalanobis D2 statistic for twelve characters. The genotypes were grouped into five clusters. Cluster I comprised 12 parental genotypes (L1, L2, L3, L4, L5; L6, L7, L8, L9, L11; L12, L13), while Cluster II (T3), III (T1), IV (L10) and V (T2) were mono-genotypic, suggesting more variability in genetic makeup of the genotypes included in these clusters. The correlation coefficients and linear regressions were used to know the effects of parental genetic distance in determining heterosis and per se performance of the hybrids. Parental genetic distance exhibited significant negative association and significant linear regression along with very low coefficient of determination with better parent heterosis (BPH) and non-significant with per se performance of the hybrids. The present investigation, therefore, the parental genetic distance has significant role in determining heterosis and hybrid performance in kharif maize.

scholarly journals Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Wagner Mateus Costa Melo ◽  
Renzo Garcia Von Pinho ◽  
Marcio Balestre
Keyword(s):  
Training Trial ◽  
Cross Validation ◽  
Predictive Accuracy ◽  
Field Performance ◽  
Training Population ◽  
Maize Hybrids ◽  
Single Cross ◽  
The Cross ◽  
Predictive Validation ◽  
Single Cross Hybrids

The present study aimed to predict the performance of maize hybrids and assess whether the total effects of associated markers (TEAM) method can correctly predict hybrids using cross-validation and regional trials. The training was performed in 7 locations of Southern Brazil during the 2010/11 harvest. The regional assays were conducted in 6 different South Brazilian locations during the 2011/12 harvest. In the training trial, 51 lines from different backgrounds were used to create 58 single cross hybrids. Seventy-nine microsatellite markers were used to genotype these 51 lines. In the cross-validation method the predictive accuracy ranged from 0.10 to 0.96, depending on the sample size. Furthermore, the accuracy was 0.30 when the values of hybrids that were not used in the training population (119) were predicted for the regional assays. Regarding selective loss, the TEAM method correctly predicted 50% of the hybrids selected in the regional assays. There was also loss in only 33% of cases; that is, only 33% of the materials predicted to be good in training trial were considered to be bad in regional assays. Our results show that the predictive validation of different crop conditions is possible, and the cross-validation results strikingly represented the field performance.

Performance of Exotic × Temperate Single‐Cross Maize Hybrids

Crop Science ◽  
1995 ◽  
Vol 35 (4) ◽  
pp. 1042-1045 ◽  
Author(s):  
E. Brent Godshalk ◽  
Keith D. Kauffmann
Keyword(s):  
Maize Hybrids ◽  
Single Cross

scholarly journals Evaluation of maize hybrids and environmental stratification by the methods AMMI and GGE biplot

2010 ◽  
Vol 10 (3) ◽  
pp. 247-253 ◽  
Author(s):  
Rogério Lunezzo de Oliveira ◽  
Renzo Garcia Von Pinho ◽  
Márcio Balestre ◽  
Denys Vitor Ferreira
Keyword(s):  
Interaction Analysis ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Multiplicative Interaction ◽  
Maize Hybrids ◽  
Growing Seasons ◽  
Single Cross ◽  
Predictive Correlation ◽  
Environmental Stratification ◽  
Main Effects

The purpose of this study was to evaluate yield stability, adaptability and environmental stratification by the methods AMMI (Additive Main Effects and Multiplicative Interaction Analysis) and GGE (Genotype and Genotypes by Environment Interaction) biplot and to compare the efficiency of these methods. Data from the evaluation of 20 experimental single-cross and three commercial hybrids and 11 locations, in two growing seasons, 2005/2006 and 2006/2007 were used. Analyses of variance, adaptability, stability and environmental stratification were performed. A better combination of adaptability and stability was observed in the hybrids 10 and 16, according to the graphics of AMMI and GGE biplot methods, respectively. The number of locations could be reduced by 28% based on stratification. The predictive correlation of the AMMI and GGE methods was 0.88 and 0.86, respectively. The results showed that it is possible to reduce the number of evaluation sites; AMMI tended to be more accurate than GGE analysis.

Contributions of Parental Inbreds and Heterosis to Morphology and Yield of Single-Cross Maize Hybrids in China

Crop Science ◽  
2014 ◽  
Vol 54 (1) ◽  
pp. 76-88 ◽  
Author(s):  
Yongxiang Li ◽  
Yu Li ◽  
Xinglin Ma ◽  
Cheng Liu ◽  
Zhizhai Liu ◽  
...  
Keyword(s):  
Maize Hybrids ◽  
Single Cross
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