Cultivar development of allogamous crops

Souza, Cláudio Lopes de

doi:10.1590/s1984-70332011000500003

Cited by 12 publications

(10 citation statements)

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“…In reciprocal crosses that present superior combining ability, the progenies of each population are selected and the genotypes are recombined to generate enhanced populations (Souza Jr., 2011), so that the evaluation is made among populations and recombination is done within each population, thereby maintaining the identity of each population. Therefore, in this type of process two types of progeny are required, one for evaluation (interpopulational) and the second for recombination (intrapopulational;Souza Jr., 2001).…”

Section: Introductionmentioning

confidence: 99%

“…However, in many situations it has been reported that these interpopulational selection methods have significantly increased the interpopulational hybrid response in one of the populations, with unsatisfactory response, or even a negative response, in another population (Souza Jr., 1999). For a more comprehensive discussion of RRS we suggest reading Hallauer et al (2010) andSouza Jr. (2011).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of progenies from the fifth reciprocal recurrent selection cycle in maize

Alves¹,

Pádua²,

Dias³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. The objective of this study was to evaluate the performance of 119 full sib progenies of the fifth cycle of reciprocal recurrent selection (RRS) derived from of Universidade Federal de Lavras maize breeding program. The experiment was carried out in an 11 x 11 triple lattice design at two locations (Lavras, Lambari). The plots consisted of two rows of 3 m, with four plants per 1 m and 0.60 meters of spacing between lines. The grain yield was obtained as kg/plot through weighing of husked ears. The contrast between progenies and controls was not significant, indicating there were no significant differences among the average grain yields of the progenies and controls. When considering the joint analysis, heritability was 64.2%; however, this estimate did not differ from the values estimated for each location separately. Estimates of genetic and phenotypic variance among progenies ranged from 0.21 to 0.28 and 0.30 to 0.47, respectively. Estimates of selection gain, for 10% selection intensity, indicated gains of 16% in the joint analysis of the two locations. The progenies of the fifth cycle of RRS had high average grain yield, associated with high variability. In comparison to the average grain yields exhibited by the controls, it was concluded that the progenies have the potential to be commercially exploited.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of progenies from the fifth reciprocal recurrent selection cycle in maize

Alves¹,

Pádua²,

Dias³

et al. 2015

Genet. Mol. Res.

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“…On the other hand, the mixed models, in which treatments effects are assumed as random, the genetic effects can be predicted free of the influence of the fixed model effects by using the Best Linear Unbiased Predictor -BLUP (Henderson 1975). The BLUP method has been widely used in data analyses of animal breeding programs, but has only recently been adopted in plant breeding programs (Piepho et al 2008, Souza Jr 2011.…”

Section: Introductionmentioning

confidence: 99%

“…Such situations are mere routine in maize breeding programs, where large numbers of treatments are evaluated at numerous locations (Mi et al 2011, Souza Jr 2011, Fritsche-Neto 2010. Moreover, the MHPRVG multiplied by the overall mean of the experiments provides a measurement in the same magnitude of the parameter evaluated, facilitating agronomic interpretations.…”

Section: Introductionmentioning

confidence: 99%

Adaptability and stability of maize varieties using mixed model methodology

Mendes

Guimarães

Souza

et al. 2012

Crop Breed. Appl. Biotechnol.

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“…New methods, such as the Best Linear Unbiased Prediction (BLUP), are useful in the analysis of VCU trials data in view of their accuracy and precision, especially for the annual elimination of inferior lines and particularly in non-orthogonal data analysis (Borges et al 2012). Originally, BLUP was used in animal breeding and has only recently been exploited in plant breeding programs (Souza Jr. 2011). …”

Section: Opportunities and Difficulties With The New Regulatory Framementioning

confidence: 99%