Value for cultivation and use of upland rice cultivars tested in multi-environments

Borges, Vanderley; Soares, Antônio Alves; Resende, Marcos Deon Vilela de; Reis, Miria Hespanhol Miranda; Cornélio, Vanda Maria de Oliveira; Leite, Natália Alves; Soares, Plínio César; Júnior, Geovani Tadeu Costa

doi:10.1590/s1984-70332012000100004

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…Similarly, the predicted genotypic (µ+g) values and the mean genotypic values (µ+g+gem) showed the same classification between genotypes; this indicates that the recommendation -besides being the same -can be made by both parameters; this also makes it possible to recommend the cultivars for untested sites in the experimental network using (µ+g) values, as the genotypic performance is free of interactions in this case. A similar result was also reported by Borges et al (2012).…”

Section: Resultssupporting

confidence: 91%

Agronomic performance of modern soybean cultivars in multi-environment trials

Matei

Benin

Woyann

et al. 2017

Pesq. agropec. bras.

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The objective of this work was to evaluate the productive performance, and the adaptability and stability parameters of modern soybean (Glycine max) cultivars in multi-environment trials, as well as to identify the ideal genotypes for eight growing environments in Brazil. A randomized complete block experimental design was carried out, with three replicates, for the evaluation of 46 soybean cultivars in eight environments, in the microregions of adaptation 102, 201, and 202, in the 2014/2015 crop season. A complex genotype x environment interaction occurred, with changes in the ranking of genotypes among locations. The NA 5909 RG, M6410IPRO, NS 5959 IPRO, NS6823RR, M5917IPRO, NS 6767 RR, and 6563RSF IPRO cultivars showed the highest mean yields. The NA 5909 RG, NS6823RR, M6410IPRO, and NS 5959 IPRO cultivars showed high adaptability and stability and high grain yield, in the evaluated environments, and were ranked next to the ideal genotype for the analyzed environments. There are modern soybean cultivars, which are adapted, stable, and highly productive, for cultivation in the microregions 102, 201, and 202 for soybean crop adaptation in Brazil.

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Section: Resultssupporting

confidence: 91%

Agronomic performance of modern soybean cultivars in multi-environment trials

Matei

Benin

Woyann

et al. 2017

Pesq. agropec. bras.

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“…Entretanto, no melhoramento de espécies anuais, seu uso não é tão frequente, embora haja um número crescente de relatos, em diferentes espécies, como milho (Viana et al, 2010a(Viana et al, , 2011(Viana et al, , 2012, feijão (Baldissera et al, 2012), arroz (Borges et al, 2012) e trigo .…”

Section: Introductionunclassified

Parentesco na seleção para produtividade e teores de óleo e proteína em soja via modelos mistos

Pinheiro

God

Faria

et al. 2013

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar influência da informação de parentesco na seleção de progênies de soja quanto à produtividade e aos teores de óleo e proteína, com base no uso de modelos mistos de predição dos valores genéticos. Novecentas progênies F 4:6 e 200 progênies F 4:7 de soja foram avaliadas nas safras 2010/2011 e 2011/2012, respectivamente. As progênies foram obtidas de cruzamentos múltiplos a partir de 57 progenitores. Os dados foram analisados por meio de modelos aleatórios (quadrados mínimos) e mistos BLUP/REML ("best linear unbiased prediction/restricted maximum likelihood"). Os maiores valores de ganhos preditos foram obtidos com o BLUP/REML. Os valores genéticos preditos com o método BLUP/REML, sem informação de parentesco, apresentaram alta correlação com aqueles obtidos com o modelo aleatório, além de detectada alta coincidência das progênies selecionadas. A inclusão da matriz de parentesco resultou na seleção de progênies diferentes e em maior acurácia na predição dos valores genéticos.Termos para indexação: Glycine max, BLUP/REML, ganhos de seleção, matriz de parentesco. Relationship in the selection for productivity and oil and protein contents in soybean using mixed modelsAbstract -The objective of this work was to evaluate the influence of relationship information for selecting soybean progenies as to their productivity, and oil and protein contents, using mixed models for the prediction of breeding values. Nine hundred F 4:6 and 200 F 4:7 soybean progenies were evaluated in the seasons 2010/2011 and 2011/2012, respectively. The progenies were obtained from multiple crosses from 57 parents. Data were analyzed using random models (least squares) and mixed models BLUP/REML (best linear unbiased prediction/restricted maximum likelihood). The highest values of predicted gains were obtained by BLUP/REML. The breeding values predicted with the use of BLUP/REML without relationship information were highly correlated with the ones obtained with the random model, and the selected progenies were rather coincident. The inclusion of the relationship matrix resulted in the selection of different progenies and in higher accuracy of breeding values.

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“…However, the application to direct recommendations of cultivars is still limited, probably because the lines are not the same in all test years, the number of lines being tested is limited, the precision in the determination of environmental indices is low and the correlation of the performance of lines with the environmental index is high. 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%

Breeders' work after cultivar development: the stage of recommendation

Federizzi

Carbonell

Pacheco

et al. 2012

Crop Breed. Appl. Biotechnol.

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Value for cultivation and use of upland rice cultivars tested in multi-environments

Abstract: -Data from 11 years of a breeding program for upland rice of the partner institutions

Cited by 5 publications

References 10 publications

Agronomic performance of modern soybean cultivars in multi-environment trials

Agronomic performance of modern soybean cultivars in multi-environment trials

Parentesco na seleção para produtividade e teores de óleo e proteína em soja via modelos mistos

Breeders' work after cultivar development: the stage of recommendation

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