The effect of bienniality on genomic prediction of yield in arabica coffee

Carvalho, Humberto Fanelli; Galli, Giovanni; Ferrão, Luís Felipe Ventorim; Nonato, Juliana Vieira Almeida; Padilha, Lílian; Maluf, Mirian Perez; Resende, Marcio F. R.; Filho, Oliveiro Guerreiro; Fritsche‐Neto, Roberto

doi:10.1007/s10681-020-02641-7

Cited by 27 publications

(23 citation statements)

References 44 publications

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“…Coffee trees have a long reproductive cycle, with fluctuations in production over time (biennial), and differences in precocity and productive longevity [ 12 ]. For this reason, accurate, efficient, and informative statistical methods, such as the residual maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure, have been recommended for the genetic analysis of coffee trees [ 13 , 14 ], considering phenotypic [ 14 – 21 ] and genomic [ 22 – 26 ] data.…”

Section: Methodsmentioning

confidence: 99%

Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

et al. 2021

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Breeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.

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Section: Methodsmentioning

confidence: 99%

Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

et al. 2021

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“…The phenotypic values were corrected for the effect of years in the R software according to the correction proposed by (Fanelli Carvalho et al, 2020). The linear model used was: where y ik is the phenotypic value for the genotype i and the year k ; μ is the population mean; a k is the fixed effect of the k th year; g i is the fixed effect of the i th genotype; and e ik is the random effect of residual, with .…”

Section: Methodsmentioning

confidence: 99%

Single and Multi-trait Genomic Prediction for agronomic traits inEuterpe edulis

Canal

Barreto

Almeida

et al. 2022

Preprint

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Popularly known as juçaizeiro, Euterpe edulis has been gaining prominence in the fruit growing sector and has demanded the development of superior genetic materials. As it is a native species and still little studied, the application of more sophisticated techniques can result in higher gains with less time. Until now, there are no studies that apply genomic prediction for this crop, especially in multi-trait analysis. In this sense, this study aimed to apply new methods and breeding techniques for the juçaizeiro, to optimize this breeding program through the application of genomic selection. This data consisted of 275 juçaizeiro genotypes from the breeding population of Rio Novo do Sul-ES, Brazil. The genomic prediction was performed using the multi-trait (G-BLUP MT) and single-trait (G-BLUP ST) models and the selection of superior matrices was based on the selection index of Mulamba and Mock. Similar results for predictive ability were observed for both models. However, the G-BLUP ST model provided greater selection gains when compared to the G-BLUP MT. For this reason, the genomic estimated breeding values (GEBVs) from the G-BLUP ST were used to select the six superior genotypes (UFES.A.RN.390, UFES.A.RN.386, UFES.A.RN.080, UFES.A.RN.383, UFES.S.RN.098, and UFES.S.RN.093), to provide superior genetic materials for the development of seedlings and implantation of productive orchards, which will meet the demands of the productive, industrial and consumer market

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“…In autogamous breeding programs, plant selection is practiced in advanced generations of self-fertilization, maximizing genetic progress through the additive effects of genes (Hallauer et al, 2010). Classical C. arabica breeding is composed of genealogy and backcross breeding methods, and the mating system is applied for effective pure-line selection from selfing and elite genotype testing (Fanelli Carvalho et al, 2020). Thus, in autogamous species, such as C. arabica, GCA is important for breeders because it depends on additive variance, while SCA depends on the variance due to deviations in dominance.…”

Section: Diallel Analysismentioning

confidence: 99%

Combining Ability and Molecular Marker Approach Identified Genetic Resources to Improve Agronomic Performance in Coffea arabica Breeding

Medeiros

Caixeta

Oliveira

et al. 2021

Front. Sustain. Food Syst.

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Plant breeding aims to develop cultivars with good agronomic traits through gene recombination and elite genotype selection. To support Coffea arabica breeding programs and assist parent selection, molecular characterization, genetic diversity (GD) analyses, and circulating diallel studies were strategically integrated to develop new cultivars. Molecular markers were used to assess the GD of 76 candidate parents and verify the crossing of potential F1 hybrids. Based on the complementary agronomic traits and genetic distance, eight elite parents were selected for circulating diallel analysis. The parents and 12 hybrids were evaluated based on 10 morpho-agronomic traits. For each trait, the effects of general and specific combining abilities, as well as the averages of the parents, hybrids, and predicted hybrids, were estimated. Crosses that maximize the genetic gains for the main agronomic traits of C. arabica were identified. Joint analysis of phenotypic and molecular data was used to estimate the correlation between molecular GD, phenotypic diversity (PD), phenotypic mean, and combining ability. The selection of parents that optimize the allele combination for the important traits of C. arabica is discussed in detail.

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The effect of bienniality on genomic prediction of yield in arabica coffee

Cited by 27 publications

References 44 publications

Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits

Single and Multi-trait Genomic Prediction for agronomic traits inEuterpe edulis

Combining Ability and Molecular Marker Approach Identified Genetic Resources to Improve Agronomic Performance in Coffea arabica Breeding

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