Acta Scientiarum Agronomy

URI permanente para esta coleçãohttps://thoth.dti.ufv.br/handle/123456789/11111

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2019 - 201912020 - 20212

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Assunto: search.filters.subject.Genética e melhoramento

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Agora exibindo 1 - 3 de 3
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    Plot size for evaluation of Arabica coffee yield
    (Editora da Universidade Estadual de Maringá - EDUEM, 2019) Moraes, Bráulio Fabiano Xavier de; Toledo, Fernando Henrique Ribeiro Barroso; Dias, Kaio Olímpio das Graças; Andrade, Vinícius Teixeira; Ferreira, Daniel Furtado; Gonçalves, Flávia Maria Avelar
    In most cases, in genetic breeding of Arabica coffee, plot size is defined in an empirical manner. It is often based only on the experience of the breeders and the availability of resources, potentially leading to a reduction in precision. Therefore, the aim of this study was to estimate the size of the experimental plot for evaluation of coffee yield. We evaluated two experiments for validation of cultivars with 12 treatments set up in a randomized complete block design with three replicates and plots composed of 50 plants. Each plant was considered as a basic unit. Estimates of ideal plot size were made by maximum curvature of the coefficient of variation, linear-plateau segmented model and by the resampling methods. We discussed the variations in the parameter estimates for different plot sizes. Divergence was seen among the plot sizes estimated by the different methodologies. Increasing the number of plants per plot led to a higher experimental precision to the point that the increase was no longer significant. The plot size recommended for evaluating coffee production is from seven to 19 plants.
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    Beverage quality of Coffea canephora genotypes in the western Amazon, Brazil
    (Editora da Universidade Estadual de Maringá - EDUEM, 2021) Morais, Johnnescley Anes de; Rocha, Rodrigo Barros; Alves, Enrique Anastácio; Espindula, Marcelo Curitiba; Teixeira, Alexsandro Lara; Souza, Carolina Augusto de
    This study aimed to evaluate the beverage quality of Coffea canephora genotypes in different environments of the western Amazon to assist plant selection and new cultivar development. To analyze beverage quality, samples of cherry coffee beans were collected separately for each genotype from clonal competition trials installed in the municipalities of Ouro Preto do Oeste, Alta Floresta do Oeste, Porto Velho, and Ariquemes in Rondônia State and Rio Branco in Acre State (Brazil). The beverage quality was assessed using the Robusta Cupping Protocol, which attribute to each genotype a score in a range from 0 to 100, highlighting nuances. Analysis of variance and principal components using reference points were used to quantify genotype x environment interaction (G x E). The analysis of variance indicated that genotypic and G x E interaction effects were significant (p < 0.01). By using a centroid dispersion method, we could identify four clones of low, eight of specific (to favorable or unfavorable environments), and seven of broad adaptability to the environments. The clones BRS 2314, 11, and 17 had average quality scores above 80 in all environments, with potential for specialty coffee production. The clones BRS 1216, BRS 3220, and BRS 3193 presented unstable behavior, with beans of higher quality in some of the evaluated environments. Such inconsistency in clone behavior is caused by unpredictable changes in plant performance in different environments. Our results indicate that both genotypic (clones) and G x E interaction effects are important for the expression of coffee beverage quality. However, the clones BRS 3213, BRS 3210, and BRS 2299 had less prominent nuances, with lower potential for specialty coffee production.
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    Trait selection using procrustes analysis for the study of genetic diversity in Conilon coffee
    (Editora da Universidade Estadual de Maringá - EDUEM, 2020) Pontes, Daiana Salles; Rosado, Renato Domiciano Silva; Cruz, Cosme Damião; Nascimento, Moysés; Oliveira, Ana Maria Cruz; Pensky, Scott Michael
    Trait selection is occasionally necessary to save money and time, as well as accelerate breeding program processes. This study aimed to propose two criteria to select traits based on a Procrustes analysis that are poorly explored in genetic breeding: Criterion 1 (backward algorithm) and Criterion 2 (exhaustive algorithm). Then, these two criteria were further compared with Jolliffe’s criterion, which has often been used to select traits in genetic diversity studies. Sixteen agronomic traits were considered, and 40 Conilon coffee (Coffea canephora) accessions were evaluated. This study showed that the flexibility in selecting traits by researcher preference, graphical visualization, and Procrustes statistic through criteria 1 and 2 is a fast and reliable alternative for decision-making. These decisions are based on the removal and addition of traits for phenotyping in studies of Conilon coffee diversity that can be applied to other crops. Other relevant aspects of selection traits criteria were also discussed.