Periódicos
URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
Navegar
3 resultados
Resultados da Pesquisa
Item 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 MichaelTrait 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.Item Adaptability and stability of organic-grown arabica coffee production using the modified centroid method(Crop Breeding and Applied Biotechnology, 2017-10) Moura, Waldênia de Melo; Oliveira, Ana Maria Cruz e; Gonçalves, Débora Ribeiro; Carvalho, Cássio Francisco Moreira de; Oliveira, Rebeca Lourenço de; Cruz, Cosme DamiãoThis study aimed to identify promising arabica coffee genotypes for organic systems. The experiments were arranged in a randomized block design, with 30 genotypes and three replications. The adaptability and stability analysis was carried out using the modified centroid method, considering the mean yield of two biennia (2005/2006 and 2006/2007, 2007/2008 and 2008/2009) in three municipalities (Araponga, Espera Feliz, and Tombos), totaling six environments. Significant genotype x environment interaction was observed for yield, and the municipality of Espera Feliz was the only favorable environment. Genotypes were classified into four of the seven groups proposed by the modified centroid method: maximum general adaptability (I), minimum adaptability (IV), mean general adaptability (V), and mean specific adaptability to favorable environments (VI). Cultivars IBC Palma 1, CatucaíAmarelo24/137, Sabiá 708, and H 518 are widely adapted, stable, productive and suitable for organic farming. Remove selectedItem Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation(Sociedade Brasileira de Ciência do Solo, 2012-03) Silva, Samuel de Assis; Lima, Julião Soares de SouzaThe spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 – 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K + , Ca 2+ , Mg 2+ , Na + , S, Al 3+ , pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characte- ristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.