Coffee Science - v.13, n.3, 2018
URI permanente para esta coleçãohttps://thoth.dti.ufv.br/handle/123456789/10546
Navegar
Item Incidence and severity of coffee leaf rust, cercosporiosis and coffee leaf miner in coffee progenies(Editora UFLA, 2018-07) Lima, Amador Eduardo de; Sampaio Junior, Hudinilson Gilberto; Castro, Elisa de Melo; Carvalho, Samuel Pereira de; Silva, Fabiano França da; Lima Junior, Sebastião de; Carvalho, Alex Mendonça deCoffee leaf rust is the main disease of this crop, however cercosporiosis and coffee leaf miner can also cause significant damage when they reach high levels of infestation. Plant genetic improvement for resistance is one of the best tools for controlling plant diseases. The objective in this work was to identify F 3 progenies of Coffea arabica with resistance to coffee leaf rust, which present a lower incidence and severity of cercosporiosis and coffee leaf miner. The treatments were constituted by 10 progenies, besides two cultivars coffee leaf rust susceptible, used as a control. The experimental design was a randomized block design (RBD), with two replicates, each block consisting of 12 plots randomly distributed, each corresponding to one treatments. The following characteristics were evaluated: coffee leaf rust intensity and severity, cercosporiosis and coffee leaf miner, plants vegetative vigor, grain maturity uniformity and plants height. The progeny averages were grouped by the Scott & Knott test at 5% probability. Progenies 27, 30 and 15 were selected, since they presented low incidence in relation to coffee leaf rust, cercosporiosis and coffee leaf miner, and will be used to continue the breeding program.Item Selection of Coffea arabica L. hybrids using mixed models with different structures of variance-covariance matrices(Editora UFLA, 2018-07) Pereira, Fernanda Aparecida Castro; Carvalho, Samuel Pereira de; Rezende, Tiago Teruel; Oliveira, Leonardo Luiz; Maia, Diego Rosa BaquiãoThis study aimed to evaluate different structures of variance-covariance matrices in modeling of productive performance of coffee genotypes over the years, and select hybrids of Coffea arabica using mixed models. A mixed linear model was used to estimate variance components, heritability coefficients, and prediction of genetic values of hybrids and cultivars. Three commercial cultivars and eight hybrids of C. arabica L. were evaluated. The field production after acclimatization of seedlings was conducted in March 2006. The yield averages from 2009, 2010, 2011, 2013, and 2014 agricultural years were evaluated. The selection criteria of models were used to test 10 structures of variance-covariance matrices, and later a model was chosen to estimate the components of variance, heritability coefficients, and prediction of genetic values. According to Bayesian information criterion (BIC), the best structure was ARMA (Autoregressive Moving Average); however, considering the Akaike Information Criterion (AIC) and corrected Akaike Information Criterion (AICC), the CSH (Heterogeneous Composite Symmetric) was indicated. The Spearman correlation between the genotypic values obtained in the models with ARMA and CSH type R matrix was 0.84. The high and positive correlation indicates that the best model could involve the R matrix with ARMA or CSH structure. The heritability of individual genotypes differed from heritability in broad sense, which considers the independence among agricultural years. Hybrids with higher performance were identified by ordering the genotypic effects, among them, H 2.2, H 4.2, and H 6.1 hybrids were highlighted.