Using principal components to analyze the behavior of coffee grown in full sun and shadeusing principal components to analyze the behavior of coffee grown in full sun and shade
Keywords:organic coffee, vegetative characteristics, shading, productivity, multivariate data analysis
AbstractThe aim of this work is to describe the behavior of coffee (Coffea arabica L.) grown for nine years under organic management systems in full sun and shaded by banana trees (Musa sp.) and Erythrina verna Vell., in Valença, RJ. We performed a joint evaluation of vegetative characteristics, nutritional content and yield, with the aid of a principal component analysis. Twelve treatments were arranged in a randomized block design with four replications in a split plot. The plots evaluated farming systems in full sun and shade, and the subplots consisted of the following varieties of coffee: Tupi IAC 1669-33, MG 6851, IAC 3282 Icatu, Catucaí 2SL, Obatã IAC 1669-20; lineage IAC IAC 144 . After five years we assessed the following variables, height, stem and canopy diameter, leaf area, number of branches, number of nodes per branch, number of leaves present, the distance between nodes, the percentage of green,ripe and dried fruit, number of dead plants, number of plants with death of the apical bud, coffee yield, and foliar concentrations of N, P, K, Ca and Mg. A multivariate analysis efficiently discriminates the variables in full sun and shaded cropping systems. Shading increases the percentage of green fruit, leaf area, height, diameter, distance between nodes, number of leaves on the branches, number of branches and leaf N content, but does not reduce the level of productivity when the shade is adequate.
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