This work aimed to identify the most effective method to estimate the coefficient of repeatability in genotypes of U. brizantha and predict the minimum number of measurements required for some qualitative traits. It were evaluated 9 genotypes in a randomized block design with two replications in the rainy season and drought in 2000. It were evaluated the following qualitative traits: volume of gas, in mL, packed in fast and slow fraction, crude protein; neutral detergent fiber, acid detergent fiber, cellulose, lignin sulfuric acid, silica and in vitro digestibility of organic matter. The repeatability coefficient (r) was estimated considering different strategies: Analysis of variance, principal component analysis based on the correlation matrix (CPCOR), principal components analysis based on the matrix of phenotypic variance and covariance and structural analysis based on the correlation matrix. The CPCOR method, provided more accurate estimates of r and the number of measurements required for the qualitative traits assessed due to the cyclical behavior of genotypes of U. brizantha. The traits neutral detergent fiber, cellulose and silica require two measurements, while the remaining characters require four measurements to predict the actual value of genotypes of U. brizantha with a minimum accuracy of 80%, by CPCOR method.

A B S T R A C TIn order to evaluate the agronomic performance and estimate the genetic variability of 24 common bean genotypes grown in the Savanna-Pantanal ecotone and see, which characters can be used for selection of superior genotypes. Treatments consisted of 24 common bean genotypes (CNFC Requinte, BRS Pontal, BRS 9435 Cometa e BRS Estilo). The following traits were evaluated: Early flowering, early maturity, height of the first pod, number of pods per plant, number of grains per pod, weight of 100 grains and grain yield. The following parameters were estimated: environmental, phenotypic and genotypic variances, experimental and genotypic coefficient of variation, genotypic coefficient of determination, b quotient, environmental, phenotypic and genetic correlations. The CNFP 10794 genotype had the best agronomic performance in the Savanna-Pantanal ecotone region. The population presents genetic variability and potential for selection of all traits. Based on genetic parameters estimates, the characters number of grains per pod and weight of hundred grains can be used in direct selection for more productive genotypes.

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A B S T R A C TThe monitoring of the Earth's surface and the dynamics of its vegetation using remote sensing techniques stands out in agricultural activities. The objective of this study was to estimate and map areas cultivated with soybean [Glycine max (L.) Merr.] by means of mono and time-series MODIS images in Paraná state through principal component techniques. For this mapping were used vegetation index (EVI and CEI) with the help of as time-series from images of MODIS sensor also was performed by supervised classification algorithms and partially unsupervised with use of principal component analysis. For statistical evaluation parameters were used Kappa and overall accuracy and their respective Z and t-tests. When analyzing the data obtained by the methods used in the estimates of soybean areas it appears that the ratings by the CEI index was highlighted with higher Kappa parameters (κ) and Overall Accuracy (OA), unlike the classifier K-means. For the principal component used five images including vegetation indices, presented to the Kappa 0.48 parameter. The mapping, discrimination and quantification of soybean fields in the state of Paraná was possible with the use of classifiers and MODIS images, which the systematization presented results of Kappa parameters and overall accuracy satisfactory.