João Gilberto Corrêa da Silva

Adaptabilidade e estabilidade do rendimento de grãos de genótipos de feijão

Adaptation and stability analysis of grain yield of eleven bean (Phaseolus vulgarisL.) genotypes were performed using data collected from trials carried out in 23 locations of Rio Grande do Sul State (Brazil), from 1988/89 to 1993/94, comprising 72 environments. The objective was to identify the best genotypes for cultivation throughout the state as well as for breeding purposes. Genotypes, were Rio Tibagi, Guateian 6662, EMPASC201, FT 120, Macanudo, Pampa, Minuano, Macotaco, CNF 5491, Carioca and Irai. Segmented regression method with estimated join point was used. Absence of significant alteration of the genotype individual linear response rates indicated the linear regression method as appropriate for this study. All genotypes presented significant regression deviation, characterizing phenotypic instability. Genotypes differed in regard to average yield and response rate, being classified as: Minuano, Macotaco, CNF 5491 and Macanudo of general adaptation; Rio Tibagi, Pampa and Irai of poor adaptation to all environments; Guateian 6662 and EMPASC201 of specific adaptation to poor environments; genotypes FT 120 and Carioca of average adaptation to all environments. These results pointed out Minuano, Macotaco, CNF 5491 and Macanudo as the most productive and best adapted to the considered environments. These genetically related genotypes displayed similar adaptability among themselves and different from the others as well as no differential stability from some of them.

Ajuste do rendimento para a variação do estande em experimentos de melhoramento genético do feijão

O objetivo deste trabalho foi avaliar o ajuste do rendimento pela variacao do estande em experimentos de feijao e propor procedimento para ajustamento por analise de co-variacao. Utilizaram-se dados de 33 ambientes do Ensaio Estadual de Feijao do Rio Grande do Sul. Realizaram-se as analises de variacao e de co-variacao de rendimento e de estande em cada ambiente. Foram considerados quatro modelos de ajustamento alternativos: sem ajuste para a variacao do estande; com ajuste para o estande medio geral; com ajuste para os estandes medios dos genotipos; e com ajuste para os estandes medios dos grupos de genotipos. Em 70% dos ambientes, ocorreu efeito linear ou quadratico significativo de estande sobre rendimento e em 85% efeito significativo de genotipo sobre estande. O efeito compensatorio manifestou-se com diferentes intensidades nos ambientes. O ajuste do rendimento para a variacao do estande, considerando o efeito de genotipos sobre o estande, e importante em ensaios de melhoramento do feijao. E necessario o registro de informacoes que permitam discriminar a origem da variacao do estande.

Influência do ethephon e do ácido indolbutírico no enraizamento de estacas de ramos de goiabeira (Psidium guajava L.)

The objective of this work was to evaluate the influence of ethephon, indole butyric acid (IBA) and substrate on root formation of guava stem cuttings. Orchard plants withfive years old were sprayed with ethephon in concentrations of zero, 50 and 100ppm. However, after seven days, stem cuttings were made, of the last lauching with three knots by cutting including one pair of leaves. Cuttings were treated with concentrations of zero, 1000, 2000. 3000 and 4000ppm of liquid IBA by immersion of two centimeter of the basis of cutting for five minutes. Vermiculite and ash rice were used as substrato. Results showed that the use of vermiculite produced greater percentage of cuttings rooted (21.48%). A greater cutting rooted and number of roots were obtained using ethephon and IBA.

Regionalização para o cultivo do feijão no Rio Grande do Sul com base na interação genótipo x ambiente

Common bean cropping regionalization in Rio Grande do Sul State, Brazil, based on genotype x environment interaction The stratification of the crop region is a strategy used to control the effect of the genotype x environment interaction. This approach is based on results of an experiment conducted in several years and locations, in which the statistical analysis has difficulties originated from the incomplete data structure and variance heterogeneity of the experimental error. This paper reports results of a research on the magnitude and the nature of the genotype x environment interaction and on the convenience for the stratification of the common bean production region in Rio Grande do Sul State, Brazil, for the control of this interaction. Data from the Common Bean Yield State Trial carried out in 24 locations for eight years were evaluated. Joint analyses of each year, of two sub-groups of four and of a set of eight years, as well as cluster analyses, were performed using a methodology that circumvents the statistical difficulties. The results of the annual analyses revealed highly significant genotype x location interaction. This interaction was also significant in the set of the eightyears, but not significant in the two groups of four-years. The genotype x location x year interaction was highly significant in these three sets of years. The cluster analyses based on the eight years constituted sub-regions incoherent with the sub-regions formed by the annual analyses, which were not consistent among themselves. The results point out for the inadequacy of a regional division of the area of common bean production in Rio Grande do Sul.

Um algoritmo prático para determinação da variância do estimador de um contraste de parâmetros

Significance tests of contrasts of effects of levels of a factor or of combinations of levels of two or more factors require the knowledge of the estimates of the variances of the estimators of these contrasts. In general, the expressions of these estimates for experiments with complex designs are not available in textbooks. Their algebraic derivation from the equation of the statistical model is tedious. A practical algorithm for obtaining the variance of the estimator of any contrast of parameters for balanced complete designs is presented. The algorithm is based on the expected values of mean squares.