Programa de Pós-graduação em Agronomia
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Item Distribuição espacial do percevejo-do-colmo (Tibraca limbativentris Stål) em arroz irrigado(Universidade Federal de Goiás, 2012-11-09) ALVES, Tavvs Micael; BARRIGOSSI, José Alexandre Freitas; http://lattes.cnpq.br/5377957113836597The injury imposed by Tibraca limbativentris Stål in plants of rice can negatively affect the production and reduce grain yield. Knowing the spatial arrangement of this species allows fast and accurate sampling and identifies focuses of infestation determining the ideal moment of decision-making for the control. The aim of this study was to investigate the spatial and probabilistic distribution of adults and nymphs of T. limbativentris in irrigated rice. Fifteen fields with plants of 50-80 days after emergency were sampled on approximately regular grids in 2008, 2010, and 2011. Poisson and Negative binomial distributions were tested and Pearson chi-squared test was used to determine a probability distribution with the best fit. Polynomial regressions of the number of individuals versus geographical coordinates were used to try detecting trends related with macroscale. Later, semivariograms were used to interpret the spatial dependence and distribution of insects. The semivariance of the samples obtained with nymphs showed patterns grouped in 13% of fields sampled. Similar pattern was also obtained by semivariograms of adults in 26% of fields sampled. However, there were no spatial dependence in the most of the sampled fields with adults (74%) and nymphs (87%). In conclusion, adults and nymphs of T. limbativentris are randomly distributed in irrigated rice fields, though rarely clustered pattern can occur. The probability distribution that best fits the data sampling is the Negative binomial. Adults and nymphs do not inhabit the same local in the rice field. Population levels above the value of economic damage may occur, but individuals are not present in about 2/3 of the units sampled. Polynomial regression models tested are not appropriate to fit the trends related to macro-scale in irrigated rice fields.