Fungi, mycotoxins and phytoalexin in peanut varieties, during plant growth in the field

The aim of the present study was to analyze the mycobiota, occurrence of mycotoxins (aflatoxins and cyclopiazonic acid), and production of phytoalexin (trans-resveratrol) in two peanut varieties (Runner IAC 886 and Caiapo) during plant growth in the field. Climatic factors (rainfall, relative humidity and temperature) and water activity were also evaluated. The results showed a predominance of Fusarium spp. in kernels and pods, followed by Penicillium spp. and Aspergillus flavus. Aflatoxins were detected in 20% and 10% of samples of the IAC 886 and Caiapo varieties, respectively. Analysis showed that 65% of kernel samples of the IAC 886 variety and 25% of the Caiapo variety were contaminated with cyclopiazonic acid. trans-Resveratrol was detected in 6.7% of kernel samples of the IAC 886 variety and in 20% of the Caiapo variety. However, trans-resveratrol was found in 73.3% of leaf samples in the two varieties studied. (C) 2011 Published by Elsevier Ltd.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.