Some endophytes can synthesize molecules that elicit the induction of plant resistance to infection by pathogens. The objective of this study was to demonstrate that protein fractions 42 and 75 from Bacillus amyloliquefaciens and Bacillus pumilus were capable of acting as elicitors of induced resistance in tomato plants against Xanthomonas vesicatoria, following partial resolution by gel-filtration chromatography. Tomato plants sprayed with protein fractions 42 and 75 reduced, respectively, 63.5 and 56.6% of bacterial spot, compared with control plants. Additionally, these fractions promoted the increase of peroxidase (POX) and polyphenol oxidase (PPO) enzyme activities in treated plants. In SDS-PAGE stained with silver nitrate, protein fractions 42 and 75 appeared as simple bands with estimated molecular mass of 28 and 43 kDa, respectively. We report the partial characterization of two macromolecules synthesized by endophytic bacteria that act as elicitors of systemic resistance in tomato against X. vesicatoria.

As condições de ambiente térmico e aéreo, no interior de instalações para animais, alteram-se durante o dia, devido à influência do ambiente externo. Para que análises estatísticas e geoestatísticas sejam representativas, uma grande quantidade de pontos distribuídos espacialmente na área da instalação deve ser monitorada. Este trabalho propõe que a variação no tempo das variáveis ambientais de interesse para a produção animal, monitoradas no interior de instalações para animais, pode ser modelada com precisão a partir de registros discretos no tempo. O objetivo deste trabalho foi desenvolver um método numérico para corrigir as variações temporais dessas variáveis ambientais, transformando os dados para que tais observações independam do tempo gasto durante a aferição. O método proposto aproximou os valores registrados com retardos de tempo aos esperados no exato momento de interesse, caso os dados fossem medidos simultaneamente neste momento em todos os pontos distribuídos espacialmente. O modelo de correção numérica para variáveis ambientais foi validado para o parâmetro ambiental temperatura do ar, sendo que os valores corrigidos pelo método não diferiram pelo teste Tukey, a 5% de probabilidade dos valores reais registrados por meio de dataloggers.

Thermal and air conditions inside animal facilities change during the day due to the influence of the external environment. For statistical and geostatistical analyses to be representative, a large number of points spatially distributed in the facility area must be monitored. This work suggests that the time variation of environmental variables of interest for animal production, monitored within animal facility, can be modeled accurately from discrete-time records. The aim of this study was to develop a numerical method to correct the temporal variations of these environmental variables, transforming the data so that such observations are independent of the time spent during the measurement. The proposed method approached values recorded with time delays to those expected at the exact moment of interest, if the data were measured simultaneously at the moment at all points distributed spatially. The correction model for numerical environmental variables was validated for environmental air temperature parameter, and the values corrected by the method did not differ by Tukey's test at 5% significance of real values recorded by data loggers.