Olívio Fernandes Galão

Alcalóides de flores e folhas de Erythrina speciosa Andrews

In vitro bioassays with leave extracts of Erythrina speciosa showed promising activity against Trypanosoma cruzi. From the flowers of E. speciosa two alkaloids were isolated: erysotrine and erythartine. The leaves furnished one alkaloid, nororientaline. The structures were determined on the basis of spectroscopic evidence. This is the first report about the investigation of alkaloids in flowers and leaves of this species, as well the first report of nororientaline occurrence in this plant.

Avaliação de biocombustível derivado do bio-óleo obtido por pirólise rápida de biomassa lignocelulósica como aditivo para gasolina

A biofuel was prepared from acid aqueous fraction (pH = 2) of bio-oil produced by fast pyrolysis (Bioware Technology) of lignocellulosic biomass (sugar cane residue) and tested in blends (2, 5, 10 e 20% v/v) with gasoline type C (common) marketed in Brazil. The specification tests made in the Refinery President Getulio Vargas (PETROBRAS) showed increasing in the octane number (MON) and antiknock index (AKI) with reduction in the residue generation during the combustion. The physicochemical characteristics of the biofuel were similar that combustible alcohol allowing its use as gasoline additive.

Artificial neural networks in the classification and identification of soybean cultivars by planting region

Vinte variedades de soja (Glycine max), quatorze convencionais e seis variedades transgenicas (RR) foram analisadas quanto ao teor de proteina, acido fitico, teor de oleo, fitosterois, cinzas, minerais e acidos graxos que foram tabelados e apresentados a rede neural do tipo perceptron de multiplas camadas para a classificacao e identificacao quanto a regiao de plantio e quanto a variedade convencional ou transgenica. A rede neural utilizada classificou e testou corretamente 100% das amostras cultivadas por regiao. Para o banco de dados contendo informacoes sobre sojas transgenicas e convencionais foi obtido um desempenho de 94,43% no treinamento da rede, 83,30% no teste e 100% na validacao.

Application of self-organising maps towards segmentation of soybean samples by determination of inorganic compounds content.

BACKGROUND In this study, 20 samples of soybean, both transgenic and conventional cultivars, which were planted in two different regions, Londrina and Ponta Grossa, both located at Paraná, Brazil, were analysed. In order to verify whether the inorganic compound levels in soybeans varied with the region of planting, K, P, Ca, Mg, S, Zn, Mn, Fe, Cu and B contents were analysed by an artificial neural network self-organising map. RESULTS It was observed that with a topology 10 × 10, 8000 epochs, initial learning rate of 0.1 and initial neighbourhood ratio of 4.5, the network was able to differentiate samples according to region of origin. Among all of the variables analysed by the artificial neural network, the elements Zn, Ca and Mn were those which most contributed to the classification of the samples. CONCLUSION The results indicated that samples planted in these two regions differ in their mineral content; however, conventional and transgenic samples grown in the same region show no difference in mineral contents in the grain.