Salacia crassifolia traditionally known as “Bacupari-do-Cerrado” is used to treat kidney problems, and as a healing agent for coughs and malaria. The phytochemical study of the S. crassifolia roots led to the isolation of thirteen compounds: abruslactone-A (1), urs-12-ene-3β,25,30-triol (2), carioprystimerin (3), β-sitosterol (4), pristimerin (5), dispermoquinone (6), netzahualcoyonol (7), 20-hydroxy-20-epi-tingenone (8), 6-oxo-pristimerol (9), 9β,10β-epoxi-3β-hydroxy-1βH,4βH,5βH,7βH,11αH-guaian-12,8β-olide (10), 3-O-b-D-glucosyl-b-sitosterol (11), 4`-O-methylepigalocatechin (12) and cerebroside (13). The chemical structures of 1-13 were determined by IR, 1D/2D NMR together with X-ray diffractometry. Compounds 2 and 10 are herein described for the first time. Extracts of S. crassifolia and compounds 3, 5, 8 and 9 were evaluated on acetylcholinesterase inhibition, in vitro cytotoxic activity and in vivo toxicity tests using Caenorhabditis elegans model. All tested compounds inhibited acetylcholinesterase, and compounds 3, 8 and 9 demonstrated a greater potential when compared to the standard eserine. The tested compounds showed low cytotoxicity against the THP-1, K562 and MDA-MB-231 cancer cell lines. None of the tested compounds and extracts were toxic against C. elegans since the larvae survival rate in L1 stage was higher than 90%.

O uso operacional de imagens de satélites de sensoriamento remoto para mapear lavouras de café em grandes áreas, para fins de obtenção de estatísticas agrícolas confiáveis e oportunas, ainda se encontra em desenvolvimento. Diversos são os fatores que dificultam a correta identificação e mapeamento do parque cafeeiro. Contudo, os avanços tecnológicos observados nos últimos anos em termos de aquisição de imagens com melhor qualidade e em maior quantidade, bem como o desenvolvimento de novas ferramentas de análise, propiciam o desenvolvimento de um método operacional que pode contribuir na formação das estatísticas agrícolas oficiais do café no Brasil. Neste sentido, o presente trabalho tem por objetivo relatar a metodologia e apresentar os resultados do mapeamento das áreas cultivadas com café nos Estados de Minas Gerais e São Paulo, utilizando imagens de sensoriamento remoto e técnicas de geoprocessamento. A abordagem metodológica consiste em quatro fases: a) restauração das imagens e georreferenciamento; b) classificação não supervisionada; c) interpretação visual na tela do computador para minimizar erros de omissão e inclusão, e d) determinação da área cultivada com café. Os resultados indicaram que a metodologia utilizada foi adequada para o mapeamento das lavouras de café de Minas Gerais e São Paulo.

The operational use of remote sensing images to map coffee fields in large areas, in order to obtain reliable and timely agricultural statistics, is still under development. Several factors raise difficulties to correctly identify and map the coffee crop. However, technological advances observed in the last years, in terms of image acquisition with improved quality and greater quantity, as well as the development of new tools for image analysis, is favoring the development of an operational method that may contribute to establish the official coffee crop statistics in Brazil. Therefore, the present work has the objective to describe the method and to present the result of the coffee fields mapped in the states of Minas Gerais and São Paulo using remote sensing images and geoprocessing techniques. The methodological approach consisted of four steps: a) image restoration and georeferencing; b) non-supervised classification; c) visual interpretation on the computer screen to suppress omission and commission errors; and d) coffee crop area estimation. The results indicated that the applied method was appropriate to map the coffee crop in the states of Minas Gerais and São Paulo.