Classification of Cabernet Sauvignon from Two Different Countries in South America by Chemical Compounds and Support Vector Machines
ABSTRACT A simple approach is proposed for the classification of Cabernet Sauvignon wines from two different countries in South America (Brazil and Chile). The strategy combines the wines’ functionality, designed as antioxidant activity (DPPH and ORAC), total polyphenols (TP), total anthocyanins (TA), and color, with a data mining technique known as support vector machines (SVM). The original dataset has 16 wine samples from Brazil and 113 from Chile. Algorithms were used to balance the dataset. Using resampling algorithms, we extended the Brazilian wines to 32 samples and reduced the Chilean wines to 32. With the proposed methodology, it was possible to classify the origin of the wine with an accuracy of 89% when using the 20 original elements. An accuracy of 83% was found using only 5 elements (L, DPPH, delph-3-acetylglu, peon-3-(coum)glu, and pet-3-acetylglu). Our methodology can be used for origin certification of other wines.
Using Cluster Analysis and ICP‐MS to Identify Groups of Ecstasy Tablets in Sao Paulo State, Brazil
The variations found in the elemental composition in ecstasy samples result in spectral profiles with useful information for data analysis, and cluster analysis of these profiles can help uncover different categories of the drug. We provide a cluster analysis of ecstasy tablets based on their elemental composition. Twenty‐five elements were determined by ICP‐MS in tablets apprehended by Sao Paulo's State Police, Brazil. We employ the K‐means clustering algorithm along with C4.5 decision tree to help us interpret the clustering results. We found a better number of two clusters within the data, which can refer to the approximated number of sources of the drug which supply the cities of seizures. The C4.5 model was capable of differentiating the ecstasy samples from the two clusters with high prediction accuracy using the leave‐one‐out cross‐validation. The model used only Nd, Ni, and Pb concentration values in the classification of the samples.
Production of xylanase by Aspergillus awamori on complex medium in stirred tank and airlift tower loop reactors
Abstract Aspergillus awamori was cultivated on complex medium containing wheat bran as sole carbon source in the precultures as well as in the main cultures in stirred tank and airlift tower loop reactors. The decomposition of the wheat bran particles by α -amylase and xylanase produced by the fungus was investigated by monitoring the enzyme activities, the CO 2 production rate, the concentrations of reducing sugars, glucose, xylose, phosphate and ammonium as well as by applying transmission electron microscopy. By applying synthetic medium in the preculture, the time lag was longer, the growth faster, the xylanase activity higher in the main culture, than by using wheat bran in the preculture. With increasing the stirrer speed the intimate contact between the pellets and the wheat bran was reduced, which caused a decrease of the growth and the xylanase production. By applying ground wheat bran, filamentous mycelium was formed, the growth and the substrate uptake rates increased, but the xylanase production decreased due to the less intimate contact between the fungus and the wheat bran. In the airlift tower loop reactor filamentous mycelium was formed due to the low specific power input. In spite of the high medium viscosity, high xylanase productivity was obtained. With ground wheat bran the particles were completely covered by filamentous mycelium, medium viscosity strongly increased and as consequence the growth and xylanase production decreased.