The incidence of filamentous fungi and toxin levels in grapes and wines varies depending on the variety of grapes, the wine region, agricultural practices, weather conditions, the harvest and the winemaking process. In this sense, the objective of this study was to evaluate the diversity of Aspergillus and Penicillium fungi isolated from wine grapes of the semi-arid tropical region of Brazil, evaluate the presence of ochratoxin A (OTA) in the experimental wine and verify if there is a correlation between occurrence of these fungi and the physicochemical characteristics of the wine grapes grown in the region. For the isolation of fungi we used the direct plating technique. The presence of OTA in the experimental wine was detected by high-performance liquid chromatography. The species found were Aspergillus niger, A. carbonarius, A. aculeatus, A. niger Aggregate, A. flavus, A. sojae, Penicillium sclerotiorum, P. citrinum, P. glabrum, P. decumbens, P. solitum and P. implicatum. All isolates of A. carbonarius were OTA producers and all P. citrinum were citrinin producers. The highest concentration of OTA was found in red wine (0.29μg/L). All species identified in this study, except A. flavus, showed a positive correlation with at least one physicochemical parameter assessed, highlighting the pectin content, total sugar, total acidity and phenolic compounds.
Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.
The aim of this paper is to determine the existence of gaps in the literature, by investigating studies that statistically analyzed the relationship between sustainable development and economic performance. A literature review was conducted in the Web of Science and Scopus databases. The study analyzed the authors, publication years, journals involved, methodologies used, and results obtained. The identified gaps and opportunities were (a) opportunity to create or employ different measurements for financial, social, and environmental performance and (b) to use different kinds of control or moderating variables, in order to further explore the relationship between sustainable development and financial performance.
The genera Aspergillus comprises species that produce mycotoxins such as aflatoxins, ochratoxins and patulin. These are cosmopolitan species, natural contaminants of agricultural products. In coffee grains, the most important Aspergillus species in terms of the risk of presenting mycotoxins belong to the genera Aspergillus Section Circumdati and Section Nigri. The purpose of this study was to assess the occurrence of isolated ochratoxigenic fungi of coffee grains from organic and conventional cultivation from the South of Minas Gerais, Brazil, as well as to evaluate which farming system presents higher contamination risk by ochratoxin A (OTA) produced by fungi. Thirty samples of coffee grains (Coffea arabica L.) were analysed, being 20 of them of conventional coffee grains and 10 of them organic. The microbiological analysis was done with the Direct Plating Technique in a Dichloran Rose Bengal Chloramphenicol Agar (DRBC) media. The identification was done based on the macro and micro morphological characteristics and on the toxigenic potential with the Plug Agar technique. From the 30 samples analysed, 480 filamentous fungi of the genera Aspergillus of the Circumdati and Nigri Sections were isolated. The ochratoxigenic species identified were: Aspergillus auricoumus, A. ochraceus, A. ostianus, A. niger and A. niger Aggregate. The most frequent species which produces ochratoxin A among the isolated ones was A. ochraceus, corresponding to 89.55%. There was no significant difference regarding the presence of ochratoxigenic A. ochreceus between the conventional and organic cultivation systems, which suggests that the contamination risk is similar for both cultivation systems.
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