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Essential oils are well known to act as biopesticides in pest management programs. The main purpose of this research is to explore the insecticidal potential (fumigant and repellent toxicity) of binary mixtures of essential oils extracted from leaves of three Mentha species namely Mentha rotundifolia, M. viridis and M. longifolia collected from north Tunisia against adults of the rice weevil Sitophilus oryzae. Gas chromatography-mass spectrometry analyses revealed quantitative and qualitative variations among oils chemical composition. Three common compounds β-pinene (0.37–1.06%), α-limonene (0.32–18.39%) and pulegone (0.54–68,057%) were detected. Results showed that when applied alone, the oils exhibited a strong gradient of toxicity with M. rotundifolia being the most effective (CL50: 7.67 μL/L air) compared to M. longifolia (CL50: 12.32 μL/L air) and M. viridis oil (CL50: 100.16 μL/L air). In essential oils binary mixtures experiments, the combination M. rotundifolia x M. viridis exhibited the strongest insecticidal activity (CL50: 8.19 μL/L air) followed by M. rotundifolia x M. longifolia (CL50: 12.49 μL/L air) and M. longifolia x M. viridis (CL50: 19.36 μL/L air). Repellent toxicity was highly dependent upon oils binary mixture and concentrations. The mixture M. longifolia x M. viridis was more effective (PR = 40% at the concentration of 0.032 μl/cm2). Overall, this work demonstrates the interest of combing essential oils as a promising alternative to control S. oryzae in storage. This work promotes operating technologies of essential oils to better guide the biopesticide industry towards a sustainable development path. [ABSTRACT FROM AUTHOR]

Natural iron oxide-coated sand (NCS), extracted from the iron ore located in North-West of Tunisia, was employed to investigate its capacity to remove copper and nickel from aqueous solutions. The aim of this work was to characterize the considered sorbent (NCS) and to assess the possibility of removing nickel and copper from aqueous solutions by this sorbent. The effects of agitation time, pH, initial metal ion concentration and temperature on the removal of these metals were studied. In order to study the sorption isotherm, two equilibrium models, the Freundlich and Langmuir isotherms, were analyzed. The effect of solution pH on the adsorption onto NCS was studied in the pH range from 2 to 7 and 2 to 9 for copper and nickel respectively. The adsorption was endothermic and the computation of the parameters, ΔH°, ΔS° and ΔG°, indicated that the interactions were thermodynamically favourable. Experiments with Cu and Ni adsorption measured together showed that Cu severely interfered with Ni adsorption to the NCS and vice versa under the conditions of the two coexisted ions adsorption. [Copyright &y& Elsevier]

Authentication of geographical origin of virgin olive oils is necessary to protect consumer and producers from frauds. A method able to classify virgin olive oils from the main worldwide producing countries is still missing. In this work, we developed 3 chemometric approaches for classification of virgin olive oils from Italy, Spain, Greece, Portugal, Tunisia and other countries all over the world. The approaches were developed starting from a data-set containing fatty acid composition and the amount of 72 volatile compounds, evaluated by a never applied HS-SPME-GC-MS quantitation method, of 1217 oil samples from three different olive oil campaign. The approach that gave the best predictive results is based on Linear Discriminant Analysis run on quantitative data from only 25 volatile compounds selected by one-way ANOVA as the most capable in discriminating between the diverse origins. The method was built and internally validated using a training-set of 1000 samples and externally validated with a test-set of 217 independent samples. The method was able to classify the geographical origin of 94.5% samples, with a percentage of correct classification even higher than 97% for some origins. Preliminary studies also suggested the proposed approach is able to correctly classify the geographical origin of binary mixtures of oils from different origins. The approach proposed in this manuscript is easily applicable in testing laboratories and represents a very useful tool for the olive oil field, helping in protecting consumers and producers from frauds. • 1217 virgin olive oils from the main producing countries analyzed by HS-SPME-GC-MS. • Three chemometric approaches for authentication of geographic origin were proposed. • The ANOVA-LDA model gave 87.3% of correct prediction only using 25 VOCs. • For some origins, the model correctly predicted more than 97% of samples. • The model correctly classifies the geographic origin of binary mixtures of VOOs. [ABSTRACT FROM AUTHOR]