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Online monitoring of coffee roasting in an industrial plant is becoming an important issue as the experience of the roast master still plays an important role. Despite several approaches have been tested, some limitations were not surmountable as difficulties in scalability from bench scale to industrial roaster, the use of expensive analytical instrumentation, and the need to handle a large dataset of variables. In this paper, response of an electronic nose sampling, the headspace of roasted beans, was correlated with brightness and mean density, using the generalized least square regression in combination with a stepwise backward selection of predictors. To avoid scalability issues, roasting took place in an industrial plant using two Arabica (Brazil and Costa Rica) and two Robusta (Vietnam and India) origins. Regression showed R ranging in the interval 0.994-0.999, with statistical significance p < 0.0001. The present approach has the potential to be used effectively instead of roast master, in the online monitoring of coffee roasting in industrial plants. [ABSTRACT FROM AUTHOR]

This study investigated the temporal trends of element concentrations and ecophysiological parameters (integrity of cell membranes, membrane lipid peroxidation, and sample vitality) in thalli of the lichen Pseudevernia furfuracea transplanted in and around an industrial area of S Italy from May 2010 to May 2011, once every 3 months. Element accumulation at levels indicating that the atmosphere of the study area was polluted by most elements occurred only during the third trimester of exposure, and the ecophysiological parameter best reflecting this trend was sample vitality expressed in terms of activity of the enzyme dehydrogenase. Among the available climatological parameters, the different amount of rainfall during the exposure period may influence the results, especially the number of hours with rainfall >16 mm/day, which is the threshold between light-moderate and moderate-heavy rainfall in the Mediterranean area. [ABSTRACT FROM AUTHOR]

Five arsenic-resistant bacterial strains (designated MP1400, MP1400a, MP1400d, APSLA3, and BPSLA3) were isolated from soils collected at the Alps region (Italy), which showed no contamination by arsenic. Phylogenetic analysis of the 16S rRNA gene sequences assigned them to the genera Pseudomonas and Bacillus. Bacillus sp. strain 1400d and Pseudomonas spp. strains APSLA3 and MP1400 showed higher tolerance to As(III), as indicated by minimum inhibitory concentrations of 10 mmol/L. Pseudomonas sp. strain MP1400 exhibited higher tolerance to As(V) (minimum inhibitory concentration of 135 mmol/L). The isolated arsenic-resistant strains were able to reduce As(V) to As(III), especially Pseudomonas sp. strain MP1400 reducing 2 mmol/L of As(V) to As(III) within 24 h. The results suggest that the isolated bacterial strains play a role in the arsenic biogeochemical cycle of arsenic-poor soils in the Alps mount area. [ABSTRACT FROM AUTHOR]