Fungal nanoscale metal carbonates and production of electrochemical materials

Fungal biomineralization of carbonates results in metal removal from solution or immobilization within a solid matrix. Such a system provides a promising method for removal of toxic or valuable metals from solution, such as Co, Ni, and La, with some carbonates being of nanoscale dimensions. A fungal Mn carbonate biomineralization process can be applied for the synthesis of novel electrochemical materials.</p

Vermiculite bio-barriers for Cu and Zn remediation: an eco-friendly approach for freshwater and sediments protection

The increase in heavy metal contamination in freshwater systems causes serious environmental problems in most industrialized countries, and the effort to find ecofriendly techniques for reducing water and sediment contamination is fundamental for environmental protection. Permeable barriers made of natural clays can be used as low-cost and eco-friendly materials for adsorbing heavy metals from water solution and thus reducing the sediment contamination. This study discusses the application of permeable barriers made of vermiculite clay for heavy metals remediation at the interface between water and sediments and investigates the possibility to increase their efficiency by loading the vermiculite surface with a microbial biofilm of Pseudomonas putida, which is well known to be a heavy metal accumulator. Some batch assays were performed to verify the uptake capacity of two systems and their adsorption kinetics, and the results indicated that the vermiculite bio-barrier system had a higher removal capacity than the vermiculite barrier (?34.4 and 22.8 % for Cu and Zn, respectively). Moreover, the presence of P. putida biofilm strongly contributed to fasten the kinetics of metals adsorption onto vermiculite sheets. In open-system conditions, the presence of a vermiculite barrier at the interface between water and sediment could reduce the sediment contamination up to 20 and 23 % for Cu and Zn, respectively, highlighting the efficiency of these eco-friendly materials for environmental applications. Nevertheless, the contribution of microbial biofilm in open-system setup should be optimized, and some important considerations about biofilm attachment in a continuous-flow system have been discussed.This work has been produced thanks to the collaboration of Dip.SA (University of Bologna) and IBB (University of Minho). A particular acknowledgment is due to Dr. E. Rosales. The work was partially financed by the FCT Strategic Project Pest-OE/EQB/LA0023 and the Project ‘‘BioEnv—Biotechnology and Bioengineering for a sustainable world,’’ co-funded by the Programa Operacional Regional do Norte (ON.2–O Novo Norte), QREN, FEDER

Uranium bioprecipitation mediated by yeasts utilizing organic phosphorus substrates

In this research, we have demonstrated the ability of several yeast species to mediate U(VI) biomineralization through uranium phosphate biomineral formation when utilizing an organic source of phosphorus (glycerol 2-phosphate disodium salt hydrate (C3H7Na2O6P·xH2O (G2P)) or phytic acid sodium salt hydrate (C6H18O24P6·xNa+·yH2O (PyA))) in the presence of soluble UO2(NO3)2. The formation of meta-ankoleite (K2(UO2)2(PO4)2·6(H2O)), chernikovite ((H3O)2(UO2)2(PO4)2·6(H2O)), bassetite (Fe++(UO2)2(PO4)2·8(H2O)), and uramphite ((NH4)(UO2)(PO4)·3(H2O)) on cell surfaces was confirmed by X-ray diffraction in yeasts grown in a defined liquid medium amended with uranium and an organic phosphorus source, as well as in yeasts pre-grown in organic phosphorus-containing media and then subsequently exposed to UO2(NO3)2. The resulting minerals depended on the yeast species as well as physico-chemical conditions. The results obtained in this study demonstrate that phosphatase-mediated uranium biomineralization can occur in yeasts supplied with an organic phosphate substrate as sole source of phosphorus. Further understanding of yeast interactions with uranium may be relevant to development of potential treatment methods for uranium waste and utilization of organic phosphate sources and for prediction of microbial impacts on the fate of uranium in the environment.</p

Detection, Quantification and Classification of Ripened Tomatoes: A Comparative Analysis of Image Processing and Machine Learning

In this paper, specifically for detection of ripe/unripe tomatoes with/without defects in the crop field, two distinct methods are described and compared. One is a machine learning approach, known as ‘Cascaded Object Detector’ and the other is a composition of traditional customized methods, individually known as ‘Colour Transformation’, ‘Colour Segmentation’ and ‘Circular Hough Transformation’. The (Viola Jones) Cascaded Object Detector generates ‘histogram of oriented gradient’ (HOG) features to detect tomatoes. For ripeness checking, the RGB mean is calculated with a set of rules. However, for traditional methods, color thresholding is applied to detect tomatoes either from a natural or solid background and RGB colour is adjusted to identify ripened tomatoes. In this work, Colour Segmentation is applied in the detection of tomatoes with defects, which has not previously been applied under machine learning techniques. The function modules of this algorithm are fed formatted images, captured by a camera mounted on a mobile robot. This robot was designed, built and operated in a tomato field to identify and quantify both green and ripened tomatoes as well as to detect damaged/blemished ones. This algorithm is shown to be optimally feasible for any micro-controller based miniature electronic devices in terms of its run time complexity of O(n3) for traditional method in best and average cases. Comparisons show that the accuracy of the machine learning method is 95%, better than that of the Colour Segmentation Method using MATLAB. This result is potentially significant for farmers in crop fields to identify the condition of tomatoes quickly