Produzione scientifica CNR-ISMN:

Grasso, G., Cocco, G., Zane, D., Frazzoli, C., Dragone, R. (2022). Microalgae-Based Fluorimetric Bioassays for Studying Interferences on Photosynthesis Induced by Environmentally Relevant Concentrations of the Herbicide Diuron. Biosensors, 12 (2), 67.

Dragone, R., Grasso, G., Frazzoli, C. (2020). Amperometric Cytosensor for Studying Mitochondrial Interferences Induced by Plasticizers Bisphenol B and Bisphenol A. Molecules, 25(21), 5185.

Grasso, G., Caracciolo, L., Cocco, G., Frazzoli, C., Dragone, R. (2018). Towards simazine monitoring in agro-zootechnical productions: A yeast cell bioprobe for real samples screening. Biosensors, 8(4), 112.

Kalunke, R. M., Grasso, G., D’Ovidio, R., Dragone, R., Frazzoli, C. (2018). Detection of ciprofloxacin residues in cow milk: a novel and rapid optical β-galactosidase-based screening assay. Microchemical Journal, 136, 128-132.

Dragone, R., Cheng, R., Grasso, G., Frazzoli, C. (2015). Diuron in water: Functional toxicity and intracellular detoxification patterns of active concentrations assayed in tandem by a yeast-based probe. International Journal of Environmental Research and Public Health, 12(4), 3731-3740.

Dragone, R., Frazzoli, C., Grasso, G., Rossi, G. (2014). Sensor with intact or modified yeast cells as rapid device for toxicological test of chemicals. J. Agric. Chem. Environ., 3(02), 35.


Dragone, R., Frazzoli, C., Monacelli, F. (2015). Chemical-physical sensing device for chemical-toxicological diagnostics in real matrices (Snoop). EU Patent, EP2697628 B1.

Produzione scientifica UTOV:

De Santis, D., Del Frate, F., Schiavon, G. (2022). Analysis of Climate Change Effects on Surface Temperature in Central-Italy Lakes Using Satellite Data Time-Series. Remote Sens., 14, 117.

Duca, R., Del Frate, F. (2008). Hyperspectral and Multi-Angle CHRIS Proba Images for the generation of land cover maps.  IEEE Transactions on Geoscience and Remote Sensing, vol. 46, n. 10, pp. 2857-2866.

Licciardi, G., Del Frate, F. (2011). Pixel unmixing in hyperspectral data by means of neural networks,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, n. 11, pp. 4163-4172.

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