Introduction
============

The number of nuclear plants in the world, either in or out of service, is growing and many of them are built with obsolete technology and are becoming older and older [@ref1]. Therefore some release of radionuclides into the environment can be expected in the future.

For this reason, the average (informed) citizen and big organizations could both be interested in innovative and simple methods to check the radiological safety of the local environment and of commodities, starting from foods. Traditional methods require special expertise with expensive and heavy devices and for this reason they are not very popular and only specialized organizations can afford them. On the other hand, if detecting radioactivity were as simple and cheap as measuring atmospheric pressure or body temperature, it could raise a great interest especially in our networked society and particularly during a radiological emergency.

In recent years, an astounding availability of portable and wearable [@ref2] sensors has flooded the consumer market, as an effect of the explosion of the smartphone market.

Almost anyone can currently monitor georeferenced environmental parameters and can find out and share their measurements in real time [@ref3].

The parameters that can be more easily measured by a smartphone and the appropriate apps installed and running are: local magnetic field (Intensity and direction), visible light (intensity and composition in terms of three-component colorimetric measurement), sound (level and spectrum), atmospheric pressure, atmospheric humidity, latitude, longitude, speed, acceleration, local gravity. In the same way it is well known that almost everyone can take and share in real time georeferenced photos, videos and sound recordings.

It is less widely known that with the same hardware (a smartphone with a built-in camera) and the appropriate software, anyone can monitor radioactivity and measure its intensity, although with sensitivity limitations [@ref4]^,^[@ref5]^,^[@ref6]^,^[@ref14].

In this work, three methods for radioactivity detection and measurement in commodities and in the environment are briefly compared and discussed. They are different in technology, sensitivity, resolution, and cost.

A method that is very recent relies on the current smartphone technology, with no need for additional hardware, which makes it cheap and widely available. It could be valuable for a wide screening activity and for the production, spreading and sharing of information [@ref7]. The aim of this work is to verify its putative usefulness in the field.

The two other methods are well known in the specialized laboratory and depend on specialized instruments. They were adopted here as a reference to evaluate the usefulness of the method based on the smartphone technology.

Methods
=======

**The Reference Sources**

To test and calibrate the detectors adopted in this work, a reference standard, characterized by a weak and safe (NRC/IAEA/EU exempt quantity) but clearly detectable gamma ray emission, was needed. A set of eight factory-calibrated point sources was chosen: the RSS8UN set by [Spectrum Techniques, LLC](http://www.spectrumtechniques.com/)., including Ba-133 (t~1⁄2~ = 10 year), Cd-109 (t~1⁄2~ = 462.6 day), Co-57 (t~1⁄2~ = 271 day), Co-60 (t~1⁄2~ = 5.27 year), Mn-54 (t~1⁄2~ = 312 day), Na-22 (t~1⁄2~ = 2.6 year) and Zn-65 (t~1⁄2~ = 244 day) at 3.7×10^4^ Bq on May 2015, Cd-109 (t~1⁄2~ = 463 day) and Na-22 (t~1⁄2~ = 2.6 year) at 3.7×10^4^ Bq on Apr 2015 and Cs-137 (t~1⁄2~ = 30 year) at 3.7×10^3^ Bq on Apr 2015.

**The Instruments**

The first kind of detector adopted was based on smartphone technology.

Three common models were tested. They were equipped with a specialized app: \"RadioactivityCounter\" [@ref4]^,^[@ref8] (<http://www.hotray-info.de/>). The app is available for Android and iOS systems.

The adopted models were Samsung S4, Samsung S7 and Samsung A3.

The S4 is equipped with a 4.4x3.4=15 mm^2^ sensor (resolution 4128 x 3096 = 12780288 pixel), the S7 is equipped with a 4.2x3.1=13 mm^2^ sensor (resolution 4032 x 3024=12192768 pixel), the A3 is equipped with a 3.6x2.7=9.7 mm^2^ sensor (resolution 3264 x 2448 = 7990272 pixels).

CCD or CMOS chips, used as digital image sensors in surveillance or in smartphone cameras, are sensitive not only to visible light but also to higher energy photons. The software analyzes the signals produced by the front or by the rear camera of the smartphone, which has been previously shielded from visible light by an alluminium foil, subtracts the thermal noise and estimates the gamma-ray exposure of the sensor. Furthermore the background emission (measured before) can be subtracted.

The second kind of detector was the Geiger counter PRD 100 (<http://www.prd100.com/>), made by ITS srl. This device is equipped with a Geiger-Müller tube of 111 mm length x 11 mm diameter (max. section 1221 mm^2^), which is small enough to allow full portability but whose section is much larger (82 times) than the section of the largest smartphone sensor (15 mm^2^).

This detector shows additional interesting features: it is cheap (around 100 €), it is small and easily portable (190 g, 123 mm x 91 mm x 35 mm) it works with rechargeable standard batteries (3 AA), it can work in stand-alone mode and/or connected with a smartphone via a Bluetooth radio interface.

A dedicated app ([Marie pro PRD-100](https://play.google.com/store/apps/details?id=it.ipom.marieprd100&hl=en)) running on the smartphone provides some essential real time radiation counting and data displaying, saving, sharing and geo-referencing.

The third kind of instrument chosen in this work was a 1024 channel NaI(Tl) gamma spectrometer made by [Ortec](http://www.ortec-online.com/Products-Solutions/Radiation-Food-Monitoring-Food-Screening.aspx), priced around 18000 €.

The system hardware consists of a thallium-doped sodium iodide detector enclosed in a low-background lead shield (30 mm thick), an analog-to-digital converter (ORTEC DigiBase) integrated in an all-in-one spectrometer, and a laptop PC. The digiBASE supplies the multi-channel analyzer function, the high voltage for the NaI(Tl) detector, and all the signal processing electronics. The internal stabilization electronics and the internal check source (K-40 4500 Bq/kg) allow the system to be used over a wide range of environmental conditions. However it can be hardly defined portable, if the 80 kg lead shield is taken into consideration. The NaI(Tl) crystal is a 76.2 mm height x 76.2 mm diameter (3" x 3") standard. The digiBase is connected to the control computer via a USB interface, which powers the whole system.

Several proprietary software components control the instrument, from the first setting to the final analysis. Ortec MCB Connections-32 acts as a first-level connection driver for the DigiBase. Maestro-32 MCA Emulation Software provides the second-level control of the DigiBase, the live spectral display and the automatic control of acquisition and analysis. This is achieved via a graphical user-programmable interface or via pre-programmed job streams. The software provides also data and results printing and storage. NuclideNavigator is an interactive gamma-ray reference and library program to view, query, and extract gamma-ray energies and yields, half-lives and parent/daughter relations from databases. It can be used to build application libraries or working libraries. ScintiVision-32 is an integrated multi-channel analyzer (MCA) emulator and gamma-spectrum analysis program. It integrates Maestro-32 functions and manages the collection and analysis of gamma-ray spectra. It includes commands that allow you to edit nuclide libraries and automated command sequences or "job streams."

The set of technologies described regarding gamma-spectroscopy with sodium iodide scintillator allows the identification and quantitative determination of gamma ray emitting radioisotopes, either natural ones such as K-40, U-238, Th-232 or anthropic ones such as Cs-137 and I-131 [@ref9], single or in simple mixture [@ref10].

A fourth method must be cited, though it was not experienced in this work, because it represents the state-of-the art in gamma-ray spectroscopy. It is based on High Purity Germanium (HPGe) detectors and can give excellent gamma signal resolution in the whole spectral window, even for energies as low as 3 keV, where NaI(Tl) detectors cannot usefully work and gives a resolution 16 times better than NaI(Tl). The major drawback of germanium detectors is that they must be cooled to liquid nitrogen temperature to produce spectroscopic data. An HPGe system is more complex to manage and on average is priced five to ten times as much as a NaI(Tl) system.

**The radon issue**

The Radon is a ubiquitous gas, mainly derived from the natural U-238 decay chain.

Radon isotopes emit alpha particles but some radionuclides from Radon\'s progeny (Pb-214, Bi-214) emit gamma rays and can add their signals to the spectrum of a sample. To address this problem an independent Radon sensor was adopted to estimate the radon concentration during the analyses by the NaI(Tl) system.

The sensor adopted is the Rstone by [Rsens](http://www.rsens.it/en/). It can be connected to a computer by a proprietary USB pen. A proprietary program can read and analyze the data stored in the sensor\'s memory. The sensor itself runs on a battery whose charge can guarantee up to two weeks of continuous autonomy and monitoring, and has a display to check the current Radon concentration measured during the last 30\'.

**The Background management**

With the "RadioactivityCounter" app running on a smartphone, the sensor noise and the background emission can be measured and stored in the memory, and can be subtracted from each sample measure. Measures are expressed in CPM and saved as total and by-minute counts, together with the sensor temperature (that can affect the measure).

No background compensation is provided by the PRD-100 Geiger counter and by the corresponding Marie PRO PRD-100 app running on a smartphone connected to the instrument. The counting is only instantaneous.

The NaI(Tl) gamma spectroscopy systems allow full control of the background.

The instrument is protected by a lead shield that effectively prevents the variable environmental background radiation from hitting the sensor. The shield itself is a source of radiation mainly from U-238, and Th-232 decay series; anyway this radiation is constant (except for the environmental radon contribution) and can be measured and subtracted with high reliability and precision, acquiring "blank" spectra periodically. The K-40 internal standard can also be included in the background. Therefore a spectrum of the background and of the internal standard was acquired for 963933 s, checking for its stability (on the Energy axis) and saving the result every 1800 s. The stability was assessed by continuously keeping the laboratory temperature as close as possible to 295K and monitoring the stabilizer of the instrument, locked to the K-40 peak: if some adjustment occurred, then the corresponding 1800 s set of data were discarded. This way, the centroid of the photopeak of the K-40 at 1461 keV was always kept corresponding to the channel 552.20+/- 0.20.

**The Calibration of the NaI(Tl) system**

The spectrum described above, was used either for the background subtraction or for the first calibration step [@ref11] and all the following spectra were acquired with the constraint of the K-40 centroid corresponding to channel 552.20 +/-0.20.

The energy calibration of the NaI(Tl) system was done in several steps. For a first energy calibration the K-40 peak (4518 Bq) was considered with some clearly recognizable peak of the background: the Tl-208 peak at 2614 keV, near the high energy end of the spectral window , from the Th-232 decay chain, which is widely used as a gamma tracer of natural thorium [@ref12]^,^[@ref13] and the Bi-214 peak at 1765 keV which is widely used as a gamma tracer of natural uranium [@ref12]^,^[@ref13].

During the second step the energy calibration was refined by considering, from the same background spectrum, the Ac-228 peak at 969 keV, the Tl-208 peak at 511 keV and the Pb-212 at 239 keV from the Th-232 decay chain.

For the final energy calibration steps, three reference sources were chosen and their corresponding spectra were acquired: Ba-133 (53 and 81 keV peaks), Cd-109 (88 keV peak) and Cs-137 (662 keV peak). The spectrum of each source was acquired separately, for 66691 s (Ba-133 and K-40), for 14189 s (Cd-109 and K-40) and for 81453 s (Cs-137 and K-40). The three point sources were acquired without any correction for the geometry, at 75mm from the detector surface, to lower the intensity of their signals and make it possible for the stabilizer to work properly.

The final calibration is reported below, where "Channel" is the integer index of the channel ranging from 0 to 1023:

Energy = -7.7883 +2.568091\*Channel +0.000165948\*Channel^2^

The full width at half maximum (FWHM) was calibrated as a linear function of energy:

FWHM = 4.8213 +0.038887\*Channel

The Efficiency was factory-calibrated.

**The test of smartphone sensitivity**

The rear (main) camera of each smartphone was shielded from light using a piece of aluminium foil. The "Radiation Counter" app was loaded and launched and the shielding effectiveness was verified by assessing that the background remained unchanged also putting the shielded lens near a strong light lamp. The activity of the Na-22, Zn-65 and Cs-137 sources were measured putting them at 75, 30, 15, 5, 0 mm from the lens\' surface of the rear camera of each smartphone for more than 1200 s.

The Background was checked by putting the radioactive sources at a distance greater than 4m.

The same protocol was followed with the Geiger counter, referring the distances listed above to the instrument surface that directly covered the Geiger-Müller tube.

Results
=======

In the laboratory where the NaI(Tl) spectrometer works and where the radiation counters were tested, the radon concentration varied between 20 and 60 Bq/m^3^ during the testing periods and at this level did not require any special attention. The main environmental problem was to keep the temperature stable to have the NaI(Tl) spectrometer stable as well.

Only the strongest radioactive reference source (Na-22) could induce a response that was clearly different from the background in all the counters, smartphones included, as reported in [Fig. 1](#figure1){ref-type="fig"} and in [Tab. 1](#table1){ref-type="fig"}. [Figure 1](#figure1){ref-type="fig"} and [Table 1](#table1){ref-type="fig"} show graphically ([Fig 1](#figure1){ref-type="fig"}) and in tabular format ([Tab. 1](#table1){ref-type="fig"}) the measures obtained from each counter, at different distances from the Na-22 reference source.

Graph showing the relationship between counts and distance, for each counter, from the Na-22 reference source.The Graph shows the Counts Per Minute (CPM) of the four tested radiation counters and of the NaI(Tl) spectrometer, put at different distances from Na-22 reference source of gamma rays. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}.Na-22_DevicesVsDistance05

**Table 1:** The Table shows the output, expressed in CPM (Counts Per Minute) of the tested radiation counters and of the tested NaI(Tl) spectrometer, put at different distances from three different reference sources of gamma rays. For the NaI(Tl) spectrometer, the counts from the whole spectral windows were considered and the output adjusted for the half-life of the nuclides and for the different acquisition date.201705011608AlessandriTab01

The NaI(Tl) sensor showed a very different sensitivity.

For the sake of comparison, the photo-peak of the reference source of Cs-137 (3700 Bq), put on the surface of the NaI(Tl) sensor (18200 mm^2^) gave a count of 1.31\*10^4^ CPM and was "viewed" by the spectrometer as a 1L sample containing 7262 Bq/kg of Cs-137 ([Fig. 2](#figure2){ref-type="fig"}). This kind of instrument easily recognizes contents as low as the Tl-208 of the background, "viewed" as a concentration of 19.4 Bq/kg and whose photo-peak area corresponds to 6.60\*10^-2^ CPM ([Fig. 2](#figure2){ref-type="fig"}

Gamma-ray spectrum of the Cs-137 reference sourceOutput of the NaI(Tl) Gamma-ray spectrometer. The point source of Cs-137 (t1⁄2 = 30 year, 3.7×103 Bq on Apr 2015, photo-peak 662 keV) was placed on the sensor surface. Also the photo-peaks at 2614 keV (Tl-208 from the Lead shield) and at 1461 keV (K-40 internal standard) can be clearly observed.Cs137_NaI(Tl)\_SpectrumSensor Surface_04

The same reference source of Cs-137 ([Fig 3](#figure3){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}) was not sensed by the S7 and was hardly sensed by the A3 and only within a distance equal or less than 5 mm. Only the S4 performed reliably.

Graph showing the relationship between counts and distance, for each counter, from the Cs-137 reference source.The Graph shows the Counts Per Minute (CPM) of the four tested radiation counters and of the NaI(Tl) spectrometer, placed at different distances from Cs-137 reference source of gamma rays. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}.Cs-137_DevicesVsDistance04

The Zn-65 reference source ([Fig. 4](#figure4){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}) showed intermediate counts between the strongest (Na-22) and the weakest source (Cs-137).

Graph showing the relationship between counts and distance, for each counter, from the Zn-65 reference source.The Graph shows the Counts Per Minute (CPM) of the four tested radiation counters and of the NaI(Tl) spectrometer, placed at different distances from Zn-65 reference source of gamma rays. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}.Zn-65_DevicesVsDistance04

The three smartphones performed very differently. The most recent one (Samsung S7), which is equipped with the most advanced (and small) sensor showed too much background thermal noise and was not able to sense the reference sources ([Fig. 5](#figure5){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}) , except for the strongest (Na-22) at the minimum distance. On the other hand, only the S7, running under Android 6 (the A3 and the S4 runs under Android 5) showed no problem with file saving.

Graph showing the response of the S7 smartphone to the different reference sources at the different distances.The Graph shows the Counts Per Minute (CPM) of the three tested radiation sources placed at different distances from the S7 surface. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}. The residual background level is also reported.S7_NuclidesVsDistance04

Among the tested smartphones the most reliable was the S4 which showed a good sensitivity and whose counts followed the expected trend ([Fig. 6](#figure6){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}). The A3 showed less sensitivity and performed worse ([Fig. 7](#figure7){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}).

Graph showing the response of the S4 smartphone to the different reference sources at the different distances.The Graph shows the Counts Per Minute (CPM) of the three tested radiation sources placed at different distances from the S4 surface. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}. The residual background level is also reported.S4_NuclidesVsDistance04

Graph showing the response of the A3 smartphone to the different reference sources at the different distances.The Graph shows the Counts Per Minute (CPM) of the three tested radiation sources placed at different distances from the A3 surface. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}. The residual background level is also reported.A3_NuclidesVsDistance04

The Geiger counter PRD100 ([Fig. 8](#figure8){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}) showed a much higher (one order of magnitude) sensitivity of the best performing smartphone (S4) but the software running on the connected smartphone lacks some useful feature which is present in the \"RadiationCounter\" app. (that is to say data-saving in CSV standard format, a count every 60 s, temperature and battery status and, for each measuring session, total duration, background, noise related to the border of the sensor). Furthermore the app allows real-time background subtraction, 60 s to 1800 s means and general mean calculation.

Graph showing the response of the PRD100 Geiger counter to the different reference sources at the different distances.The Graph shows the Counts Per Minute (CPM) of the three tested radiation sources placed at different distances from the PRD100 surface. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}. The residual background level is also reported.PRD100_NuclidesVsDistance04

The NaI(Tl) spectrometer showed (as expected) the best sensitivity ([Fig. 9](#figure9){ref-type="fig"} and [Tab. 1](#table1){ref-type="fig"}) and the highest reliability with the best background management.

Graph showing the response of the NaI(Tl) spectrometer to the different reference sources at the different distances.The Graph shows the Counts Per Minute (CPM) of the three tested radiation sources put at different distances from the surface of the sensor of the NaI(Tl) gamma spectrometer. The total counts from the whole spectral window are considered to allow a proper comparison with the other devices. The numerical values are reported in [Tab. 1](#table1){ref-type="fig"}. The background is not reported here because it depends on the K-40 internal standard and on the lead shield, not on the external environment and it can be evaluated observing the spectrum reported in [Fig. 2](#figure2){ref-type="fig"}.NaI(Tl)\_NuclidesVsDistance04

Discussion
==========

The current smartphone technology could open up to a massive radiation monitoring, with some limitations due to low sensitivity, where the number of data could compensate for the possible lack of precision and puts in the hands of the average citizen a direct knowledge that previously only specialized entities could access.

Furthermore, the fact that anyone can check for the safety of the nearby environment leads to a new kind of bottom-up control of the information released by interested stake-holders and by the public authorities, allowing more transparent decision making.

According to the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) the worldwide average natural dose to humans is about 2.4 mSv/y (millisievert per year) [@ref15].

On the other hand, the International Commission on Radiological Protection (ICRP) recommends effective dose limits to reduce the risk of stochastic effects to tolerable levels [@ref16] for members of the general public in planned exposure situations and proposes as first reference level 1 mSv/y. The Commission considers also existing exposure situations that are defined as \"those that already exist when a decision on control has to be taken\" and explains that \"there are many types of existing exposure situations that may cause exposures high enough to warrant radiological protective actions, or at least their consideration\". The Commission proposes the reference interval between 1 and 20 mSv/y for these conditions that can be due to NORM (Naturally Occurring Radioactive Material), natural background radiation and radioactive residues within the human habitat. The Commission defines also the levels between 20 mSv/y to 100 mSv/y as \"reference levels for the highest planned residual doses in emergency situations\". Therefore according to UNSCEAR and ICRP, an annual dose ten times the \"worldwide average natural dose to humans\" is already an emergency.

According to our data, at least one of the tested smartphone (S4) is able to reliably distinguish between a residual background of 0.2 CPM and a tenfold greater gamma emission ([Tab. 1](#table1){ref-type="fig"} and [Fig. 6](#figure6){ref-type="fig"}). The cited background can be assumed to be near the average value, according to UNSCEAR\'s definition and according to the information available on the geographic area where the tests were done: the alluvial plain of Florence-Prato-Pistoia [@ref17]^,^[@ref18]. Therefore, in such conditions, the device could be used to detect an environmental radiation level that could signal a radiological emergency, according to ICRP\'s definition [@ref16]. On the other hand, no real-time detection can be expected in low exposure conditions because to achieve the reported results, several minutes were needed for each measure and all the measured counts, except the S4 measure of the Na-22 put directly on the smartphone surface (99.6 CPM) are less than one count per second. If we consider that one count per second is equal to 60 CPM that in turn, in this case, corresponds to 300 times the residual background, then it can be concluded that only high levels of gamma activity can be detected in real-time by this kind of device and that the low sensitivity of the small sensor of a smartphone can be a serious drawback, that could be compensated only by the adoption of an external sensor. The low sensitivity would not be a problem in a severe radiological emergency, where the usefulness of many working detectors should be unquestionable and where almost everybody could become an active node in an environmental sensory network. In this scenario the value of the information collected can only be imagined.

Of course the huge amount of environmental data that could be produced and shared needs some public revision and lab validation, and here a sensitive, traditional and inexpensive technology like the NaI(Tl) spectrometry can have a new role, before the definite Hi-Res confirmation that only the HPGe technology can give.

Corresponding Author
====================

Stefano Alessandri, Department of Statistics, Computer Science, Applications \"Giuseppe Parenti\", University of Florence, Florence, Italy. Email: stefano.alessandri\@unifi.it

Data Availability
=================

The data are freely available in [figshare](https://figshare.com/) repository and can be accessed via the following links:

\- Summary of smartphones, geiger counter and NaI(Tl) spectrometer dataset: https://doi.org/10.6084/m9.figshare.4555507.v1

\- NaI(Tl) raw dataset: https://doi.org/10.6084/m9.figshare.4644997.v1

Competing Interests
===================

The author has declared that no competing interests exist.

The Author is grateful to the "Fondazione Ente Cassa di Risparmio di Firenze" (www.entecarifirenze.it/en/home-en/) who funded this work, and to Ms. Nathalie Adams for the editing in English.

Stefano Alessandri - Curriculum Vitae et Studiorum Born in Florence, Italy, on 04/11/1953, he obtained a degree with honors in Agricultural Science and Technology in 1999 at the Faculty of Agricultural Science of the University of Florence, with a published thesis on \"The Quality and Variability of Olive Production in Tuscany\". He worked at the Horticulture Department of the University of Florence from 01/05/1975 to 09/01/1995, continuing to collaborate with it to 01/11/2002. Since July 2000, he is a qualified Doctor in Agronomy and is registered in the role list for Doctors in Agronomy and Doctors in Forestry of the Province of Florence (registration n. 944). From 1988 to 1993 he has been chosen as Teacher and Trainer by the Regional Institute for Educational Research Experimentation and Updating (IRRSAE, Istituto Regionale Ricerca, Sperimentazione Aggiornamento Educativi) of Tuscany, and has taken care of the epistemological aspects and problems concerning the definition and transmission of educative contents for scientific subjects within learning groups as teacher and coordinator; particularly for the training of teachers of Primary School and in the fields of Experimental Methodology, Plant Biology and Experimental Physics, making interventions in the fields of Chemistry, Earth Science and Animal Biology as well. He has been chosen as Expert in statistical elaboration of analytical data concerning olive oil quality in the Region of Tuscany, since 25/02/2000, in the Regional Project for the Improvement of the Quality of Olive Oil. He is Associate Faculty Member of the Center for Magnetic Resonance (CERM) of the University of Florence, since 24/09/2002. Since 01/11/2002 he serves as Senior Researcher (CHIM03 area) at the Dept. of Agricultural Biotechnology of the University of Florence. Since 16/02/2004 to November 2010 he has been member of the board of teachers of the International Doctorate in Structural Biology, that is held at CERM. Since 01/11/2012 belongs to the sector: SECS-P/13 Commodity Science, Concorsual sector: 13/B5. Since 01/01/2013 serves at Dipartimento: Statistica, Informatica, Applicazioni \"G. Parenti\" - DiSIA of Florence. Since 2016 is member of the Italian Commodity Science Academy (AISME). Since the Academic Year 2007/2008 to the Academic Year 2012/2013 holds the course of \"General and Inorganic Chemistry\" of the first degree course \"Plant Production Science and Environment Management\" of the Faculty of Agriculture of Florence. Since the Academic Year 2012/2013 he is holding part of the course of \"NEW TECHNOLOGIES AND ENVIRONMENTAL CHEMISTRY\", in English, of the second degree course \"DESIGN OF SUSTAINABLE TOURISM SYSTEMS\". He works on the quality, characterization and safety of agriculture and food products, especially typical products. In particular does research work on the application of multivariate statistical techniques on analytical data and the setting of classification models to recognize the origin of products. He works on structural characterization and authentication of food allergens by high resolution NMR and on characterisation of food products by high resolution NMR and low resolution Gamma-ray spectrometry. He was or is involved in the following Research Projects as Principal Investigator (or Co-investigator if a different P.I. or Coordinator is specified): 2003-2005 The Role of metal ions in metabolic processes; funded by MIUR (Italian Ministery for Instruction, University and Research) as PRIN (Italian Research Program of Relevant National Interest), Coordinator I. Bertini -- Cerm (Research Centre of Magnetic Rsonances; University of Florence). 2005-2009 Involvement as Cerm (Research Centre of Magnetic Rsonances; University of Florence) investigator and representative, with Prof. C. Luchinat as P.I. - EUROPREVALL (The prevalence, cost and basis of food allergy across Europe; http://cordis.europa.eu/result/rcn/51771_en.html) EU-Funded (FP6-FOOD, 14 329 838 €) multidisciplinary integrated project (IP) involving 17 European member-states, Switzerland, Iceland, and Ghana and 67 partners, among them 15 clinical organisations, 6 small-medium sized enterprises (SMEs) and the leading allergy research organisations in EU) The main objective of the EUROPREVALL project was to examine the complex interactions between food intake and metabolism, immune system, genetic background and socioeconomic factors to identify key risk factors and develop common European databases. Over the course of four years and seven months it has delivered the information and tools necessary for policymakers, regulators and the food industry to effectively manage food allergies across Europe and hence deliver an improved quality of life to food allergic consumers. 2006 Discovering and purification of biochemical and molecular markers of host-pathogen interaction for molecular phyto-diagnostic and non-conventional phytopharmacology; funded by DIBA (Department of Agricultural Biotechnology) and by University of Florence; P.I. Prof. Tegli S. 2006-2008 Structural Genomics strutturale of metallo-proteins and their functional interactions funded by MIUR (Italian Ministery for Instruction, University and Research) as PRIN (Italian Research Program of Relevant National Interest), Coordinator I. Bertini -- Cerm (Research Centre of Magnetic Rsonances; University of Florence). 2008 Structural Authentication of macro-molecules of agri-food interest; funded by DIBA (Department of Agricultural Biotechnology) and by University of Florence. 2008-2010 Natural Extract from Medical, Textile and Coloring Plants; Chemical Technological and Biological Characterization of Common Nettle (Urtica dioica), Laurel (Daphne sp.), Lavender (Lavandula angustifolia), Chestnut (Castanea sativa) funded by MIUR (Italian Ministery for Instruction, University and Research) as PRIN (Italian Research Program of Relevant National Interest), Coordinator A. Romani, DISIA (Department of Statistics, Computer Science, Applications; University of Florence). 2009--2012 Authentication and Structural Analysis of macro-molecules of agri-food interest; funded by DIBA (Department of Agricultural Biotechnology) and by University of Florence. 2013-2014 Chemometrical and Structural Authentication of Food Allergens, Olive (Olea europaea) Oil and Saffron (Crocus sativus); funded by DISIA (Department of Statistics, Computer Science, Applications) and by the University of Florence. 2014 Gamma Spectrometry: Traceability, Quality, Safety funded by the fundation "Ente Cassa di Risparmio di Firenze". 2015 Methods and Standards for a Diffused and Cheap Radio-isotopical Characterization,of Agri-food Products, and By-products ; funded by DISIA (Department of Statistics, Computer Science, Applications) and by the University of Florence. 2016 "Structural Authentication and Interactions of Food Allergens (Autenticazione ed interazioni strutturali diallergeni alimentari)". In Colaboration with the Medical University di Vienna (Prof K. Hoffmann-Sommergruber and Dr. P. Dubiela); funded by DISIA (Department of Statistics, Computer Science, Applications) and by the University of Florence. He has held and holds courses, seminars and workshps for the following organizations: - Horticulture Department of the University of Florence - Consortium for Irrigation Techniques (CO.T.IT.) in Scerni (Pescara) - Regional Administration of Tuscany - Regional Agency for the Development and Innovation in Agriculture and Forestry(ARSIA) of Tuscany - Chamber of Commerce (Unioncamere) of Tuscany - International Olive Oil Council (COI) - Italian National Research Council (CNR) - Faculty of Agricultural Science and Technology of the University of Florence - Tuscan Pediatric Cultural Association (ACP Toscana) - Faculty of Agricultural Science of the University of Parma. - School (fromerly Faculty) of Economy of the University of Florence The subjects of courses, seminars and workshops are: - Food quality. Particularly in oils coming from the processing of olives - General and Inorganic Chemistry - New Technologies and Environmental Chemistry - Applied Statistics, Biometry and Chemiometry especially about classification models - Experimental Methodology and computer aided techniques for acquisition and validation of experimental data - Information Technology - Communication Technologies for the finding, access, use and sharing of information (particularly scientific) on local and remote data bases He attended the workshops, seminars, round tables and courses listed in the following. 1.Information and Communication Technology - Course on FORTRAN language, organized by the National University Center of Electronic Calculus (CNUCE) at the Faculty of Agricultural Science in Florence (12-28/11/1975). - Course on PROLOG language in Bologna at Inter-university Consortium (CINECA; 22-29/09/ 1988). - Seminar on \"On-Line Research\" at CINECA in Bologna (29-30/11/1988) - Introductive course on Data Transmission \"Network services for scientific research in Italy\" organized by the CNUCE Institute and by the Research Consortium of Pisa (15-17/03/1989). 2. Statistics and Experimental Methodology - Metrology course held at the IATA Institute at the Faculty of Agricultural Science in Florence in 1985. - Base course on Statistical analysis of experimental measures in Biology held by Prof. Salvi at the Department of Pre-clinical and Clinical Pharmacology at the University of Florence in October 1986. - Course on \"Regression Analysis\" held at the Statistics Laboratory of the Department of Statistics in Florence 21-22/12/1989. - Seminar on \"Chemiometry: a new instrument to manage the quality of the environment and food\", organized by the UICI, held in Perugia 03-04/12/1991. 3. Food Quality (particularly in oils coming from the processing of olives) - International seminar on \"The Scientific innovations and their application in Olive Tree Growing and olive oil processing\" organized by the Accademia dei Georgofili and the International Olive Oil Council in Florence on 10-11-12/03/1999. - Round table \"The new European regulation on the denomination of origin of olive oil: towards the breaking of the productive chain ?\" Accademia dei Georgofili; Florence 12/03/1999. - Round table \"Productive Chain Traceability. Law impositions and competitive opportunities for agriculturally produced foodstuffs\" Accademia dei Georgofili; Florence 05/06/2000. - Stage: \"Olive growing in Mediterranean countries facing origin denomination and European policies on quality\" Accademia dei Georgofili; Florence 03/10/2000. - \"BIO: for which quality of life?\" Florence, 22/11/2000; conference organized by Italian Society of Manager Women (A.I.D.D.A.), Universities of Florence and Pisa. 4. Education, Training and Epistemology - Seminar on the \"New Programs for the Primary School - Science Module\" organized by the Tuscan Regional Institute for Educational Research Experimentation and Updating (I.R.R.S.A.E.), held in Lido di Camaiore (Lu) 18-21/05/1988. - Seminar for science teaching experts organized by the Tuscan I.R.R.S.A.E. and held in Montecatini Terme 05-07/12/1988. - Seminar for Science teachers, held in Florence 04-05/05/1990, organized by the Tuscan I.R.R.S.A.E. - Seminar for P.P.A. Teachers, held in Lido di Camaiore (Lu) from 18-20/03/1991, organized by the Tuscan I.R.R.S.A.E. and by the Organization for the Professional Training of Teachers (O.P.P.I.). - Round table on the theme of \"The teacher moving towards a change\" organized by the Local Education Office of Lucca, by the I.T.G. L. Nottolini of Lucca and by the ATCF-O.P.P.I. held in Lucca 30/05/1991. - TRAINING Course for teachers in work-groups, organized and managed by the O.P.P.I. (Organization for the Professional Training of Teachers) in Milan 26 -30/08/ 1991. - Seminar: \"The educational value of subjects in educational processes. A return to the future (new prospectives in subject analysis in formative planning)\", organized by the O.P.P.I. in Milan 28-29/03/1992. - Debate meeting on the theme: \"School and Total Quality: a challenge\", organized by the I.T.C.S. Alessandro Volta in Florence on 06/05/1992. - Seminar on \"Planning research\", organized by the O.P.P.I., in Passo del Tonale (TN) 19-23/07/1992. - Seminar for Science experts (collaborators and consultants in Primary School Work-Groups) held in Montecatini Terme (PT) 14-15/12/1992 organized by the Tuscan I.R.R.S.A.E. - Seminar \"A debated comparison of Education associations. Education strategies: the contribution of subjects to Education processes\", organized by the O.P.P.I. in Milan, at the organization headquarters 19-20/02/1993. - Seminar \"Introduction to the Philosophy of Science in the 20th Century - Part 1\", Fadini U.; Faculty of Agricultural Science of Florence, 08/03/1996. - Seminar \"Introduction to the Philosophy of Science in the 20th Century - Part 2\", Fadini U.; Faculty of Agricultural Science of Florence, 15/03/1996. - Seminar \"Comparison of Methodological aspects in subject fields of the Faculty of Agricultural Science (Earth Science, Biology, Economy, Ecology sectors); Zanzi A., Malevolti I., Vazzana C., Ferrari G.; Faculty of Agricultural Science of Florence, 10/05/1996. - Spugnoli, P., Vieri, M.; Facolta\' di Agraria di Firenze, 15/11/1996 Seminar \"Mechanization as configuration and control of the instrumental component in an agricultural system\" Spugnoli P., Vieri M., Faculty of Agricultural Science of Florence, 15/11/1996. - Seminar \"Parasite attacks on species of agricultural and forestal interest and the answer given by man in a systemic perspective\" Surico G., Belcari G.; Faculty of Agricultural Science of Florence, 06/12/1996. - Seminar \"Introduction to the Science Method\" Fadini U.; Faculty of Agricultural Science of Florence, 27/02/1998. - Seminar \"Genetics and Biotechnology between reductionism and the study of complex systems\" Buiatti M., Faculty of Agricultural Science of Florence, 06/03/1998. - Seminar \"Dynamics of complex systems. Instability and auto-organization\" Califano S.; Faculty of Agricultural Science of Florence, 13/03/1998. - Seminar \"Counseling and training on aid relationships\", by Dr. L. Guzzardi, organized by the Tuscan Territorial Group of the AIF, in Florence on 01/02/2000. - Seminar \"WWW.benessere,it\" (WWW.Well-being.it) by Prof. Enzo Spaltro, organized by the Tuscan Territorial Group of the AIF, in Florence on 19/05/2000. - Seminar \"The A.I.F. certification of the Teacher\'s competence\" organized by the Tuscan Territorial Group of the AIF, in Florence on 05/06/2000, and coordinated by Dr. B. Librandi. - G. A. Courtial; \"Pedagogy, the most ancient science of the Universe\", Florence 29/09/2000; Pedagogic meeting organized by the Education Council of the Commune of Florence and by the ANPE (National Association of Pedagogists). - A. Polin; \"The wound as a source of energy\" Florence 27/10/2000; Pedagogic meeting organized by the Education Council of the Commune of Florence and by the ANPE. - Del Medico, M., Bertoldi M., Serretti A., De Caro G.: \"Play in Work and Life\", Florence 3, 10, 17/11/2000; Workshop organized by the Mario Augusto Martini Study Center and the Italian Teachers Association (AIF). - R. Ciofi; \"The contribution given by professions in the field of psycho-pedagogy to the transformation towards a new society\" Florence 24/11/ 2000; Pedagogic meeting organized by the Education Council of the Commune of Florence and by the ANPE. - A. Amodei; \"Darwinian and Evolutionistic Psychology: problems concerning scientific training and communication\" Florence 15/12/2000; Pedagogic meeting organized by the Education Council of the Commune of Florence and by the ANPE. - ITOL, Institute of Training, 23-27 May 2012, Grundtvig workshop INOVATE - Implementing New Operating Changes for Valuing Adult Education and Training. (http://www.itol.eu/proiecte/inovate.html) Scopus Author ID:6603809597; h-index = 10; Citations 242 Firenze, 20/08/2016 Dr. Stefano Alessandri Via Morgiano 9 50012 ANTELLA FI E-mail: stefano.alessandri\@unifi.it
