Ageing characterization of Balsamic Vinegar of Modena (BVM) and Traditional Balsamic Vinegar of Modena (TBVM) by the combined use of Nuclear Magnetic Resonance spectroscopy (NMR) and multivariate statistical analysis. Our database allows to differentiate BVM from TBVM samples. Moreover, within BVMs, samples with ageing <3/>3 years can be discriminated and within TBVM, samples with ageing between 12 and 25 years as well as >25 years can be discriminated.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 1 - 11 of 11
Combined use of High-Resolution Nuclear Magnetic Resonance spectroscopy (NMR) and multivariate statistical analysis for the differentiation of PDO Parmigiano Reggiano samples according to ripening and for the differentiation of PDO Parmigiano Reggiano from “Grana type” products available on the market.
Digital Eye is an innovative, rapid and high-precision intelligent computer vision system for the non-destructive and contactless evaluation of quality and shelf-life of whole or fresh-cut fruit and vegetables. It integrates advanced vision and artificial intelligence technologies to estimate parameters useful to evaluate the quality of fruit and vegetables, during both the harvesting phase and the cold chain.
The insertion of executable programs within QR codes is a new enabling technology for many application contexts in everyday life. Every time Internet access is unavailable, QR code usage is limited to reading the data it contains without any possibility of interaction.
VisLab laboratory of IMM possesses a latest generation Raman micro-spectroscope equipped for vibrational measurements with high spatial and spectral resolution, at controlled temperature and in fast-imaging. The apparatus can be used to collect information and chemico-physical maps without the need for sample preparation and alteration, therefore for non-destructive studies and in operating conditions.
Characterization of authenticity of honey by the combined use of high resolution Nuclear Magnetic Resonance spectroscopy (NMR) and multivariate statistical analysis. Particularly, based on our database, different characterization involving authentication assessment, like botanical or geographical origin determination are possible. Moreover, it is possible to detect saccharides addictions like inulin, corn/malt syrups, and inverted sugar. Finally, it is possible to distinguish the Italian biological honey from the conventional one.
This invention comprises an interrogation and readout differential method for chemical sensors based on Surface Plasmon Resonances (SPR). The integration of the SPR sensing unit (chip or other), as intermediate reflecting element of a Fabry-Perot (FP) optical resonator, is the starting point for the application of this method.
The environment as well as the food production provide a number of both natural and synthetic compounds whose effects on human being as an organism have not yet been determined nor investigated.
High-Resolution Nuclear Magnetic Resonace (NMR) in solution also combined with multivariate statistical analysis to determine the quality and authenticity of saffron. Particularly the content of components (metabolites) is evaluated.
To the enterprises working in the field of nutrition/nutraceutics and drug development/repositioning, we offer the know-how and state-of-the-art instrumentation of our labs to monitor multiple relevant biological parameters at the cellular level: metabolic activity, vitality, health, but also stress and toxicity. The use of advanced imaging techniques based on fluorescent/bioluminescent probes together with the availability of time-lapse acquisitions, guarantee the cutting-edge analysis of different biological parameters over time.
The software is based on mathematical models able of simulating the time evolution of the different stages of a pest population starting from environmental data collected from weather stations located in an area of interest and information regarding the development stage of the host plant. The models are of two types: phenological, which provides information on the stages population as a function of time and demographic which also allows to know the abundance of each population stage.