Given the non-invasive and non-destructive nature, the measure- ment of the dielectric properties of agri-food products is the object of several studies. Dielectric characteristics of the material vary with moisture content, density, composition and structure, water activ- ity and can be measured with techniques which range from direct current to microwaves (Nelson 1991). Recently, a simple dielectric technique based on a resonant plate capacitor probe was set up to predict the freshness of shell eggs (Ragni et al., 2006). Inspired from biological nervous systems, artii cial neural networks (ANN) is a mathematical algorithm capable of relate input and out- put parameters by learning from example trough iterations. ANN is able to approximate any non-linear input output relationship by means of a simple structure with connections in parallel between neurons. h is computing method is widely applied in food quality evaluation especially using computer vision system (Goyache et al., 2001; Du and Sun, 2004; Du and Sun, 2006). Main applications con- cern the classii cation of cereal grains (Lou et al., 1999), fruits and vegetables (Brandon et al., 1990; Kavdir and Guyer, 2002) and meat (Chandraratne et al., 2007). h e present research attempts to evaluate the days of storage and the main freshness parameters of shell eggs on the basis of non- destructive spectroscopic dielectric analysis and artii cial neural network method. In conclusion, even if preliminary results, this work shows that dielectric spectroscopy could be used to set up a non-destructively technique able to predict the freshness of the shell eggs and it opens up new perspectives for on line applications.

Predicting freshness of shell eggs using a technique based on the dieletric properties / Berardinelli, A.; Cevoli, C.; Fabbri, A.; Giunchi, A.; Gradari, P.; Ragni, L.; Sirri, F.. - (2007). ((Intervento presentato al convegno XVIII European Symposium on the Quality of Poultry MeatXII European Symposium on the Quality of Eggs and Egg Products tenutosi a Prague nel 2-5 september 2007.

Predicting freshness of shell eggs using a technique based on the dieletric properties

A.BERARDINELLI;
2007

Abstract

Given the non-invasive and non-destructive nature, the measure- ment of the dielectric properties of agri-food products is the object of several studies. Dielectric characteristics of the material vary with moisture content, density, composition and structure, water activ- ity and can be measured with techniques which range from direct current to microwaves (Nelson 1991). Recently, a simple dielectric technique based on a resonant plate capacitor probe was set up to predict the freshness of shell eggs (Ragni et al., 2006). Inspired from biological nervous systems, artii cial neural networks (ANN) is a mathematical algorithm capable of relate input and out- put parameters by learning from example trough iterations. ANN is able to approximate any non-linear input output relationship by means of a simple structure with connections in parallel between neurons. h is computing method is widely applied in food quality evaluation especially using computer vision system (Goyache et al., 2001; Du and Sun, 2004; Du and Sun, 2006). Main applications con- cern the classii cation of cereal grains (Lou et al., 1999), fruits and vegetables (Brandon et al., 1990; Kavdir and Guyer, 2002) and meat (Chandraratne et al., 2007). h e present research attempts to evaluate the days of storage and the main freshness parameters of shell eggs on the basis of non- destructive spectroscopic dielectric analysis and artii cial neural network method. In conclusion, even if preliminary results, this work shows that dielectric spectroscopy could be used to set up a non-destructively technique able to predict the freshness of the shell eggs and it opens up new perspectives for on line applications.
XVIII European Symposium on the Quality of Poultry MeatXII European Symposium on the Quality of Eggs and Egg Products
CZE
Czech Brand of WPSA-World's Poultry Science Associ
Berardinelli, A.; Cevoli, C.; Fabbri, A.; Giunchi, A.; Gradari, P.; Ragni, L.; Sirri, F.
Predicting freshness of shell eggs using a technique based on the dieletric properties / Berardinelli, A.; Cevoli, C.; Fabbri, A.; Giunchi, A.; Gradari, P.; Ragni, L.; Sirri, F.. - (2007). ((Intervento presentato al convegno XVIII European Symposium on the Quality of Poultry MeatXII European Symposium on the Quality of Eggs and Egg Products tenutosi a Prague nel 2-5 september 2007.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/228977
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