The measure of quality of post-harvest fruits is considered a promising, application field for electronic nose technology such as the detection of defects. Among the possible defects present in fruits those due to post-harvest treatment are particularly important. Among them defects like mealiness (due to post-harvest over-ripening), skin damage (due to mechanical or temperature stresses), and infections affect strongly the perception of consumers. They have to be avoided in order to achieve high quality products. In this paper, the study of the variations of aroma of oranges, during the storage, and apples, due to the presence of mealiness and skin damage by means of a thickness shear mode quartz resonators- (TSMR) based electronic nose, is illustrated and discussed. Results have evidenced that the electronic nose has enough sensitivity and resolution to distinguish among the various classes and to correctly predict the amount of defects (for apples) and storage days (for oranges).
The evaluation of quality of post-harvest oranges and apples by means of an electronic nose
Di Natale C;Macagnano A;Paolesse R;Proietti E;D'Amico A
2001
Abstract
The measure of quality of post-harvest fruits is considered a promising, application field for electronic nose technology such as the detection of defects. Among the possible defects present in fruits those due to post-harvest treatment are particularly important. Among them defects like mealiness (due to post-harvest over-ripening), skin damage (due to mechanical or temperature stresses), and infections affect strongly the perception of consumers. They have to be avoided in order to achieve high quality products. In this paper, the study of the variations of aroma of oranges, during the storage, and apples, due to the presence of mealiness and skin damage by means of a thickness shear mode quartz resonators- (TSMR) based electronic nose, is illustrated and discussed. Results have evidenced that the electronic nose has enough sensitivity and resolution to distinguish among the various classes and to correctly predict the amount of defects (for apples) and storage days (for oranges).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.