Fac-simile Scheda Linee di Ricerca - Federalimentare

Dati pubblicati inerenti il tema di ricerca:1. Romani, S., Rocculi, P., Mendoza, F., Dalla Rosa, M. (2009) Image characterization of potatochip appearance durino frying. Journal of Food Engineering doi:10.1016/j.jfoodeng.2009.02.017The aim of this study was to evaluate the suitability of a computerized image analysis technique (with a flatbedscanner for image acquisition) in order to measure the amount and distribution of the most important visualaspects of potato chips: colour (L*, a* and b* components) and brown and oily areas on the surface. Potato sliceswere fried at three temperatures (170, 180 and 190° C) and times (2, 3 and 4 min). Pre-processing, segmentationand colour analysis were carried out by a software programmed in Matlab v6.5. Results showed a high linearrelationship (R 2 > 0.962) between image RGB values and those measured by conventional colorimeter. Theapplied image analysis technique was able to differentiate with high sensitivity among potato chip colours afterfrying processes. On average the percentages of normal, brown and oily area detected on the samples were53.24, 24.04 and 22.96% respectively. While data of brown area appearance were congruous with browningincidence bound to the entity of the frying process, discrepant results were obtained using the objective colourpattern for the evaluation of the extension of oily area in the surface of potato chips. Anyway, this techniquepresents a high potential to develop a computer vision on-line system for frying process optimization, as afunction of the fat content of the final product.2. Alessandrini, L., Romani, S., Pinnavaia, G.G., Dalla Rosa, M. (2008) Near InfraredSpectroscopy: an analytical tool to predict coffee roasting degree. Analytica Chimica Acta,625, 95-102.The main purpose of this study was to investigate the relationship between some coffee roasting variables(weight loss, density and moisture) with near infrared (NIR) spectra of original green (i.e. raw) and differentlyroasted coffee samples, in order to test the availability of non-destructive NIR technique to predict coffeeroasting degree. Separate calibration and validation models, based on partial least square (PLS) regression,correlating NIR spectral data of 168 representatives and suitable green and roasted coffee samples with eachroasting variable, were developed. Using PLS regression, a prediction of the three modelled roasting responseswas performed. High accuracy results were obtained, whose root mean square errors of the residuals inprediction (RMSEP) ranged from0.02 to 1.23%. Obtained data allowed to construct robust and reliable modelsfor the prediction of roasting variables of unknown roasted coffee samples, considering that measured vs.predicted values showed high correlation coefficients (r from 0.92 to 0.98). Results provided by calibrationmodels proposed were comparable in terms of accuracy to the conventional analyses, revealing a promisingfeasibility of NIR methodology for on-line or routine applications to predict and/or control coffee roastingdegree via NIRspectra.3. Romani, S., Rocculi, P., Dalla Rosa, M. (2006) Studio preliminare sull’uso del nasoelettronico per discriminare biscotti in funzione della formulazione. Industrie Alimentari, 464,(12), 1273-1276.Scopo di tale lavoro è stato quello di verificare l’abilità del NE nel discriminare biscotti diversi per tipologia eformulazione (frollini alla panna, all’uovo, alla granella di zucchero, con yogurt e mandorle, al burro, alcioccolato), prodotti dalla medesima azienda. Sono stati, inoltre, sottoposti all’analisi con NE alcuni ingredientiprincipali, utilizzati nella formulazione degli stessi biscotti, allo scopo di verificare eventuali analogie tra le“impronte olfattive” degli ingredienti e dei prodotti finiti. I dati ottenuti dall’analisi effettuata col NE sono statielaborati mediante analisi delle componenti principali (PCA). I risultati ottenuti mostrano come l’utilizzo del NEsia in grado di fornire alcune informazioni relative alle impronte aromatiche di biscotti diversi. Tuttavia, non intutti i casi i sensori dello strumento sono riusciti a discriminare i differenti tipi di biscotti analizzati. Tra i tipi dibiscotti che lo strumento è stato in grado di discriminare, non sono state registrate analogie tra le loro impronteolfattive e quelle degli ingredienti impiegati nella loro formulazione, ad eccezione che tra l’aroma di arancia e latipologia di biscotto che lo conteneva.SISTAL - SOCIETA’ ITALIANA DI SCIENZE E TECNOLOGIE ALIMENTARIDipartimento di Scienze e Tecnologie Agroalimentari, Università degli Studi della TusciaVia San Camillo de Lellis, 01100 ViterboTel.: 0761- 35 74 94/7 , Fax: 0761- 35 74 98, e-mail: mmoresi@unitus.it53