Fac-simile Scheda Linee di Ricerca - Federalimentare

Dati pubblicati inerenti il tema di ricerca:1. Mariotti, M., Sinelli, N., Catenacci, F., Pagani, M.A., Lucisano, M. (2008). Retrogradationbehaviour of milled and brown rice pastes during ageing. Journal of Cereal Science (accepted;DOI: 10.1016/j.jcs.2008.09.005)Retrogradation of gelatinised starch is the main phenomenon that influences the texture of cooked rice. The rateof retrogradation is affected by several factors including amylose and amylopectin ratio, protein and fibre. Theobjective of this study was to analyse the pasting properties and the retrogradation behaviour of six traditionaland five aromatic Italian rice varieties. The pasted gels, after cooling, were evaluated by dynamic rheologicalmeasurements for up to 7 days of storage at 4°C. The samples were also analysed by a NIR spectrometer. Thepasting properties and the retrogradation behaviour of milled rice flours strongly depended on the rice varieties.During gel ageing, a noticeable increase of G’ and G” was observed only for the milled rice varieties Asia,Gange, Fragrance and Vialone Nano, characterised by a high amylose content. No further hardening was foundeither for the other milled varieties or for all the brown samples. The methods used in this work (dynamic oscillatoryrheometry and FT-NIR spectroscopy) turned out to be very useful in the definition of rice starch gels ageing.2. Foca, G., Ulrici, A., Corbellini, M., Pagani, M.A., Lucisano, M., Franchini, G.C., Tassi, L.(2007). Reproducibility of the Italian ISQ method for quality classification of bread wheats:an evaluation by expert assessors. Journal of the Science of Food and Agriculture 87:839–846.The great variety of different bakery products in Italy has led to the development of a method, the Synthetic Indexof Quality (Indice Sintetico di Qualità, ISQ), for the classification of bread wheats in different quality categories.Based on chemical and rheological properties, each wheat sample is assigned to the most suitable class byan expert assessor. In many cases this procedure is not straightforward, making the class assignation uncertain,thus leading to the possibility of controversies during the trading phase. In the present study, in order to have aquantitative estimate of the validity and reliability of this procedure, a panel composed of nine expert assessorswas utilised for the repeated evaluation of 100 samples of bread wheats of various qualities. The results suggestthat the proposed approach can be used both to monitor the reliability of the single assessors, and to identifysamples whose class assignation is reasonably indubitable, e.g. to be used for the development of automatedclassification methods. Moreover, the analysis of the most uncertain assignation cases can be useful in order toenhance the ISQ classification method itself.3. Sinelli, N., Pagani, M.A., Mariotti, M., Lucisano, M., D'Egidio, M.G. (2007). Prediction ofSemolina Quality Using FT-NIR Spectroscopy. Proceedings of “The 13 th International Conferenceon Near Infrared Spectroscopy” (13 th ICNIRS), Umeå-Vasa, Sweden&Finland, June,15-21.The aim of this work was to investigate the feasibility of applying FT-NIR spectroscopy to set up suitable modelsto evaluate and predict semolina characteristics by collecting the spectra directly from durum wheat kernels.This work was carried out on durum wheat kernels and the corresponding semolina produced on pilot-scale.More than 500 samples of both grains and semolina, representative of the Italian production and coming from 4different crops (from 2002/2003 to 2005/2006) were analysed. Pasta-making capability of each semolina samplewas assessed by the reference methods for protein and gluten content and by the alveographic test. This approachrequires long times due both to the milling process and the chemical and rheological analysis of the semolinasamples. All samples were also evaluated by NIR spectroscopy, using a FT-NIR spectrometer, fitted with a integrationsphere, working in diffuse reflectance. Kernels were directly put in the Petri box and the spectra werecollected over the range from 12000 to 3600 cm -1 .Predictive models were evaluated using raw data, 1st derivative and 2nd derivative after pre-treatment withStandard Normal Variate (SNV). The processed spectra of kernels were correlated with the chemical andrheological parameters obtained by the reference methods on semolina samples. The PLS algorithm was used todevelop calibration models from the original spectra sets. Protein content (r val >0.93, SEP 0.90, SEP