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European hazelnut is an important nut crop in Italy, where about 121,750 tons of in-shell nuts are produced every year. Roasting is the most important practice for hazelnut preservation and commonly is carried out in commercial electrical ovens at 120-160°C for 10-20 min. This needful practice is time and energy expensive, so the development of new processing methods is required to reduce processing costs and to obtain top quality roasted nuts. The aim of this study was to develop a simple microwave treatment for hazelnuts peeling and roasting.With this aim, some physical (colour, temperature, moisture) and chemical (taste, lipoxygenase activity, fatty acids, vitamins, sensory attributes) features of inshell nuts and kernels of three Italian hazelnut varieties (Tonda di Giffoni, Tonda Romana and Nocchione) after conventional oven or microwave roasting were evaluated.Results showed that microwave roasting of kernels for 450 s gave a higher peeling score than the conventional oven treatment. This paralleled with better colour and taste scores for microwaved roasted kernels. Furthermore, a 360-450 s microwave roasting was able to inactivate almost completely lipoxygenases, avoiding adverse effects on fatty acids hydroperoxides and PUFA content. A shorter microwave treatment (360 s) was enough to obtain good peeling and sensory scores of inshell hazelnuts.Taken together our results indicated that microwave technology can be successfully applied to both kernels and inshell hazelnuts to obtain suitable peeling and high quality roasted nuts.

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SUMMARYThe EU-Rotate_N model was developed as a tool to estimate the growth and nitrogen (N) uptake of vegetable crop rotations across a wide range of European climatic conditions and to assess the economic and environmental consequences of alternative management strategies. The model has been evaluated under field conditions in Germany and Norway and under greenhouse conditions in China. The present work evaluated the model using Italian data to evaluate its performance in a warm and dry environment. Data were collected from four 2-year field rotations, which included lettuce (Lactuca sativa L.), fennel (Foeniculum vulgare Mill.), spinach (Spinacia oleracea L.), broccoli (Brassica oleracea L. var. italica Plenck) and white cabbage (B. oleracea convar. capitata var. alba L.); each rotation used three different rates of N fertilizer (average recommended N1, assumed farmer's practice N2 = N1 + 0·3 × N1 and a zero control N0). Although the model was not calibrated prior to running the simulations, results for above-ground dry matter biomass, crop residue biomass, crop N concentration and crop N uptake were promising. However, soil mineral N predictions to 0·6 m depth were poor. The main problem with the prediction of the test variables was the poor ability to capture N mineralization in some autumn periods and an inappropriate parameterization of fennel. In conclusion, the model performed well, giving results comparable with other bio-physical process simulation models, but for more complex crop rotations. The model has the potential for application in Mediterranean environments for field vegetable production.

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