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A strawberry spreadable cream was developed, valorizing regional raw materials, contributing to food waste reduction and agri-food ecosystem sustainability. Spreadable creams are water-in-oil emulsions whose lipid phase normally contains a blend of vegetable oils, natural colourants, stabilizers, emulsifiers, flavourings, antioxidants, lecithin, and fat-soluble vitamins. The aqueous phase normally contains skim milk proteins and small quantities of other ingredients, such as salt, preservatives, thickeners, and water-soluble vitamins. The methodology involved the experimental technological development articulated with microbiological, proximal, physicochemical, and sensorial analysis. This new product revealed nutritional advantages over similar products already on the market. The final prototype was subjected to food pairing and food design with incremental acceptance according to gastronomic use, in addition to its direct use as a spreadable cream. This work was part of the project Agrio et Emulsio—new products development (POCI-01-0145-FEDER-023583), whose main objective was the formulation and design of innovative food emulsions based on processed raw materials, with potential application in certain markets such as gourmet, diet, and vegan.

This study evaluates the simulation of water balance components at half-hourly time steps from the Canadian Land Surface Scheme (CLASS) when driven by a 500-year stochastic meteorological data set produced by the Advanced WEather GENerator (AWE-GEN) at two boreal sites with contrasting water availability. The CLASS was driven by ERA5 reanalysis data (CLASS-CTL) over 39 years and its output was used as a surrogate for land surface observations. At both sites, the mean monthly and annual values of all meteorological variables used to drive CLASS, including precipitation, are well captured by AWE-GEN, but their variability is, sometimes, biased. In general, CLASS driven by stochastic data (CLASS-WG) tends to produce higher evapotranspiration compared to values simulated by CLASS-CTL, especially during spring and summer at the wet site. The interannual evapotranspiration-precipitation and runoff-precipitation relationships derived from CLASS-WG and those derived from CLASS-CTL were very similar to each other at the dry site; they both indicate that evapotranspiration and runoff are limited by water availability. At the wet site, however, CLASS-WG only captured well the interannual runoff-precipitation relationship. The sensitivity analysis shows that CLASS water fluxes are particularly affected by the replacement of physically consistent input time series of incoming short-wave radiation, precipitation, temperature, and specific humidity. In conclusion, the results show that even though a weather generator can produce coherent climate time series, the use of this synthetic data as meteorological forcing in a physically based land surface model does not necessarily reproduce the complex surface processes, such as the surface water fluxes. More studies are encouraged to further analyze the constraints of this framework.