A climatic characterisation of the sub-Appellations in the Niagara Peninsula wine region

The valley of Caravelí (Peru) received the first vine plants in colonial times and the tradition of cultivation is maintained thanks to its terroir and artisanal techniques.

Analysis of phenolic compounds typically involve spectrophotometric methods as well as liquid chromatography combined with DAD, fluorimetric, or MS detection. However, the complexity of wine phenolic composition generated, in recent years, attention towards other analytical approaches, including those allowing rapid and inexpensive operations. Voltametric AIM Oxidation of white wine phenolics occurs at different stages during winemaking and storage and can have important implications for wine sensory quality. Phenolic compounds, in particular those with a ortho-diphenol moiety, are main target of oxidation in wine. Strategies for the methods are particularly suited for the analysis of oxidizable compounds such as phenolics. The redox-active species can be oxidized and reduced at the electrode, therefore, applications of electrochemistry have been developed both to quantify such species, and to probe wine maturation processes.3 The project on the diversity of Italian wines aims at collecting and analysing large-scale compositional dataset related to Italian white wines.

As Vitis vinifera varieties are susceptible to fungal diseases, numerous chemical treatments are generally required to ensure the quantity and quality of the harvest. However, in the context of sustainable viticulture, there are increasing societal request, political incitation, and winegrowers’ awareness to reduce the use of pesticides.

The recent Free Trade Agreement negotiations between Australia and the European Union have again put the issue of Geographical Indications (GIs) in the spotlight. Australia has long demonstrated its understanding of GIs and maintains a clear and rigorous GI protection system for wine. For many years, Australia’s wine sector was a strong advocate for GIs and a strong system to protect the

The need to combine multimodal data for complex samples is due to the different information captured in each of the techniques (modes).