Machine Learning and Vinho Verde

Red Wine Quality Forecasts using Machine Learning Google Colab

Portugal is a top ten wine exporting country. Exports of its vinho verde wine (from the northwest region) have increased dramatically in recent years. The Vinho Verde nomenclature is unique in the wine world. It refers to both a style of wine and to the area from which it comes. Vinho Verde is Portugal’s largest wine region, stretching to the Spanish border in the north and across to the Atlantic Ocean to the west. Vinho Verde simply means ‘green wine’. Whilst it is true for a few wines which incidentally have a somewhat green hue, the name reflects the regional landscape and flora. Verde has a cool, wet climate with levels of rainfall approaching Leinster, Ireland. These wines are generally high in acidity and relatively low in alcohol, intended to be drunk young. The pedigree of wine has enormous bearing on price and the economics of branding play out by traditionally bestowing on tasters and connoisseurs enormous influence. In the analysis presented below, laboratory measures of physical properties are included in the analysis of establishing a quality ratings.

https://winefolly.com/deep-dive/vinho-verde-the-perfect-poolside-wine-from-portugal/

Wine certification and quality assessment are central to preventing illegal adulteration and can help build reputation. Quality evaluation is often part of the certification process and can be used to improve wine making (by identifying the most influential factors) and long term helps to elevate premium brands and pricing. Physicochemical and sensory tests are mutually important. Physicochemical laboratory tests are routinely used to characterize wine. These include determination of; density, alcohol and pH values while sensory tests rely on human expertise. The data were recorded by a computerized system (iLab), which automatically manages the process of wine sample testing from producer requests to laboratory and sensory analysis. Each entry denotes a given test. Please see paper here.