###### Abstract  
The evaluation of the variety suitability regarding each appellation's specificities should be a strategy for maximizing the varieties' oenological potential while contributing to the sustainable production of quality wines, keeping their typicity and rationalizing winemaking costs. Thus, the combination of several grape physicochemical attributes, modulated by climate and vineyard characteristics, providing knowledge for each grape variety's oenological potential, is a relevant and reliable support for winemakers' decisions. To prove this hypothesis, six mature grape varieties from three harvests, each one from three vineyard parcels with different topographical conditions from Bairrada Appellation (Portugal), were studied using analysis of variance-simultaneous components analysis (ASCA). The effects of harvest year and parcel on grape berry weight, pH, titratable acidity, total sugars, total phenolics, antiradical activity, and volatile composition in free and glycolically-linked forms were analyzed. The compositional plasticity of autochthonous varieties (white Arinto and Bical and red Baga, Castelao, and Touriga Nacional) was observed. Sauvignon Blanc grape composition was significantly modulated by harvest. This study represents an important contribution for the maintenance of varieties' biodiversity while contributing to establishing their peculiarities. Autochthonous varieties, if accurately exploited, can provide higher characteristic diversity than worldwide used varieties, an aspect to be more objectively taken into consideration by winemakers. grape variety suitability; vineyard parcels; harvest conditions; physicochemical parameters; volatile profile; chemometric tools; metabolic plasticity +
Footnote †: journal: Medical  
by a vineyard characteristic, namely soil type, that can act as a regulator of the climate elements, due to its water-retaining (affecting water and nutrient availability to the plant), heat-retaining, and light-reflecting capacities (affecting microclimate) and penetrability (affecting the root growth) [9; 10]. Additionally, vineyard topographical factors, such as altitude and slope, modulate grape composition, influencing grapevine vigor and grape ripening, and are directly associated with the vineyards' resulting humidity, surrounding vegetation, sunlight exposure and shadow, orientation, and trellising [1; 9]. To understand the grape variety's oenological potential under the uncontrollable harvest climatic conditions and vineyard's characteristics, the application of chemometric tools to obtain fast and reliable information that can help the winemakers' decision is crucial. Robust multivariate analysis of the long-term data series may represent a key tool to reduce the environmental impact on wine quality by assisting in the implementation of adequate winemaking practices and technologies, while contributing to reducing wine production costs. Over many years, research has been aimed at developing a simple model or method that could define and/or predict grape and wine quality. In fact, different models constructed by the application of multivariate methods have already been developed [11; 12; 13; 14; 15]. For instance, a Pearson's correlation model was developed to predict Sauvignon Blanc wine quality, correlating microclimatic data (temperature and radiation) with volatile concentration and wine sensory parameters [11]. Geo-spatial modelling and partial least squares (PLS) were also used to assess the spatial behavior of three grape varieties (Cabernet Sauvignon, Syrah, and Merlot) according to quality zone delineation [12]. Although contributing to the understanding of the relationships that may occur between factors, such as climate, viticulture techniques, vineyard ecosystems, and grape composition, this kind of model is restricted in space and in the number of parameters evaluated, thus limiting its prediction power.