**2. Material and methods**

*Plant Communities and Their Environment*

wine culture for best wine production [2].

proposal of the Marquis of Pombal.

The concept of *terroir* began to be used in the fourteenth century for some production properties of high-quality wines in Côte d'Or, Burgundy [2], being difficult to define the ideal factors that make up the *terroir* due to the interaction that exists between them [3]. This complexity of individual natural factor analysis, soil particularly, is gradually overcome with new tools for detection, management, and data analysis. In any case, although the physical and chemical interactions that affect the vineyard are not known with total accuracy, the dissemination of the *terroir* concept is fostering a better knowledge and use of geology, soil, climate, and

The first scientific studies related to the viticultural environment elements and their interactions are carried out in the last quarter of the twentieth century, being able to consider the doctoral thesis of Professor Morlat [4], one of the pioneering studies on the *terroir* zoning in the modern meaning of the term. The aforementioned work takes place in the middle area of the Loire Valley, and European countries have traditionally given more importance to the environment elements in the wine characterization, thus protecting the origin of the wines. Two examples of this tradition are the current classification of Bordeaux wines, which have been practically unchanged since its creation in 1855, and the classification of port wines that were delimited in 1758 (now that zoning has been expanded) and carried out by "Companhia Geral da Agricultura das Vinhas do Alto Douro" (a company similar to the current Regulatory Councils) at the

The globalization of international wine trade has led to increased production, especially in new countries, of varietal and brand wines, and the adoption of lowinput techniques, exerting significant pressure on traditional *terroir* wine producers [5]. Even so, there are many recent scientific publications on the concept of *terroir*, interrelating elements of the environment such as temperature [6], water status [7],

To study the influence of climate in the vineyard, it is traditional to differentiate between macroclimate, mesoclimate, and microclimate depending on the scale of work. The first refers to the climate of a region and is the main limiting factor for the cultivation of the vine [11], while the mesoclimate is characteristic of a specific topographic and landscape location and affects a set of plants equally in a given geomorphological unit. Finally, the microclimate refers to the vine, surrounds to leaves and clusters and has a great influence in the biological cycle (e.g., it is of great importance in the grape ripening stage), being able to modify through the vineyard

Geology and geomorphology allow a synthetic approach adapted to small-scale

The soil study methodology is specified in the genesis of the soil taxonomic units (STU) and the soil map (or cartographic) units (SMU) during the process of their recognition. The processing of the information generated in the different layers of information by a geographic information system (GIS) results in the quantification of the contents and the possibility of their statistical treatment [15]. This methodology has been and continues to be used as part of the *terroir* zoning of both smallscale viticultural regions (macrozoning), for example, 1:50,000 or 1:25,000, and in vineyards or sets of smaller vineyards at larger scales (microzonifications) between

zonings (≤ 1:50,000), explaining the behavior of the vine only indirectly [12]. The geological or geomorphological maps are useful as a first approximation to the *terroir* zoning, since very different soils can be included in the same map unit, so it is necessary to determine the types of soil [13]. For this reason, many of the approaches to viticultural zoning borrow their approach from pedological cartogra-

light [8], geology [9], soil [10], etc. with the response of the vine.

**178**

management.

phy, with some variants [14].

1:5000 and 1:10,000.

The experimental work is carried out for 4 consecutive years (2012, 2013, 2014, and 2015) in four vineyards (A, B, C, and D) located at an average distance of 2 km from each other, in the municipality of Oyón (Álava). The vineyards are protected by the DOCa Rioja, appellation of origin associated with the Ebro River, and located in the northern third of the Iberian Peninsula.

Regarding the climate of the area where the vineyards are framed, the rainfall and average annual temperature are 459 L m<sup>−</sup><sup>2</sup> and 13.7°C and during the vegetative period (April–October) are 260 L m<sup>−</sup><sup>2</sup> and 18.1°C, respectively. According to the Multicriteria System of Climatic Classification (MSCC) [28], the climate is warm temperate (HI + 1), of cool nights (CI + 1) and moderately dry (DI + 1). Although the dominant wind is from the west, another typical northwest wind (known as *cierzo*) has influence during the grape ripening.

The greater part of the vineyards of the area is grown on sandstone and lutites of Haro's facies (Middle-Upper Miocene) [29]. Some of the soils found on this geology and their associated quaternary system are [30] alfisols (e.g., Calcic Haploxeralf subgroup), entisols (e.g., Typic Xerofluvent subgroup), or inceptisols (e.g., Typic Xerocrept subgroup). For more details of the study area, see [9]. The grape cultivar is Tempranillo, grafted on 41B, and the vines are trained using a single trellis system (bilateral cordon Royat pruning), with 2976 vines/ha, and soil management is by tillage.

A zoning is carried out under viticultural criteria (variety and vine age) in the four vineyards, and in the resulting subplots, a FIA was drawn from digital orthophotographs of 0.25 meters of spectral resolution [31], discriminating sectors (A1, A2, A3 for vineyard A and analogously for the rest of the vineyards) on a scale of 1:2500, that is, on a vineyard scale. In each sector, 12 vines are marked, divided into 2 repetitions of 6 plants. Measurements of vegetative growth and yield are carried out, as well as physical-chemical analysis of the grape on each repetition. For the pedological study, a pit is made next to each of the repetitions of six vines,

describing the profile and analyzing the different horizons in the laboratory. In this way, between two and three pits per hectare of vineyard are made, density suitable for very detailed soil zoning [12, 32]. The soil classification proposed by the United States Department of Agriculture has been used [30].

The NDVI is defined as the difference between the radiance value in near infrared and red, divided by their sum [20]. In this work, these radiance values have been obtained from multispectral images captured by the Pléiades satellite (0.5 meters of spatial resolution) on August 25, 2014, and August 19, 2015, and by the SPOT 5 satellite (2.5 meters of spatial resolution) on August 14, 2013. The calculation and graphic representation of the NDVI are carried out pixel by pixel, with the help of the ArcGIS 10.1 software from the Environmental Systems Research Institute (ESRI). The definition of the classes (very low, low, medium, high, and very high) is done according to five quantiles, the first quantile corresponding to the very low class and the fifth quantile to the very high class.

The statistical analysis of the data was carried out through principal component analysis (PCA) and univariate ANOVA, after checking normality and homogeneity of variances of the variables. The significance of these analyses was determined for the probability levels p < 0.05 (\*), p < 0.01 (\*\*), and p < 0.001 (\*\*\*). The means are compared by the Duncan test when there were significant differences in the analysis of variance. The SPSS program, version 15.0 (SPSS Inc. Chicago, Illinois), was used for the ANOVA analyses, and for the rest of the statistical calculations, the XLSTAT 2019.1.2 supplement was used on Microsoft Excel 2007. This complement was also used to perform an agglomerative hierarchical clustering (AHC) reducing the 28 analyzed variables of the epipedon before performing the PCA. In this case, the correlation between variables has been calculated for a significance level alpha = 0.05.

For the geostatistical study of the NDVI distribution, the normalized Moran index (NMI) is used, which measures the spatial autocorrelation allowing to evaluate if the NDVI pattern is clustered, dispersed, or random. For the calculation of this index, as well as the associated z-value, the ArcGIS 10.1 ESRI tool is used.
