Vegetation index cartography as a methodology complement to the terroir zoning for its use in precision viticulture

摘要

Aim: Precision Viticulture (PV) is a form of vineyard management based on tools that offer winegrowers georeferenced information of each vineyard, mainly sector mapping (sub-areas) differentiated by characteristics capable of influencing vineyard usage. This provides knowledge of the variations in these sectors and PV treats each one of them in an independent and optimised manner. This allows, amongst many other possibilities, to monitor fruit ripening with the objective of performing site-specific harvest based on the characteristics of each given sector. Local variations in soil features and natural environmental factors, such as climate, lithology, geomorphology and soil, determine the units that drive or limit PV.Methods and results: In this paper, multispectral images are used. These have been obtained between veraison and harvest in three different years in order to calculate four vegetation indexes (VI) that have been used since the end of the last century to delimit homogenous sectors in vineyards: the Normalized Difference Vegetation Index (NDVI), the Improved Soil Adjusted Vegetation Index (MSAVI), the Simple Ratio Index (SR) and the Modified Simple Ratio Index (MSR). Mapping of these VI has allowed to relate their distribution with natural environmental factors with the objective of valuing their use in the discrimination of homogenous sectors as a complement and/or alternative to traditional methodologies to terroir zoning. Results show that, in the area studied, the vineyards planted in alluvial soil and conglomerated zones, over dominant fine-loamy, mixed, mesic, Calcixerollic Xerochrept soil series, at elevations between 519 and 604 m, oriented east and on slopes less than 5o present higher values for all four indexes throughout the three years of study.Conclusions: It is precisely these environmental elements (lithology, soil, elevation, orientation and slope) and many soil features that must be relatively uniform in order to make an efficient use of the studied VI.Significance and impact of the study: The study addresses the use of VI as a companion tool to viticultural zoning, which has not been much explored at such scale level. In addition, the results obtained may lead to changes in the use of VI, which are usually used without taking into account soil and/or terrain features. Introduction The fundamental objective of Precision Viticulture (PV) is to use detailed information about the biophysical characteristics and performance of a vineyard, at high spatial resolution, as the basis for viticultural management and decision making (Bramley, 2010). Its practical implementation is dependent on various technological developments: crop sensors and yield monitors, local and remote sensors, Global Positioning Systems (GPS), Variable-Rate Application (VRA) equipment and machinery, Geographical Information Systems (GIS) and data analysis and interpretation systems (Arno et al., 2009). Therefore, PV allows maximizing yield and quality while minimizing environmental impacts and risk (Proffitt et al., 2006).????Before the advent of PV, variability within vineyards was normally managed as "noise" (background level) and often went unnoticed. Therefore, the group of parameters involved in this variability could not be explained nor linked to each other (Cook and Bramley, 1998; Bramley and Hamilton, 2004).Local variations in climate, lithology, geomorphology and soil factors determine the existence of sectors, which define the units that drive or limit PV (Gómez-Miguel, 2011). More precisely, some elements, mainly climate and soil, allow for sector discrimination based on grapevine development and grape composition, which can be explained by their influence on the water status of the plant (van Leeuwen et al., 2004).The graphic representation of the different sectors, defined by the environmental characteristics, is carried through cartography and the mapping technique provided by the use of GIS. Climate maps have been produced (Jones et al., 2010), as well as lithological, geological and geomorphological maps (Morlat, 1989; Vaudour, 2010), soil maps (Morlat and Bodin, 2006), altitude, slope and orientation maps and/or a combination of various elements integrated in one unique map (Gómez-Miguel and Sotés, 1997). The completion of these maps, specially the soil map, is a complex and expensive task, but they are the basis of PV because not only do they allow the differentiation of homogenous sectors (sub-areas), they also help explain the effects of this variability in the vineyard.When working at a regional level, medium and small scales are used (≤1:25.000/50.000), while when studying variability within or between vineyards, the used scales are larger (≥1:5.000) (Gómez-Miguel, 2011). Thus, at the field level, PV technology highlights micro-scale variability which is mainly due to variations in soil depth and physicochemical properties (Bramley and Hamilton, 2007), whereas when the area considered is l