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TEMPORAL STABILITY OF WITHIN-FIELD VARIABILITY OF TOTAL SOLUBLE SOLIDS OF GRAPEVINE UNDER SEMI-ARID CONDITIONS: A FIRST STEP TOWARDS A SPATIAL MODEL
The experiment was carried out on four fields (one cultivar each) of the cvs Cabernet Sauvignon (CS), Chardonnay (CH), Sauvignon Blanc (SB) and Carménère (CA), all of them located in the Maule Valley, Chile, under irrigated conditions (Fig. 1). The cultivars CS, CH and SB are located at the University of Talca’s experimental vineyard, while the cultivar CA is located in a commercial vineyard in Pencahue, 18 kilometers away from the other fields. All vineyards were managed according to the conventional agricultural practices used in the commercial vineyards of central Chile in terms of canopy management, fertilization, pest and disease control, pruning and irrigation, for all the seasons of the study period. Characteristics of each field are summarized in Table 1.
Figure 1 Location of the Maule Valley in Chile.
VSP: Vertical shoot positioned System
Within each vine field, a regular sampling grid of 20×20 m was designed (Fig. 2). According to the field area, this sampling grid considered 18 sampling sites for cv CS, 19 sites for cv CH, 30 sites for cv SB and 20 sites for cv CA. Each sampling site of the grid was represented by four consecutive plants in the same row. This sample grid was mainly conditioned by the operational constraints related to the time required to make the measurements over the fields. Note however, that in absence of other spatial information, considering the average spatial variability of yield on a large number of vineyard plots Caractérisation et modélisation de la variabilité spatiale de la phénologie de la vigne à l’échelle intra-parcellaire Nicolás VERDUGO-VÁSQUEZ – 2017 (Taylor et al. 2005), this distance was sufficient to account for a large part of the within field variability. The borders of the fields and sampling sites within each field were geo-referenced with a differential global positioning system receiver (Trimble, Pathfinder ProXRS, Sunnyvale, California, USA) and stored as East and North coordinates (Datum WGS84, UTM projection, Zone 19S).
Climatic data
An automatic weather station (Adcon Telemetric, A730, Klosterneuburg, Austria) installed under reference conditions was used to characterize the environmental conditions (air temperature and precipitation) of the seasons. Data were collected at 15-minute intervals from September to April every year. The automatic weather station was located at 0.3 km from the CS, CH and SB cultivars and at 18 km from CA cultivar.
Measurements of total soluble solids (TSS)
On each site of the grid (Fig. 2), TSS was measured using a thermo-compensated refractometer (BRIX30 model, Leica, USA) on a sample of 48 berries. Berries were selected following the same methodology for each site and proposed by Trought and Bramley (2011): for each of the 4 vines of a site, two clusters were randomly chosen, and for each cluster, two berries were sampled at the top, the middle and the bottom of the clusters to obtain a total of 6 berries per clusters which resulted in 48 berries per site. The 48 berries were crushed in a plastic bag and TSS was measured from the resulting juice. For each site, measurements were made from veraison to harvest at intervals ranging from 2 to 15 days. Measurements of phenology (budburst and veraison) was estimated using the Eichhorn and Lorenz phenological scale as modified by Coombe (Coombe 1995). In the following sections the term precocity will be used to define the time of occurrence of phenological stages (Tesic et al. 2001). The number of sampling dates was related to the precocity of each cultivar. This experiment lasted 4 years for CS and CH, 3 years for SB and 2 years for CA.
Descriptive statistics, such as mean, standard deviation (SD) and coefficient of variation (CV) were calculated for each dataset (date×cultivars). For the classical statistical analysis, the Statgraphics Plus 5.1 (StatPoint Inc., Virginia, USA) software was used.
Intra-annual TSWFV
In order to quantify the intra-annual TSWFV, two statistics were used: (i) The Kendall coefficient of concordance (W) and (ii) The Spearman’s rank correlation coefficient (rs). Both statistics (W and rs) have been used in similar studies (Kazmierski et al. 2011; Tisseyre et al. 2008). W was used to analyse the intra-annual TSWFV between all dates for each cultivar and season. W focuses on the rank of the values and provides an assessment on how the rank given by several judges fits between the different n objects (Saporta 1990). In this work, the n objects were the sampling sites of each vine field (Fig. 2), and the “judges” were the different sampling dates measured in each season and cultivar. The analysis was then conducted on a matrix where the lines referred to the sampling sites and the columns to values of TSS measured at different dates for each season and cultivar. The W varies from 0 (total disagreement or no temporal stability) to 1 (total agreement or high temporal stability). W was computed according to Eq. 1 (Saporta 1990).
Table of contents :
CHAPTER 1: SPATIAL VARIABILITY OF PHENOLOGY IN TWO IRRIGATED GRAPEVINE CULTIVAR GROWING UNDER SEMI-ARID CONDITIONS
CHAPTER 2: TEMPORAL STABILITY OF WITHIN-FIELD VARIABILITY OF TOTAL SOLUBLE SOLIDS OF GRAPEVINE UNDER SEMI-ARID CONDITIONS: A FIRST STEP TOWARDS A SPATIAL MODEL
CHAPTER 3: IDENTIFICATION OF MAIN FACTORS AFFECTING THE WITHIN FIELD SPATIAL VARIABILITY OF GRAPEVINE PHENOLOGY AND MATURATION: ZONING USING AUXILIARY DATA
CHAPTER 4: TOWARDS AN EMPIRICAL MODEL TO ESTIMATE THE SPATIAL VARIABILITY OF GRAPEVINE PHENOLOGY AT THE WITHIN FIELD SCALE
CHAPTER 5: TOWARDS AN EMPIRICAL SPATIAL MODEL TO ESTIMATE THE SPATIAL VARIABILITY OF THE TOTAL SOLUBLE SOLIDS OF GRAPEVINE AT THE WITHIN FIELD SCALE
CHAPTER 6: ASSESSMENT OF AN EMPIRICAL SPATIO-TEMPORAL MODEL OF THE GRAPEVINE PHENOLOGY AT THE WITHIN-FIELD SCALE
CONCLUSIONES GENERALES Y PERSPECTIVAS
