The Impact of Soil Conductivity on Petit Verdot Ripeness and Wine Quality in VSP Trellising (2017)

Summary

This study attempts to quantify the impact of soil conductivity on VSP-trained Petit Verdot juice and wine chemistry, as well as on the sensory qualities of wine.  Soil conductivity was determined by EM mapping performed by Bubba Beasley, in order to find areas of low and high conductivity within the vineyard block.  The low conductivity soil had a low rock content, and the high conductivity soil had high rock content (75%, shale).  Then, fruit from each conductivity region was harvested on the same day but kept separate and destemmed into two T Bins: One for low conductivity fruit, and the other for high conductivity fruit.  Fermentations were punched down twice per day, and all other treatments between wines were identical.  Yield and viticultural parameters suggest an ESVC:CW index of 1.2 for both the low conductivity and high conductivity.  Acidity and potassium was higher in the high conductivity juice.  Indeed, soil pH was found to be negatively correlated to petiolar potassium and positively correlated to fruit pH.  Petiolar potassium was also found to be positively correlated to juice potassium.  Wine made from higher conductivity grapes had higher acidity and lower potassium.  The high conductivity treatment had slightly lower anthocyanin and tannin measures.  These results, overall, suggest that the lower conductivity wine had generally “riper” characteristics.  These results would not be expected, as the higher conductivity soil (with higher rock content) would be expected to have less total available water in the soil for the grapevines to use.  It would be more expected, therefore, that the high conductivity vine would have had less water, and thus potentially more “ripe” chemistry characteristics.  Overall, the wines were not found to be significantly different at tastings.  There may have been a slight preference for the low conductivity wine, but if so it was very weak.  There were slight tendencies for the high conductivity treatment to have higher Acidity and Bitterness, and slightly lower Body.  These further suggest a less “ripe” wine was produced at the high conductivity block.  This study should be repeated over multiple vintages in order to determine whether these results are replicable.

 

Introduction

Electromagnetic conductivity (EC) soil mapping is a measurement of electrical current that often times correlates with various soil characteristics that determine plant health. These characteristics can include drainage, salt composition, nutrient density, and soil character. High electrical conductivity correlates to high cation exchange capacity, and is often found in drier soils (due to less salt leaching) or clay soils.  Higher conductivity soils also tend to have lower rock content.  Soil conductivity, indirectly measuring ionic characteristics of the soil, may also give insight into pH characteristics of fruit grown in that soil.  When conductivity mapping is used in vineyards, it may provide valuable information on vineyard management, and help the winemaker select the most productive and hearty vines.

The purpose of this study was to quantify differences of soil EC, rock content, and canopy design on Petit Verdot fruit and juice chemistry and sensory, physical and chemical properties of wines.  The rock content and EC were determined by an EC mapping project conducted by Bubba Beasley.  This study in particular looks at a VSP block and should be compared to its sister study performed on ballerina trellising (where conductivity differences were more extreme).

 

Results and Discussion

High and low conductivity harvest zones were determined using EM mapping and laid out in the field using differential GPS technology.  Soil variability is controlled by soil depth and the occurrence of shale, based on observations of soil auger holes and backhoe test pits.  Composite soil samples, veraison petiole, and harvest fruit samples were taken at several pre-determined sample locations in each zone.  Moderate EC differences were found in the two soil types.  Interestingly, the high EC soil also had a high rock content (75% shale), whereas the low EC soil had low rock content.  It must therefore be born in mind that the differences in the results may not only be due to electroconductivity differences, but also to differences in soil rock content.

Soil pH was found to be negatively correlated to petiolar potassium and positively correlated to fruit pH.  Petiolar potassium was also found to be positively correlated to juice potassium.

Yield and viticultural parameters suggest an ESVC:CW index of 1.2 for both the low conductivity and high conductivity.  Acidity and potassium was higher in the high conductivity juice.  Wine made from higher conductivity grapes had higher acidity and potassium.  The high conductivity treatment had slightly lower anthocyanin and tannin measures.  These results, overall, suggest that the lower conductivity wine had generally “riper” characteristics.  These results would not be expected, as the higher conductivity soil (with higher rock content) would be expected to have less total available water in the soil for the grapevines to use.  It would be more expected, therefore, that the high conductivity vine would have had less water, and thus potentially more “ripe” chemistry characteristics.

 

For the triangle test on April 4, of 10 people who answered, 5 people chose the correct wine (50%), suggesting that the wines were not significantly different.  Of those who correctly distinguished the wines, 4 preferred the low conductivity wine, and one preferred the high conductivity wine.  The low conductivity wine may have had slightly riper characteristics.  For the descriptive analysis, there were no strong trends for the descriptors used in this study.  There was a slight tendency for the low conductivity wine to have higher Body, Fruit Intensity, and lower Bitterness and Herbaceous/Green character.

 

For the triangle test on April 18, of 10 people who answered, 4 people chose the correct wine (40%), suggesting that the wines were not significantly different.  There were no distinguishable preference trends between each treatment.  For the descriptive analysis, there were no strong trends for the descriptors used in this study. There was a slight tendency for the high conductivity wine to have higher Acidity and Bitterness, and perhaps lower Body.

 

Overall, the wines were not found to be significantly different at tastings.  There may have been a slight preference for the low conductivity wine, but if so it was very weak.  There were slight tendencies for the high conductivity treatment to have higher Acidity and Bitterness, and slightly lower Body.  These further suggest a less “ripe” wine was produced at the high conductivity block.  This study should be repeated over multiple vintages in order to determine whether these results are replicable.

 

Methods

Soil sampling and analysis was performed by Bubba Beasley (HydroGeo Environmental).  Soil pH numbers are the weighted average of topsoil and two different subsoil samples, and fruit pH is the fruit harvest pH.  Soil samples were taken adjacent to the vine on which fruit samples were taken.  Bloom petioles were taken throughout the block, and fruit potassium represents harvest potassium (obtained by homogenizing grape samples).

Approximately 0.75 tons/treatment of Barren Ridge Petit Verdot were harvested into 25 pound lugs on 10/6/2017 and held overnight in a reefer truck at 40°F. The next day, on 10/7/17, the fruit was destemmed whole-berry into 2 T-bins in the following treatments:

1) T-bin 1: 0.70 tons destemmed fruit, not crushed, from High conductivity

2) T-bin 2: 0.70 tons destemmed fruit, not crushed, from Low conductivity

Each treatment received 4.5 g/hL sulfur dioxide during destemming layered at half full and on top of T-bin. Prior to inoculation, a juice panel was drawn for in-house analysis and WRE analysis.  All treatments were inoculated with D254 at 20g/hL on 10/7/17 with 24 g/hL GoFerm during yeast rehydration. After inoculation, each T-bin was allowed 24 hours of rest before twice-daily punch down. When must temperature reached 65°F and lag phase complete, ColorPro was added at 20ml/hL and Superfood at 20g/hL on 10/10/17. Malolactic bacteria (Alpha, Lallemand) were inoculated in each T-bin on 10/13/17 near the end of primary fermentation (0 Brix). VR Color (Laffort) was added 10/13/17.

All treatments were pressed on 11/7/17 to ensure equal maceration time. Before pressing, a single, first-use barrel was filled with free run from each treatment T-bin. Ana Sol ML were used. Tartaric acid was added to each treatment barrel on 12/4/17 at a rate of 1.2 g/L and stirred to mix.  Malolactic fermentation was monitored until all lots were below approximately 0.05g/L malic acid. On 3/1/17, 4.4g/hL sulfur dioxide was added to each barrel using two Oenosteryl 5 Effervescent (Laffort) tablets. WRE samples were removed from barrel on 3/9/17.

These wines were tasted on April 4 and April 18.  For the triangle test, descriptive analysis, and preference analysis for the April 4 tasting, anybody who did not answer the form were removed from consideration for both triangle, degree of difference, and preference.  Additionally, anybody who answered the triangle test incorrectly were removed from consideration for degree of difference and preference.  Additionally, any data points for preference which did not make sense (such as a person ranking a wine and its replicate at most and least preferred, when they correctly guessed the odd wine) were removed.  

These wines were tasted on April 4 and April 18.  In order to balance the data set to perform statistical analysis for descriptive analysis on the April 4 tasting, any judge who had not fully completed the descriptive analysis ratings were removed.  In order to then make the number of judges between groups equivalent, 2 judges from group 1 were eliminated.  This resulted in a final data set of 3 groups, each with 2 judges (considered as replications within groups, and groups were considered as assessors).  Data was analyzed using Panel Check V1.4.2.  Because this is not a truly statistical set-up, any results which are found to be statistically significant (p<0.05) will be denoted as a “strong trend” or a “strong tendency,” as opposed to general trends or tendencies.  The statistical significance here will ignore any other significant effects or interactions which may confound the results (such as a statistically significant interaction of Judge x Wine confounding a significant result from Wine alone).  The descriptors used in this study were Fruit Intensity, Herbaceous/Green, Avidity, Bitterness, Astringency, and Body.

The same procedures for data analysis were used on the April 18 tasting.  For the descriptive analysis in this tasting, one judge was transferred from group 3 to group 1, for a total of 9 judges.