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. 2021 May 27;5(5):e00324.
doi: 10.1002/pld3.324. eCollection 2021 May.

Grapevine rootstocks affect growth-related scion phenotypes

Zoë Migicovsky  1 , Peter Cousins  2 , Lindsay M Jordan  3 , Sean Myles  1 , Richard Keith Striegler  3 , Paul Verdegaal  4 , Daniel H Chitwood  5   6
Affiliations

Grapevine rootstocks affect growth-related scion phenotypes

Zoë Migicovsky et al. Plant Direct. .

Abstract

Grape growers use rootstocks to provide protection against pests and pathogens and to modulate viticulture performance such as shoot growth. Our study examined two grapevine scion varieties ('Chardonnay' and 'Cabernet Sauvignon') grafted to 15 different rootstocks and determined the effect of rootstocks on eight traits important to viticulture. We assessed the vines across five years and identified both year and variety as contributing strongly to trait variation. The effect of rootstock was relatively consistent across years and varieties, explaining between 8.99% and 9.78% of the variation in growth-related traits including yield, pruning weight, berry weight and Ravaz index (yield to pruning weight ratio). Increases in yield due to rootstock were generally the result of increases in berry weight, likely due to increased water uptake by vines grafted to a particular rootstock. We demonstrated a greater than 50% increase in yield, pruning weight, or Ravaz index by choosing the optimal rootstock, indicating that rootstock choice is crucial for grape growers looking to improve vine performance.

Keywords: grafting; grapevines; rootstocks; root‐shoot interactions.

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Conflict of interest statement

PC, LMJ, and RKS were employed by E. & J. Gallo Winery. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Phenotypic variation across years (1995 to 1999) for each rootstock by scion combination. Ravaz index is a measurement of crop load calculated by dividing yield by pruning weight from the following dormant season. Loess smoothing lines are plotted; however, the data are independent and these are for visualization purposes only. Individual data points for this figure are plotted in Figure S5
FIGURE 2
FIGURE 2
Phenotypic variation explained by factors of interest estimated using a linear model (Equation 1). For each phenotype, the linear model was optimized by removing non‐significant interaction effects. For factors which explained a significant amount of variance (p < .05), the percent variance explained is indicated using colour and text. Position in the vineyard (block) was included in the model but is not plotted. Phenotypes are sorted in order of the most variance explained by rootstock
FIGURE 3
FIGURE 3
Variation in (a) yield, (b) berry weight, (c) pruning weight, and (d) Ravaz index across vines grafted to 15 different rootstocks. Rootstocks are ordered from highest to lowest mean values. Tukey test results are reported from a linear model accounting for variation in year, variety, position in the vineyard (block), and applicable interaction effects. Rootstocks with the same letter (indicated inside the plot) were not significantly different from each other. For estimated marginal means see Figure S3
FIGURE 4
FIGURE 4
Spearman's correlations among phenotypes for (a) ‘Chardonnay’ and (b) ‘Cabernet Sauvignon’. P values were Bonferroni‐corrected for multiple comparisons within a particular variety
FIGURE 5
FIGURE 5
Percent change in each phenotype from rootstock with the lowest median to the rootstock with the highest median. Phenotypes are ordered from largest percent change to lowest percent change. Raw values are also listed
See this image and copyright information in PMC

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