Assessing the impact of defoliation on grape volatiles profile and wine odor characteristics in four Greek red varieties (Vitis vinifera L.) using multivariate chemometrics

Abstract

Context and purpose of the study. Cultivation techniques are widely recognized for their significant impact on the aroma profile of grapes and wines. Among them, defoliation is a crucial practice for viticulture management to modify the microclimate of the fruit zone, and by extension, to improve the quality of the produced wine. In the context of climate change, characterized by rising temperatures and altered precipitation patterns, defoliation might lead to excessive light incidence and heat stress on the exposed berries, thereby its necessity as a vital strategy should be reevaluated, especially under semi-arid conditions. In the present study, the impact of defoliation on four different Greek red varieties (Agiorgitiko, Xinomavro, Mandilaria and Limniona) was assessed to establish defoliation’s impact on grape and wine aroma and their sensory attributes and possible differences in their respective repsonses.

Material and methods. Vitis vinifera L. cvs located in an experimental plot in Southern Greece, were subjected during three consecutive and climatically distinct years (2021, 2022, and 2023) to two defoliation tretaments: full removal of basal leaves and laterals at veraison and non-defoliated control vines. At the stage of optimum maturity, grape samples of each variety and treatment were harvested and analysed. Experimental wines were produced in small-scale batches according to the same protocol. The volatile compounds of the red grapes and wines were analyzed through HS-SPME couples to GC-MS, while descriptive sensory analysis was conducted by a trained panel consisting of fifteen judges.

Results. Differences between defoliation treatments across the four cultivars and possible interactions were assessed using multivariate statistical analysis, including ANOVA, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models. Variant Importance in Projection (VIP) algorithm was used to calculate the VIP scores of the determined volatiles and distinguish the most important chemical markers among them that affect the discrimination, including only the variables with VIP > 0.8. In summary, despite of some common responses to sunlight exposure found within varieties, in the most of the cases, the application of the treatment and the differentiation between varieties generate a fingerprint including volatile compounds and sensory aroma characteristics.