Exploring intra-vineyard variability with sensor- and molecular-based approaches
The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.
Fourteen spots presenting intra-parcel variability were selected and monitored in a Cabernet Sauvignon vineyard in the Sonoma wine region (CA, USA) during 2017 growing season. The Normalized Difference Vegetation Index (NDVI) was calculated using data acquired by UAV platform equipped with a multispectral camera. The NDVI was then confronted with data obtained from direct measurements on the vines and the berries (e.g., leaf area, yield, and technological berry ripening parameters). Gene expression analysis by microarrays was performed at five time points over berry development spanning from the green to the ripening phase.
Multivariate and correlation analyses were applied to determine the relationship between the vegetation index, the direct vine and berry measurements, and the gene expression information. Spatial variation in berry chemistry (e.g., total anthocyanins) followed a similar pattern to that seen in the vineyard aerial imagery in relation to the vigor zones. On top of this, relevant correlation trends were found also with the expression of the genes related to the berry compounds. Coupling multidisciplinary approaches to map intra-vineyard variability increases the potential of predicting fruit quality and of guiding targeted vineyard management.
Issue: ICGWS 2023
1 Department of Biotechnology, University of Verona, 37134 Verona, Italy
2 E. & J. Gallo Winery, Modesto, CA 95354, USA
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berry ripening, vegetation indices; gene expression analysis, sensors, precision viticulture