Viticulture is facing emerging challenges not only because of the effect of climate change on yield and composition of grapes, but also of a social demand for environmental‐friendly agricultural management. Adaptation to these challenges is essential to guarantee the sustainability of viticulture. The aim of this review is to present adaptation possibilities from the soil‐hidden, and often disregarded, part of the grapevine, the roots. The complexity of soil–root interactions makes necessary a comprehensive approach taking into account physiology, pathology and genetics, in order to outline strategies to improve viticulture adaptation to current and future threats. Rootstocks are the link between soil and scion in grafted crops, and they have played an essential role in viticulture since the introduction of phylloxera into Europe at the end of the 19th century. This review outlines current and future challenges that are threatening the sustainability of the wine sector and the relevant role that rootstocks can play to face these threats. We describe how rootstocks along with soil management can be exploited as an essential tool to deal with the effects of climate change and of emerging soil‐borne pests and pathogens. Moreover, we discuss the possibilities and limitations of diverse genetic strategies for rootstock breeding.

Canopy management operations, such as shoot thinning, leaf removal, and shoot trimming, are among the most relevant agricultural practices in viticulture. However, the supervision of these tasks demands a visual inspection of the whole vineyard, which is time-consuming and laborious. The application of photogrammetric techniques to images acquired with an Unmanned Aerial Vehicle (UAV) has proved to be an efficient way to measure woody crops canopy. Consequently, the objective of this work was to determine whether the use of UAV photogrammetry allows the detection of canopy management operations. A UAV equipped with an RGB digital camera was used to acquire images with high overlap over different canopy management experiments in four vineyards with the aim of characterizing vine dimensions before and after shoot thinning, leaf removal, and shoot trimming operations. The images were processed to generate photogrammetric point clouds of every vine that were analyzed using a fully automated object-based image analysis algorithm. Two approaches were tested in the analysis of the UAV derived data: (1) to determine whether the comparison of the vine dimensions before and after the treatments allowed the detection of the canopy management operations; and (2) to study the vine dimensions after the operations and assess the possibility of detecting these operations using only the data from the flight after them. The first approach successfully detected the canopy management. Regarding the second approach, significant differences in the vine dimensions after the treatments were detected in all the experiments, and the vines under the shoot trimming treatment could be easily and accurately detected based on a fixed threshold.