Vine field monitoring using high resolution remote sensing images: segmentation and characterization of rows of vines

There has been a shift in modern industry to implement non-destructive and non-invasive process monitoring techniques (Helmdach et al., 2013).

Sauvignon blanc was first planted in Marlborough, New Zealand in the mid-1970s. Since that time, Marlborough has gained an international reputation by producing the definitive wine style of that grape variety.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

In 2001, the Hungarian Ministry of Agriculture and Rural Development designated the Institute of Geodesy, Cartography and Remote Sensing (FÖMI) to elaborate a Geographic Information System (GIS) supported Vineyard Register (VINGIS) in Hungary. The basis of this work was a qualification methodology (vineyard and wine cellar cadastre system) dating back to several decades, however, in the 1980s and 1990s the available geographical maps and information technology did not provide enough accuracy for an overall evaluation of viticultural areas. The reason for the VINGIS elaboration and development was an obligation resulting from the EU membership to ensure the agricultural subsidies for the wine–viticulture sector.

In the context of climate change and for the sustainable exploitation of Mediterranean vineyards, it is necessary to use new strategies to adapt to the new climatic conditions.