João Serrano

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest in incorporating technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, south of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture; pH; organic matter—OM; phosphorous—P2O5; potassium—K2O; the sum of the exchange bases—SEB; and cation exchange capacity—CEC), which were determined from 20 soil samples taken in the different MZs. Validation was also performed using Rasch measures, which were defined based on the formulation of the objective and probabilistic Rasch model, integrating the information from the aforementioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. Finally, an additional validation was conducted using a vegetation index to consider the plant response, which was different in each MZ. The use of a non-contact sensor to measure ECa constitutes an efficient technological tool for implementing site-specific management in viticulture, which allows for the improvement of decision-making processes by considering the inherent spatial variability of the soil.

Permanent dryland pastures are the basis of animal feed in extensive grazing systems. Seasonality and inter-annual climatic variability, associated with shallow, acidic, and not very fertile soils, result in low productivity and rapid degradation of pasture quality, which requires the supplementation of animal feed. In this study, carried out in a biodiverse pasture field in the Mediterranean region of southern Portugal, the vegetation index (NDVI, Normalized Difference Vegetation Index) obtained from measurements performed by a proximal optical sensor (PS) and satellite images (RS) was used to assess pasture quality parameters (pasture moisture content, PMC, crude protein, CP, and neutral detergent fiber, NDF). The monitoring was carried out throughout the 2021/2022 pasture growing season. Significant correlations were obtained between the NDVI obtained by PS and RS (R2 of 0.84) and the reference values of pasture parameters obtained in laboratory protocols: PMC (R2 of 0.88 and 0.78, respectively), CP (R2 of 0.67 and 0.63, respectively), and NDF (R2 of 0.50 and 0.46, respectively). This case study also demonstrated the spatial and temporal variability of vegetative vigour and, consequently, of pasture quality in the Montado, the characteristic Mediterranean ecosystem. These results show the pertinence of these technologies in supporting the decision-making process of the farm manager, namely, to estimate the supplementation needs of animals in critical phases, especially after the spring production peak and before the autumn production peak.