The characterization of vineyard soil is a key issue for crop management, which directly affects the quality and yield of grapes. However, traditional laboratory analysis of soil properties is tedious and both time and cost consuming, which is not suitable for precision viticulture. For this reason, a fast and convenient soil characterization technique is needed for soil quality assessment and precision soil management. Here, spectroscopy appears as a suitable alternative to assist laboratory analysis. This work focuses on estimating soil properties by spectroscopy. Our study was carried out using 96 soil samples collected from three vineyards in Rias Baixas Designation of Origen (Galicia, Spain). The soils that were characterized include nitrogen (N), organic matter (OM) and clay content (Clay). The presented work compared two regression techniques (partial least squares (PLSR) and random forest (RF)) and four spectral ranges: visible—VIS (350–700 nm), near infrared—NIR (701–1000 nm), short wave infrared—SWIR (1001–2500 nm) and VIS-NIR-SWIR (350–2500 nm) in order to identify the more suitable prediction models. Moreover, the effect of pre-treatments in reflectance data (smoothing Svitzky–Golay, SG, baseline normalization, BN, first derivative, FD, standard normal variate, SNV, logarithm of 1/reflectance or spectroscopy (SP) and detrending, SNV-D) was evaluated. Finally, continuous maps of the soil properties were created based on estimated values of regression models. Our results identified PLSR as the best regression technique, with less computation time than RF. The data improved after applying transformation in reflectance data, with the best results from spectroscopy pre-treatment (logarithm of 1/Reflectance). PLSR performances have obtained determination coefficients (R²) of 0.69, 0.73 and 0.52 for nitrogen, organic matter, and clay, respectively, with acceptable accuracy (RMSE: 0.03, 1.06 and 2.90 %) in a short time. Furthermore, the mapping of soil vineyards generates information of high interest for the precision viticulture management, as well as a comparison between the methodologies used.

Water erosion is a severe threat to soil resources, especially on cultivated lands, such as vineyards, which are extremely susceptible to soil losses. In this context, management practices aiming at reducing erosion risks must be favored. This current study aimed at estimating soil losses in two vineyards under Atlantic climatic conditions (Galicia, North West Spain). The capacity of two management practices for reducing soil erosion was tested and compared with tilled soil in the inter-rows: (i) application of mulching, and (ii) maintaining native vegetation. Soil losses were assessed using erosion pins and micro-plots. In addition, the improved stock unearthing method (ISUM) was employed in one of the vineyards to estimate soil remobilization since plantation. Soil loss rates in one of the vineyards were lower when soil was managed under mulching (0.36 Mg ha⁻¹) and native vegetation (0.42 Mg ha⁻¹), compared to tilled soil (0.84 Mg ha⁻¹). Sediment losses measured in the second vineyard ranged between 0.21 and 0.69 Mg ha⁻¹, depending on the treatment, but no clear conclusions could be drawn. Long-term soil loss, as estimated by ISUM, was of the same order of magnitude than that obtained by erosion pins and micro-plots. In both vineyards, soil loss rates were lower than those registered in Mediterranean vineyards, and were below the limit for sustainable erosion in Europe. Nevertheless, soil management practices alternative to tillage in the inter-row might reduce erosion risks under Atlantic climate conditions.

Soil properties show a high spatio-temporal variability, affecting productivity and crop quality within a given field. In new vineyard plantations, with changes in the initial topographic profile, this variability is exacerbated due to the incorporation of soil from different origins and qualities. The aim of the current study was to characterize the variability of soil properties in a newly established vineyard, and delineating zones for site-specific management of fertilization. For this purpose, the soil apparent electrical conductivity (EC_a) in the first 150 cm was measured with an electromagnetic induction sensor. A soil sampling was performed following a regular grid (35 × 35 m, 149 samples), collecting samples down to 40 cm depth for determining soil chemical properties. Spatial variability was assessed through semivariogram calculation and ordinary kriging. The soil properties that better represent the variability in this newly established vineyard were pH, effective cation exchange capacity (ECEC), carbon content, clay and EC_a. The EC_a was homogeneous all over the vineyard, except for the area closer to the river where a greater human intervention had occurred, with contributions of external soil at a greater depth. Soil properties showed a great spatial variability. Interpolated maps allowed for detecting areas with a lack of nutrients in which a differential fertilization could be performed in search of a sustainable and balanced production. The information provided by the maps of pH, ECEC and carbon and potassium contents allow for performing a differential management of the vineyard in terms of fertilization. In addition, the results obtained suggest that the vineyard should be divided into two sectors for a differential irrigation management. The EC_a was not significantly correlated to most of the soil properties determined in the current study; however, it allowed for a low-cost mapping of the vineyard soil and established large areas of management within the vineyard.