Extensive animal production in Iberian Peninsula is based on pastures, integrated within the important agro-silvo-pastoral system, named “montado” in Portugal and “dehesa” in Spain. Temperature and precipitation are the main driving climatic factors affecting agricultural productivity and, in dryland pastures, the hydrological cycle of soil, identified by soil moisture content (SMC), is the main engine of the vegetation development. The objective of this work was to evaluate the normalized difference water index (NDWI) based on Sentinel-2 imagery as a tool for monitoring pasture seasonal dynamics and inter-annual variability in a Mediterranean agro-silvo-pastoral system. Forty-one valid NDWI records were used between January and June 2016 and between January 2017 and June 2018. The 2.3 ha experimental field is located within the “Mitra” farm, in the South of Portugal. Soil moisture content, pasture moisture content (PMC), pasture surface temperature (T_ir), pasture biomass productivity and pasture quality degradation index (PQDI) were evaluated in 12 satellite pixels (10 m × 10 m). The results show significant correlations (p < 0.01) between NDWI and: (i) SMC (R² = 0.7548); (ii) PMC (R² = 0.8938); (iii) T_ir (R² = 0.5428); (iv) biomass (R² = 0.7556); and (v) PQDI (R² = 0.7333). These findings suggest that satellite-derived NDWI can be used in site-specific management of “montado” ecosystem to support farmers’ decision making.

Montado is an agro-forestry system occupying a large surface in countries of the Mediterranean region. In this system, the natural dryland pasture is the principal source for animal feed in extensive grazing. The climatic seasonality associated with the inter-annual irregularity of precipitation greatly influences the development of pasture and its vegetative cycle. The end of spring is a critical period in terms of animal feed due to the notable reduction in the nutritive value of the plants. The objective of this work was to evaluate, through the correlation between pasture quality indexes (Pasture Quality Degradation Index, PQDI and Normalized Difference Vegetation Index, NDVI), two technological approaches for monitoring the evolution of the quality of a biodiverse pasture in the period of greatest vegetative development (between February and June). The technological approaches consisted of (i) proximal sensing (PS), with the use of an active optical sensor; and (ii) remote sensing (RS), using images captured by a Sentinel-2 satellite. The results of this study show strong and significant correlations between PQDI and NDVI (obtained by PS or RS). These two techniques (PS or RS) can, therefore, be used in a complementary way to identify and anticipate the food supplementation needs for animals and support farmers in decision making.

The main objective of this study was to compare two apparent soil electrical conductivity (EC_a) sensors (Veris 2000 XA and DUALEM 1S) for mapping variability of soil properties in a Mediterranean shallow soil. This study also aims at studying the effect of soil cover vegetation on the EC_a measurement by the two types of sensors. The study was based on two surveys carried out under two very different situations: in February of 2012, with low soil moisture content (SMC) and with high and differentiated vegetation development (non grazed pasture), and in February of 2013, with high SMC and with short and relatively homogeneous vegetation development (grazed pasture). The greater temporal stability of Veris sensor, despite the wide variation in the SMC and vegetation ground cover indicates the suitability of using this sensor for monitoring soil properties in permanent pastures. The survey carried out with the DUALEM sensor in 2012 might have been affected by the presence of a 0.20 m vegetation layer at the soil surface, masking the soil properties. These differences should be considered in the selection of EC_a sensing systems for a particular application.

The aim of this study was to identify the importance assigned by futsal coaches with different education levels to the sports performance factors (technical, tactical, physical and psychological) and to the training contents. The sample was divided into three groups (novice: n=35, intermediate: n=42; and elite coaches: n=15) depending on the degree of specific education, coaching experience and the level of the teams trained. To achieve this goal, the coaches answered a questionnaire previously validated by specialists in sport sciences. The results showed significant differences between the novice and elite group in small-sided games, inferiority games, opposition and execution timing of the training and drill items. The analyses also showed significant differences between the novice and intermediate group in inferiority games and opposition of the training and drill items. Although, no differences were identified between groups for the remaining performance factors and training and drill items considered, the identified trends provide a baseline related to the knowledge that contributes to the development of expertise of futsal coaches.