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This study evaluated the possibility of using two complementary electronic sensors (rising plate meter (RPM) and active optical sensor (AOS)) to obtain a global indicator, pasture crude protein (CP) in kg ha−1. This parameter simultaneously integrates two essential dimensions: pasture dry matter availability (dry matter (DM) in kg ha−1) measured by RPM, and pasture quality (measured by AOS), and supports management decisions, particularly those related to the stocking rates, supplementation, or rotation of animals between grazing parks. The experimental work was carried out on a dryland biodiverse and representative pasture, and consisted of sensor measurements, followed by the collection of a total of 144 pasture samples, distributed between three dates of the pasture vegetative cycle of 2023/2024 (Autumn—December 2023; Winter—February 2024; and Spring—May 2024). These samples were subjected to laboratory reference analysis to determine DM and CP. Sensor measurements (compressed height (HRPM) in the case of RPM, and normalized difference vegetation index (NDVI) in the case of AOS) and the results of reference laboratory analysis were used to develop prediction models. The best correlations between CP (kg ha−1) and "HRPM × NDVI" were obtained in the initial and intermediate phases of the cycle (autumn: R2 = 0.86 and LCC = 0.80; and Winter; R2 = 0.74 and LCC = 0.81). In the later phase of the cycle (spring), the accuracy of the forecasting model decreased dramatically (R2 = 0.28 and LCC = 0.42), a trend that accompanies the decrease in the pasture moisture content (PMC) and CP. The results of this study show not only the importance of extending the database to other pasture types in order to enhance the process of feed supplement determination, but also the potential for the research and development of proximal and remote sensing tools to support pasture monitoring and animal production management. [ABSTRACT FROM AUTHOR]

This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a "Grassmaster II" capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha−1). The sampling process consisted of sensor measurements, followed by pasture collection and a laboratory reference analysis. In this comparative study, carried out throughout the 2023/2024 pasture growing season, a total of 288 pasture samples were collected in two phases (calibration and validation). The calibration phase (n = 144) consisted of measurements on three dates (6 December 2023, 29 February and 10 May 2024) in 48 georeferenced sampling areas of the experimental field "Eco-SPAA" ("MG" field), located at Mitra farm (Évora, Portugal). This pasture is a permanent mixture of various botanical species (grasses, legumes, and others) grazed by sheep, and is representative of biodiverse dryland pastures. The validation phase (n = 144) was carried out between December 2023 and April 2024 in 18 field tests (each with eight pasture samples), in three types of representative pastures: the same mixture for grazing ("MG" field), a commercial and annual mixture for cutting (mowing) and conservation ("MM" field), and legumes for grazing ("LG" field). The best estimation model for DM was obtained based on measurements carried out in February in the case of the GMII probe (R2 = 0.61) and December 2023 and February 2024 in the case of RPM (R2 = 0.76). The estimation decreased very significantly for both sensors based on measurements carried out in May (spring). The validation phase showed greater accuracy (less RMSE) in "MG" field tests (RMSE of 735.4 kg ha−1 with GMII and 512.3 kg ha−1 with the RPM). The results open perspectives for other works that would allow the testing, calibration, and validation of these electronic sensors in a wider range of pasture production conditions, in order to improve their accuracy as decision-making support tools in pasture management. [ABSTRACT FROM AUTHOR]

The increasing variability of precipitation, higher temperatures, and recurring droughts in the semi-arid regions due to climate change are leading to increased aridity, resulting in scarcer water resources for crops. The present study aimed to analyse the spatial distribution of climate variables related to water resources in the olive-growing areas throughout Extremadura, southwestern Spain. To perform this task, three climate variables were used: the potential evapotranspiration of the crop, the FAO aridity index, and the annual water requirement. Considering data from 58 weather stations located throughout Extremadura and 17 along boundaries with at least a 30-year length (within the 1991–2021 period), each variable was computed at each station. After calculating some descriptive statistics, a multivariate geostatistical (regression-kriging) algorithm, incorporating secondary information on elevation and latitude, was used to accurately map each climate variable. Later, temporal trends and their magnitude were analysed using the Mann–Kendall test and the Sen's estimator, respectively. The highest evapotranspiration and water requirements are located in the southern part of the region, which has large areas dedicated to olive cultivation. In the northern part of the region, there is greater spatial variability in evapotranspiration and, consequently, in water requirements for olive groves due to the more rugged topography. Similarly, the olive-growing areas with the highest aridity are also in the south of Extremadura. In most areas of Extremadura, olive cultivation requires appropriate irrigation for optimal productivity. According to evapotranspiration trends, the water requirements will become greater in the future. However, it is not guaranteed that the water supply will be sufficient in olive-growing areas where aridity is higher and water resources are scarce. The results of this study are very important for evaluating water deficit and water resources in vulnerable olive-growing areas throughout Extremadura. [ABSTRACT FROM AUTHOR]

Irrigation efficiency is important for the environment and the economy. SIMDualKc has been effectively used to calculate evaporation and transpiration separately in vineyards for different irrigation strategies, but not to analyze the impact of irrigation frequency. This study was conducted for the in-field adjustment of the soil wetted fraction (wf) with a time domain reflectometry (TDR) sensor as a function of different irrigation frequency treatments (T03, T07, and T15 with irrigation every 3, 7, and 15 days, respectively). Evaporation and transpiration values were estimated separately with the SIMDualKc model for different irrigation frequencies with the adjusted wf, comparing them with vineyard field measurements and analyzing the effect of different irrigation frequencies on vineyard yield. The wf in T15 was higher than that in T07, which in turn was higher than that in T03. SIMDualKc indicates the most unfavorable treatment to be the T07, with higher evaporation and lower transpiration than T15 and T03, while T15 had higher evaporation and lower transpiration than T03. Although stomatic conductance also indicates the most unfavorable case to be T07, no clear differences were found between T03 and T15. No statistically significant differences were obtained in yield. The results indicate that the differences observed between irrigation frequencies are not reflected in yield but do show up in water use efficiency. [ABSTRACT FROM AUTHOR]

Water is a limiting factor and to adopt the most appropriate agronomic strategy it is necessary to know the water status. The objective is (i) analysing of the influence of different agronomic treatments on canopy temperature in vineyards with a thermal camera on an unmanned aerial vehicle (UAV), (ii) analysing of the influence of different agronomic treatments on vineyard water potentials with a pressure chamber, (iii) advanced technical feasibility analysis of vineyard crop monitoring. The control treatment (T07) in cv. Grenache consisted of applying 30% of reference evapotranspiration (ETo) with irrigation frequency every seven days and seven different treatments were proposed with different irrigation frequencies, pre-bud irrigation, and vine shoot distribution (T03, T15, T7A, T7V, T7P, T00, and T0P). As a result and in conclusion, the use of thermal cameras in UAVs and mid-day stem water potential allows differentiation between irrigated and unirrigated treatments, but no clear differences were shown between irrigation frequencies, pre-irrigation treatment, or vine shoot distribution. Comparing the thermal camera information in UAV and the stem water potential, certain patterns are identified with significant correlation values, the use of thermal cameras for the evaluation of plant water status is recommended, especially to obtain information in large areas. [ABSTRACT FROM AUTHOR]

In the current context of increasing costs of production factors, it is essential to optimize the management of available resources, seeking to incorporate technologies that improve knowledge of the variables involved in the agronomic production process. The aim of this study is to define and validate management zones (MZ) in a 3.3 ha vineyard located near Évora, in the South of Portugal. A contact sensor ("Veris 2000 XA") was used to map soil apparent electrical conductivity (ECa) and a precision altimetric survey of the field was carried out with a global navigation satellite system receiver (GNSS). The results of these surveys were submitted to geostatistical treatments that allowed the definition of three MZ (less, intermediate, and more productive potential). The validation of such MZ was carried out by laboratory analysis of soil samples (texture, pH, organic matter—OM, moisture content, phosphorous, potassium, exchange bases, and cation exchange capacity—CEC), measurements of soil compaction (cone index—CI) with an electronic cone penetrometer, and through indices (Normalized Difference Vegetation Index—NDVI, and Normalized Difference Water Index—NDWI) obtained by remote sensing (RS) using Sentinel-2 satellite images. All these parameters (soil parameters and RS indices) proved the validity of the MZ (of less, intermediate, and more productive potential) defined from the ECa and altimetric survey. This validation attests to the interest of expeditious technological tools for monitoring ECa as a fundamental step in implementing smart agronomic decision-making processes. [ABSTRACT FROM AUTHOR]

In recent years, different algorithms have been utilised to delineate management zones, areas with similar properties, within agricultural fields. However, there are few applications in pasture systems. In this work, the formulation of the Rasch model, as an objective and probabilistic technique to integrate different soil properties, provided measures of pasture soil fertility that were used to analyse spatial variability throughout a field. To illustrate the proposed approach, a case study was conducted in a pasture field. Ten soil properties (sand, silt, and clay contents, moisture content, pH, organic matter, nitrogen, phosphorus, potassium, and soil apparent electrical conductivity) were measured at 76 locations in a pasture field; after their integration in the model, a classification of all sampling locations according to pasture soil fertility was determined, and the influence of each soil property on the soil fertility was highlighted, with the soil moisture, clay, and sand contents and nitrogen being the most influential properties and the silt content being the least influential property. Then, an ordinary kriging algorithm was used to estimate pasture soil fertility throughout the field, and homogeneous zones were delimited from the kriged map. The possibility of using probability maps to determine management zones and provide information for hazard assessments of pasture soil fertility in the field was also shown. Finally, NDVI data at each sampling location were utilised to verify the differences between the management zones. [ABSTRACT FROM AUTHOR]

In the present study, the drying and combustion of solid biomass residues are developed. The combustion of the residues inside a boiler and a stove have been done. We used three types of solid biomass residues (i.e., cork, pine pellet and olive pomace). These residues have been dried by using screw dryers. Experimental installation has been used for a series of thermal drying tests of the residues by measuring the temperature inside the dryer and their moisture contents. A laboratory screw dryer was used to dry the olive pomace by using hot gases from a chimney of a biomass stove. Elemental and proximate analyses, as well as the higher heating value (HHV) of the raw materials, have been determined. In the experiments, moisture content variation of the residues and drying temperatures are obtained. These residues are dried several times under the same drying conditions to achieve the final moisture content rate. On the other hand, the temperature of combustion chamber of the boiler has been measured under different conditions. It has been found that by increasing hot gas temperature, the drying rate is increased. Finally, it has been found that the drying of these residues increases their calorific values and reduces the emissions. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the precipitation's spatial distribution pattern. The study uses various techniques to determine the altitude and measure the precipitation data including multivariate algorithms and simple kriging (SK), universal kriging, and ordinary kriging (OK) methods. Moreover, the study reveals that the algorithms are applicable in a geographical information system (GIS) to produce the final maps.