The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility ($K$ factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

Evapotranspiration can be used to estimate the amount of water required by agriculture projects and green spaces, playing a key role in water management policies that combat the hydrological drought, which assumes a structural character in many countries. In this context, this work presents a study on reference evapotranspiration ( ET_o ) estimation models, having as input limited meteorological parameters, namely: temperature, humidity, and wind. Since solar radiation (SR) is an important parameter in the determination of ET_o , SR estimation models are also developed. These ET_o and SR estimation models compare the use of Artificial Neural Networks (ANN), Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and hybrid neural network models such as LSTM-ANN, RNN-ANN and GRU-ANN. Two main approaches were taken for ET_o estimation: (i) directly use those algorithms to estimate ET_o , and (ii) estimate solar radiation first and then use that estimation together with other meteorological parameters in a method that predicts ET_o . For the later case, two variants were implemented: the use of the estimated solar radiation as (ii.1) a feature of the neural network regressors, and (ii.2) the use of FAO-56PM method to compute ET_o , which has solar radiation as one of the input parameters. Using experimental data collected from a weather station (WS) located in Vale do Lobo (Portugal), the later approach achieved the best result with a coefficient of determination ( R ² ) of 0.977. The developed model were then applied to data from eleven stations located in Colorado (USA), with very distinct climatic conditions, showing similar ( R ² > 0.95) results to the ones for which the models were initially designed, proving a good generalization. As a final notice, the reduced-set features were carefully selected so that they are compatible with free online weather forecast services.

The aerial parts of wild Thymus mastichina (L.) L. ssp. mastichina were collected during the flowering (May) and vegetative phases (October) at Sesimbra (southwest Portugal). The aerial parts of cultivated plants of T. mastichina maintained in two different substrates, obtained from those plants growing wild at Sesimbra, were collected during the flowering phase (May) at Algarve (southern Portugal). The oils were isolated by hydrodistillation and analyzed by GC and GC/MS. In the wild plants, it was found that harvesting time had a significant effect on the oil yield, but did not greatly affect the composition. The highest oil yield isolated from the wild plants was found to be at the time of full flowering (2.1%, v/w). The oils were comprised mainly of oxygenated monoterpenes, among which linalool (58.7–69.0%) was the most abundant. In the wild plants, α-pinene, (E)-β-ocimene, γ-cadinene and elemol were the compounds that showed the most important variations, according to the harvesting month. The effect of nutritive elements (NPK) on the yield and on the oil composition was investigated in cultivated plants in two different substrates: a non-fertilized substrate (without N:P:K supply) and a fertilized substrate (with N:P:K, 1:1:1 supply). This study was carried out only in May. In the cultivated plants the highest oil yield (2.7%, v/w) was registered in the plants maintained in the non-fertilized substrate. Although the qualitative composition of the wild and cultivated oil plants was similar, the results showed quantitative variability among the components. The fertilized substrate proved to be the best to obtain a higher concentration of linalool (69.0%), while the non-fertilized substrate provided the lowest percentage (58.7%). The non-fertilized substrate induced a higher accumulation of (E)-β-ocimene, γ-terpinene, sesquiterpene hydrocarbons and oxygenated sesquiterpenes than the fertilized substrate, while this latter supported higher p-cymene and linalool content formation. The wild plant oils were found to be richer in α-pinene, camphene, β-pinene, 1,8-cineole and camphor and poorer in p-cymene, γ-terpinene, and in sesquiterpene hydrocarbons and oxygenated sesquiterpenes, than the cultivated plant oils. Nevertheless, such quantitative differences can be also explained by the different maturity stage of the wild and cultivated plants though both were in the same developmental stage.

ISHS II WOCMAP Congress Medicinal and Aromatic Plants, Part 2: Pharmacognosy, Pharmacology, Phytomedicine, Toxicology ANTIMICROBIAL ACTIVITY OF ESSENTIAL OILS OF ROSMARINUS OFFICINALIS L., THYMUS MASTICHINA (L) L. SSP MASTICHINA AND THYMUS ALBICANS HOFMANNS & LINK

Algarve region (Portugal) has nearly 40 golf courses with a significant economic impact. Summer surveys on ten golf courses detected an unknown disease on one course in 2009, and on another course ...