Abstract
Currently, we are facing increasingly environmental issues affecting our cities and consequently the health of living beings. A practical example it's the pollution, the excess of different odors and gases. Thus, our project is to create a sensor integrated in a smart grid that can measure gas pollution. This new sensor has the ability of detecting and classification of different odors that reflect the air quality in a given space.

Abstract
Several vegetation indices (VI) derived from handheld spectroradiometer reflectance data in the visible spectral region were tested for modelling grapevine water status estimated by the predawn leaf water potential ((pd)). The experimental trial was carried out in a vineyard in Douro wine region, Portugal. A statistical approach was used to evaluate which VI and which combination of wavelengths per VI allows the best correlation between VIs and (pd). A linear regression was defined using a parameterization dataset. The correlation analysis between (pd) and the VIs computed with the standard formulation showed relatively poor results, with values for squared Pearson correlation coefficient (r(2)) smaller than 0.67. However, the results of r(2) highly improved for all VIs when computed with the selected best combination of wavelengths (optimal VIs). The optimal Visible Atmospherically Resistant Index (VARI) and Normalized Difference Greenness Vegetation Index (NDGI) showed the higher r(2) and stability index results. The equations obtained through the regression between measured (pd) ((pd_obs)) and optimal VARI and between (pd_obs) and optimal NDGI when using the parameterization dataset were adopted for predicting (pd) using a testing dataset. The comparison of (pd_obs) with (pd) predicted based on VARI led to R-2 = 0.79 and a regression coefficient b = 0.96. Similar R-2 was achieved for the prediction based on NDGI, but b was smaller (b = 0.93). Results obtained allow the future use of optimal VARI and NDGI for estimating (pd), supporting vineyards irrigation management.

Abstract
The Diagnosis and Recommendation Integrated System (DRIS) is an alternative tool for the evaluation of nutritional status and fertilizer recommendation of several crops. However, as this methodology implies the establishment of norms or standards, without which one cannot infer about the nutritional status of a crop, in Portugal this tool has little application. The aim of this study was to establish preliminary DRIS norms for vineyards in Portugal. From 2007 to 2009, petiole samples were collected on a set of 199 selected plots. The DRIS norms were established according to the proposed by Beaufils (1973), based on the results of the laboratory procedures. The results suggest the need for further studies in order to validate the DRIS norms presented. In the future it will be important to increase the number of observations for the establishment of DRIS norms, as well as to determine the relevance of establishing specific nutritional standard according the edaphic, climatic and varietal variability of Portuguese wine regions.

Abstract
A new procedure is proposed for estimating actual basal crop coefficients from vegetation indices (K-cb VI) considering a density coefficient (K-d) and a crop coefficient for bare soil. K-d is computed using the fraction of ground cover by vegetation (f(c VI)), which is also estimated from vegetation indices derived from remote sensing. A combined approach for estimating actual crop coefficients from vegetation indices (K-c VI) is also proposed by integrating the K-cb VI with the soil evaporation coefficient (K-e) derived from the soil water balance model SIMDualKc. Results for maize, barley and an olive orchard have shown that the approaches for estimating both f(c VI) and K-cb VI compared well with results obtained using the SIMDualKc model after calibration with ground observation data. For the crops studied, the correlation coefficients relative to comparing the actual K-cb VI and K-c VI with actual K-cb and K-c obtained with SIMDualKc were larger than 0.73 and 0.71, respectively. The corresponding regression coefficients were close to 1.0. The methodology herein presented and discussed allowed for obtaining information for the whole crop season, including periods when vegetation cover is incomplete, as the initial and development stages. Results show that the proposed methods are adequate for supporting irrigation management.

Abstract
Aims: The main goal of this work was to describe the genetic diversity and population structure of Portuguese isolates from Erysiphe necator using a new approach for the sampling of DNA from this pathogen. Methods and results: The present study was conducted in the main demarcated wine regions of Portugal, where leaf and berry samples were collected for further genetic analysis. After DNA extraction, the Internal Transcribed Spacer from the 18S ribosomal RNA (ITS), the Intergenic Spacer (IGS), and the beta-tubulin gene were successfully amplified and sequenced. The populations of E. necator are structured into two genetically distinct groups (A and B), with the majority of the analyzed samples belonging to group B. Conclusion: Regardless of its geographical origin and the Vitis vinifera cultivar, the population of E. necator presents low genetic diversity. Significance and impact of the study: The present work will certainly help to increase the vineyard productivity through a better definition of preventive measures and a potential decrease in the direct and indirect costs associated with the use of fungicides.

Abstract
Airborne pollen emission model was used to determine pollen metrics and to examine their relationship with vineyard phenology in two wine regions of Northern Portugal: Vinhos Verdes (1993-2007) and Douro (1992-2011). A number of airborne pollen metrics were obtained through the rate of changes of logistic model adjusted to the time series of airborne pollen. In both regions, the mean absolute differences between observed phenology and model-predicted values for start, peak and final of flowering phenophases were always lower than 5 days and the slope of the regression through the origin is close to one. These metrics can be used to accurately and precisely predict the dynamic of Vitis flowering observed at field level. The model's simplicity and flexibility are of great advantage for its practical use in aerobiology.