Abstract
Olive trees are one of the most economically important perennial crops in Portugal. During the last decade, the Alentejo olive-growing region has suffered a significantly change in the crop production system, with the regional pollen index (RPI) and olive fruit production registering a significant growth. The aim of this study was to ascertain the utility of this highly variable production and pollen data in crop forecasting modeling. Airborne pollen was sampled using a Cour-type trap from 1999 to 2015. A linear regression model fitted with the regional pollen index as the independent variable showed an accuracy of 87% in estimating olives fruit production in Alentejo. However, the average deviation between observed and modeled production was 32% with half of the tested years presenting deviations between 36 and 66%. The low accuracy of this model is a consequence of the great overall variation and significant upward trend observed in both the production and the RPI dataset that conceal the true association between these variables. In order to overcome this problem, a detrend procedure was applied to both time series to remove the trend observed. The regression model fitted with the fruit production and the RPI detrended data showed a lowest forecasting accuracy of 63% but the average deviation between observed and modeled production decrease to 14% with a maximum deviation value of 33%. This procedure allows focusing the analysis on the production fluctuations related to the biological response of the trees rather than with the changes in the production system.

Abstract
Surveillance missions in vast, difficult access environments are responsible for logistic difficulties in comparison to using an in loco monitoring team. For this and many other reasons, solutions with robotic platforms such as unmanned aerial vehicles (UAVs), present economic advantages. © 1986-2012 IEEE.

Abstract
Unmanned Aerial Vehicles (UAVs) have become a prominent research field due to their vast applicability and reduced size. An appealing aspect of theUAVs is the ability to accomplish autonomous flights in several contexts and purposes, and a variety of applications have been developed, from military to civilian fields. The system proposed in this work is a novel and simplified interaction between the user and the UAV for autonomous flight, where the necessary computation is performed in an embedded computer, decreasing response time and eliminating the necessity of long-distance communication links with base stations. Results are presented with both hardware in the loop simulations and a real UAV using Pixhawk, and Odroid and ROS as companion computer and software platform for code development. © Springer International Publishing Switzerland 2017.

Abstract
Fourier transform infrared spectroscopy has been applied in tandem with multivariate statistical approaches, with the prospect of developing a methodology for the prediction of interesting traits in distinct clones of “Olea europaea L.” For this purpose, the infrared spectra of either the drupes or the corresponding olive oils of 6 distinct clones of the Cobrançosa cultivar, in 2 ripening stages (semi-ripe and ripe), have been registered resorting to an attenuated total reflection accessory. These clones were previously evaluated with respect to antioxidant activity and olive oil yield, while multivariate analyses, namely, partial least squares regression and discriminant analysis have been applied to the spectral data collected to obtain a prediction model for the assessment of these traits in distinct clones through the infrared spectra. This methodology leads to minimal erroneous classification rates in the validation procedure of 3.9% and 6.3% for olives and olive oils, respectively, using the first derivative of the spectra. Thus, the suitability of this methodology for the assessment of different clones has been shown with visible benefits for a time consuming and costly process such as clonal selection. Furthermore, this procedure might be extended for other cultivars or different species once proper calibration models are attained for each matrix. Copyright © 2017 John Wiley & Sons, Ltd.

Abstract
Olive oil displays remarkable organoleptic and nutritional features, which turn it into a foodstuff appreciated by consumers, and a basic component of the Mediterranean diet. Indeed, the noticed benefits of including olive oil in the diet have been assigned to the presence of diverse bioactive compounds with different molecular structures. These compounds confer a wide range of biological properties to this food matrix, including the prevention of distinct human diseases as well as the modulation of their severity. The most relevant bioactive compounds present in olive oil correspond to benzoic and cinnamic acids, phenolic alcohols and secoiridoids, and also flavonoids. Over the last decades, several studies, devoted to gaining a further insight into the relative contribution of the separate groups and individual compounds for their biological activities, have been conducted, providing relevant information on structure-activity relationships. Therefore, this paper critically reviews the health benefits evidenced by distinct phenolic compounds found in olive oils, thus contributing to clarify the relationship between their chemical structures and biological functions, further supporting their interest as essential ingredients of wholesome foods.

Abstract
Grape and wine phenolics display a noticeable structural diversity, encompassing distinct compounds ranging from simple molecules to oligomers, as well as polymers usually designated as tannins. Since these compounds contribute critically to the organoleptic properties of wines, their analysis and quantification are of primordial importance for winery industry operators. Besides, the occurrence of these compounds has been also extensively described in winery residues, which have been pointed as a valuable source of bioactive phytochemicals presenting potential for the development of new added value products that could fit the current market demands. Therefore, the cumulative knowledge generated during the last decades has allowed the identification of the most promising compounds displaying interesting biological functions, as well as the chemical features responsible for the observed bioactivities. In this regard, the present review explores the scope of the existing knowledge, concerning the compounds found in these winery by-products, as well as the chemical features presumably responsible for the biological functions already identified. Moreover, the present work will hopefully pave the way for further actions to develop new powerful applications to these materials, thus, contributing to more sustainable valorization procedures and the development of newly obtained compounds with enhanced biological properties.