Auxiliary Companies of the Horticultural Sector as a Competitiveness Element: The Case of Almeria (Spain)

The horticultural model of Almeria (Spain) based on the operation of greenhouses is an international reference and has been considered as an economic miracle. Alongside this agricultural development has been the deployment of the diverse productive activity of auxiliary companies. The objective of this article is to understand how these companies operate and analyze their factors of competitiveness, competing needs, and future competitive improvements, taking as reference four of the most important subsectors (machinery, greenhouse infrastructure, plastics, and seeds). The Delphi method was used and through a panel of experts the conditioning factors of each of the variables to be analyzed (factors, needs, and competitiveness improvements) was chosen. Of the 120 companies that were sent questionnaires, 72 participated. The sectors that make up the auxiliary companies are heterogeneous and therefore the results obtained have differed among them. The synergies between the greenhouse crops and the auxiliary companies are an example of diversification of productive activity that can be extrapolated to other production areas worldwide. The future of the auxiliary companies is linked to that of the intensive agriculture and the key variables must be underscored by competitiveness and sustainability

A Look at the Past, Present and Future Research Trends of Artificial Intelligence in Agriculture

Technification in agriculture has resulted in the inclusion of more efficient companies that have evolved into a more complex sector focused on production and quality. Artificial intelligence, one of the relevant areas of technology, is transforming the agriculture sector by reducing the consumption and use of resources. This research uses a bibliometric methodology and a fractional counting method of clustering to analyze the scientific literature on the topic, reviewing 2629 related documents recorded on the Web of Science and Scopus databases. The study found significant results regarding the most relevant and prolific authors (Hoogenboom), supporting research organizations (National Natural Science Foundation of China) and countries (U.S., China, India, or Iran). The identification of leaders in this field gives researchers new possibilities for new lines of research based on previous studies. An in-depth examination of authors’ keywords identified different clusters and trends linking Artificial Intelligence and green economy, sustainable development, climate change, and the environment

Local Development and Gentrification Resulting from the Rehabilitation of Singular Buildings: Analysis of Neural Networks

The recovery of a built heritage and specifically of singular buildings is a key aspect of local development. The aim of this study was to understand the influence of these regenerations on their environment by transforming adjacent businesses and initiating parallel processes of gentrification and local development. The renewed attraction of these new businesses to the area can result in increased employment and production. The methodology used was based on self-organizing maps of neural networks with matrix architecture and competitive learning. Through the analysis of neural networks, we were able to identify common relationships and behaviors in commercial properties which are adjacent to singular buildings and that share common patterns and characteristics or attributes. The singular buildings analyzed are located along the Spanish Mediterranean coast in the cities of Almería, Barcelona, and Valencia. The results obtained were based on the following hypotheses: occupancy model and the classification based on total occupancy, total variation in occupancy, and the most common types of usage of a given ground floor commercial property. Among the conclusions, we highlight the existence of commercial premises that display anti-cyclical economic behavior and the presence of commercial premises considered to be “unfortunate” or with low potential

Combination of image processing and artificial neural networks as a novel approach for the identification of Bemisia tabaci and Frankliniella occidentalis on sticky traps in greenhouse agriculture

Integrated Pest Management (IPM) lies at the core of the current efforts to reduce the use of deleterious chemicals in greenhouse agriculture. IPM strategies rely on the early detection and continuous monitoring of pest populations, a critical task that is not only time-consuming but also highly dependent on human judgement and therefore prone to error. In this study, we propose a novel approach for the detection and monitoring of adult-stage whitefly (Bemisia tabaci) and thrip (Frankliniella occidentalis) in greenhouses based on the combination of an image-processing algorithm and artificial neural networks. Digital images of sticky traps were obtained via an image-acquisition system. Detection of the objects in the images, segmentation, and morphological and color property estimation was performed by an image-processing algorithm for each of the detected objects. Finally, classification was achieved by means of a feed-forward multi-layer artificial neural network. The proposed whitefly identification algorithm achieved high precision (0.96), recall (0.95) and F-measure (0.95) values, whereas the thrip identification algorithm obtained similar precision (0.92), recall (0.96) and F-measure (0.94) values

Effects of ventilator configuration on the flow pattern of a naturally-ventilated three-span Mediterranean greenhouse

Natural ventilation used in agricultural greenhouses is important to control greenhouse microclimate. The effect of the ventilator configuration on the flow pattern of a three-span Mediterranean greenhouse with an obstacle to airflow (a neighbouring greenhouse) was investigated. Two different ventilator configurations, two or three half-arch roof vents with two roll-up side vents, were evaluated using sonic anemometry. It was observed that the flow pattern through the greenhouse depends of the ventilation surfaces distribution and the obstruction to the ventilation system. Moreover, the magnitude and distribution of ventilation surface affected the overall ventilation rate and the ventilation rate at plant level. The ventilator configuration with two roof and two side vents improved air movement at the plant level, although the overall volumetric flow rate was lower than that with three roof and two side vents

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Triangulation Applied to the Intra-European Union Tomato Market

An understanding of the intracommunity trade is essential for the agents involved in the fresh tomato market (farmers, entrepreneurs, public administrations, and consumers). The purpose of this paper is to analyze the interdependent relationships between exporting and importing countries within the European Union for a specific product such as fresh tomatoes and thus understand which have been the key countries in three specific years (2002–2007–2017). The methodology used to study the interrelationships of trade flows in the countries of the European Union (EU) is that of triangulation by means of the Leontief input-output model. Artificial intelligence techniques are used to process and triangulate the data based on pathfinding techniques using a cost function. The triangulation results have created a hierarchy of countries (suppliers and customers). This type of methodology has not been applied to the field of foreign trade. The results show that Netherlands and Spain are key countries in intracommunity trade as they have a strong impact both with regard to their exports and their imports and are fundamental when analyzing the growth of specific sectors and how they are able to stimulate the economies of other countries

An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology

Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of <0.06 m·s‾1 for airflow speed and <0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points