In vitro propagation of insectivorous plants for phytochemical purposes

Dissertação mest., Engenharia Biológica, Universidade do Algarve, 2009

The role of papyrus plants (Cyperus papyrus) and internal waves in the nutrient balance of Lake Victoria, East Africa

Dissertação mest., Gestão da água e da costa, Universidade do Algarve, 2007

Phytochemical studies and biological activity of carnivorous plants from the Mediterranean region

Tese de doutoramento, Ciências Biotecnológicas (Biotecnologia Vegetal), Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

Temperature, pH, and conductivity control of the nutrient solution of an hydroponic greenhouse

One of the aspects of modern agriculture is characterised by a culture without soil (hydroponic cultures). These culture techniques are identified by possessing automatic control systems to control the nutrient solution. In first hydroponic cultures this control was accomplished by “on- off” analog controllers that applied a single control law implemented in hardware. Therefore, the changes of the control law resulted in the change of all interface electronics. In digital control implemented by micro-controllers the alteration of such control law is easily performed by changing only a computer program, leaving untouched all the interface hardware. In this way, the use and substitution of the control strategy is improved, as well, the use of advanced control strategies.

A greenhouse climate multivariable predictive controller

A multivariable predictive controller was implemented to regulate the air temperature, humidity and CO2 concentration for a greenhouse located in the north of Portugal. The controller outputs are computed in order to optimise the future behaviour of the greenhouse environment, concerning the set-point accuracy and the minimization of energy inputs.

Application of radial basis function neural networks to a greenhouse inside air temperature model

The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

Comparison of on-line learning algorithms for RBF models in greenhouse environmental control problems

The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

Design and implementation of a real-time data acquisition system for the identification of dynamic temperature models in a hydroponic greenhouse

This text describes a real data acquisition and identification system implemented in a soilless greenhouse located at the University of Algarve (south of Portugal). Using the Real Time Workshop, Simulink, Matlab and the C programming language a system was developed to perform real-time data acquisition from a set of sensors.

Real-time data acquisition system for the Identification of dynamic temperature models in a hydroponic greenhouse

A real-time data acquisition and identification system implemented in a soil-less greenhouse located in the south of Portugal is described. The system performs real-time data acquisition from a set of sensors connected to a data logger.

Real-time parameter estimation of dynamic temperature and humidity models for greenhouse adaptive climate control

A real-time parameter estimator for the climate discrete-time dynamic models of a greenhouse located at the North of Portugal are presented. The experiments showed that the second order models identified for the air temperature and humidity achieve a close agreement between simulated and experimantal data.

Real-time parameter estimation of dynamic temperature models for greenhouse environmental control

For a greenhouse located at UTAD-University, the methods used to estimate in real-time the parameters of the inside air temperature model will be described. The structure and the parameters of the climate discrete-time dynamic model were previously identified using data acquired during two different periods of the year.

Dynamic temperature models of a soiless greenhouse

In this paper climate discrete-time dynamic models for the inside air temperature of a soilless greenhouse are identified, using data acquired during two different periods of the year. These models employ data from air temperature and relative humidity.

Identification of greenhouse climate dynamic models

In this paper climate discrete-time dynamic models for the inside air temperature of two different greenhouses are identified, using data acquired during two different periods of the year. These models employ data from air temperature and relative humidity (both outside and inside the greenhouse), solar radiation, wind speed, and control inputs (ventialtion, etc.).

Predicting the greenhouse inside air temperature with RBF neural networks

The application of the Radial Basis Function (RBF) Neural Network (NN) to greenhouse inside air temperature modelling has been previously investigated (Ferreira et al., 2000a). In those studies, the inside air temperature is modelled as a function of the inside relative humidity and of the outside temperature and solar radiation. A second-order model structure previously selected (Cunha et al., 1996) in the context of dynamic temperature models identification, is used.

Root ferric chelate reductase is regulated by iron and copper in straberry plants

In the present experiment, we studied the interaction between copper (Cu) and iron (Fe) in strawberry plants grown in nutrient solutions containing different concentrations of Fe. Plants grown in the absence of iron (Fe0) had the characteristic symptoms of Fe deficiency, with smaller chlorotic leaves, less biomass, acidification of the nutrient solution, and roots that were smaller and less ramified, while no symptoms of Fe deficiency were observed in plants grown with Fe. A greater amount of Cu was found in roots of chlorotic plants than in those grown with Fe, while plants grown with 20M of Fe (Fe20) in the nutrient solution had a greater amount of Fe compared with plants from the other treatments. Chlorotic plants (Fe0) and plants grown with the greatest level of Fe (Fe20) had a greater root ferric chelate reductase (FC-R; EC 1.16.1.17) activity compared with the other treatments with 5 or 10M Fe in the nutrient solution. The same pattern was obtained for relative FC-R mRNA concentration and for the sum of Fe and Cu contents in shoots (leaves plus crowns). The DNA obtained from amplification of the FC-R mRNA was cloned and several of the inserts analysed by single strand confirmation polymorphism (SSCP). Although there were different SSCP patterns in the Fe20 treatment, all the inserts that were sequenced were very similar, excluding the hypothesis of more than one FC-R mRNA species being present. The results suggest that Cu as well as Fe is involved in FC-R expression and activity, although the mechanism involved in this regulation is unknown so far. Both small contents of Fe and Cu in plants led to an over-expression of the FC-R gene and enhanced FC-R activity in strawberry roots.