Browsing by Author "Faria, E. A."
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- Application of radial basis function neural networks to a greenhouse inside air temperature modelPublication . Ferreira, P. M.; Faria, E. A.; Ruano, AntonioThe 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 problemsPublication . Ferreira, P. M.; Faria, E. A.; Ruano, AntonioThe 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 greenhousePublication . Ferreira, P. M.; Faria, E. A.; Ruano, AntonioThis 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.
- Diagnosis and correction of iron chlorosis in fruit trees: a reviewPublication . Correia, Maribela Pestana; de Varennes, A.; Faria, E. A.Several plant species grown in calcareous soils in arid and semiarid regions are iron-deficient, a condition known as lime-induced iron chlorosis, or simply as iron chlorosis. The nutritional status of perennial plants is commonly evaluated by leaf analysis. However, there is often no correlation between iron in leaves and degree of chlorosis, and therefore leaf analysis presents serious limitations as a technique to evaluate lime-induced iron chlorosis. Recently, a technique for the early prognosis of iron chlorosis based on floral analysis was developed for fruit trees to help prevent the development of iron deficiency and avoid losses in yield and quality. Correction of iron chlorosis is commonly carried out by massive applications of synthetic iron chelates to soils. Since iron is rapidly immobilised in the soil, this treatment has to be repeated each year, representing a major part of fertilizer costs. Environmental impacts of chelates in soils have not been properly investigated, but it is known that they also result in enhanced plant uptake of metals such as copper and nickel. Alternative, more environment-friendly treatments are being evaluated. In this article we concentrate on reviewing current methods to detect and correct iron chlorosis in fruit trees.
- Differential tolerance to iron deficiency of citrus rootstocks grown in nutrient solutionPublication . Correia, Maribela Pestana; de Varennes, A.; Abadia, J.; Faria, E. A.We studied the effects of Fe deficiency on physiological parameters of citrus rootstocks grown in nutrient solution. Three 4-week old rootstocks ('Troyer' citrange - Citrus sinensis (L.) Osb. x Poncirus trifoliata (L.) Raf., Citrus taiwanica Tan. and Shim., and 'Swingle' citrumelo - Poncirus trifoliata (L.) Raf. x Citrus paradisi Macf.) were grown in nutrient solutions with 0, 5, 10, 15 and 20 mumol Fe dm(-3). Calcium carbonate (1 g dm(-3)) was added to all solutions to mimic the natural conditions in calcareous soils. For each rootstock, shoot length, number of leaves, and root and shoot dry weights were measured at the end of experiment. Chlorophyll concentration was estimated using a portable SPAD-502 meter calibrated for each rootstock. The amount of nutrients (P, K, Mg, Ca, Fe, Zn, Mn, and Cu) was determined in shoots. Chlorophyll fluorescence parameters (F-0: basal fluorescence; F-m: maximum fluorescence; F-v = F-m - F-0: variable fluorescence) were measured with a portable fluorimeter. 'Troyer' citrange rootstock was the most tolerant to Fe deficiency. These plants grew more and accumulated more chlorophyll and nutrients than the others in the presence of low levels of Fe (10 mumol Fe dm(-3)). 'Swingle' citrumelo plants needed 20 mumol Fe dm(-3) in the nutrient solution to secure adequate growth. 'Taiwanica' orange rootstock had an intermediate behaviour, but could be distinguished from 'Troyer' citrange based on fluorescence parameters, since there was a variation in the basal fluorescence in the former, whereas in 'Troyer' citrange the basal fluorescence was not affected by the supply of Fe. (C) 2004 Elsevier B.V. All rights reserved.
- Dynamic temperature models of a soiless greenhousePublication . Cunha, J. B.; Ruano, Antonio; Faria, E. A.; Couto, C.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.
- Effectiveness of different foliar iron applications to control iron chlorosis in orange trees grown on a calcareous soilPublication . Pestana, M.; Correia, P. J.; Varennes, Amarilis de; Abadía, Javier; Faria, E. A.The effectiveness on controlling Fe chlorosis in orange trees grown on calcareous soils was tested. The treatments were Fe(II) sulfate (500 mg Fe L ÿ1), sulfuric acid (0.5mM H2SO4), Fe(III)-chelate (Hampiron 654 GS, 120 mg Fe L ÿ1) and distilled water as a control. A non-ionic wetting agent was used in all treatments. The use of frequent foliar sprays alleviated Fe chlorosis in orange trees. Sprays of Fe(II) sulfate increased the concentrations of chlorophyll, Fe and zinc in leaves and improved fruit size and quality compared to fruits of control trees. Sprays of Fe(III)-chelate also increased leaf chlorophyll and Fe concentrations and improved fruit quality, but did not increase fruit size. Sprays of sulfuric acid alone slightly increased leaf chlorophyll and Fe concentrations, without improving fruit size and quality. These results suggest that foliar sprays with Fe could help to avoid yield and quality losses caused by Fe chlorosis in citrus orchards. Furthermore, these treatments could be done with relatively cheap materials such as solutions containing Fe(II) sulfate.
- Floral analysis as a tool to diagnose iron chlorosis in orange treesPublication . Correia, Maribela Pestana; de Varennes, A.; Goss, M. J.; Abadia, J.; Faria, E. A.A three-year field experiment was conducted in a commercial orange grove [Citrus sinensis (L.) Osb. cv. 'Valencia late' grafted on Citrange Troyer] established on a calcareous soil in the south of Portugal, to investigate if flower analysis could be used to diagnose lime-induced iron chlorosis. In April, during full bloom, flowers and leaves were collected from 20 trees. Leaf samples were again collected from the same trees in May, June, July and August. Total chlorophyll was estimated in all the leaves sampled for foliar analysis, using a SPAD-502 apparatus. Leaves and flowers were analysed for N, P, K, Ca, Mg, Fe, Zn, Mn and Cu. Principal Component Analysis was used to evaluate the variation of nutrient concentrations in flowers, and linear regressions were established between these and the chlorophyll content of leaves 90 days after full bloom. Evaluation of the best-fit equation was carried out using separate data obtained from other groves. Variation in the pattern of floral mineral composition in the flowers showed contrasts between the increase in N, P and K and that of Ca, Fe and Zn, while the concentration of Mg, Mn and Ca varied synchronously. The ratio of Mg: Zn in flowers explained about half of the variation of chlorophyll in leaves later in the season. A ratio below 100 indicated that trees would develop iron chlorosis, while with a ratio above 200 leaves would remain green. An early prognosis of iron chlorosis based on floral analysis can benefit growers, since it allows them to apply treatments in time to prevent loss of fruit yield and quality due to iron chlorosis.
- Neural network models in greenhouse air temperature predictionPublication . Ferreira, P. M.; Faria, E. A.; Ruano, AntonioThe adequacy of radial basis function neural networks to model the inside air temperature of a hydroponic greenhouse as a function of the outside air temperature and solar radiation, and the inside relative humidity, is addressed. As the model is intended to be incorporated in an environmental control strategy botho--line and on-line methods could be of use to accomplish this task. In this paper known hybrid o--line training methods and on-line learning algorithms are analyzed. An o--line method and its application to on-line learning is proposed. It exploits the linear–non-linear structure found in radial basis function neural networks.
- Neural network models in greenhouse environmental controlPublication . Ferreira, P. M.; Faria, E. A.; Ruano, AntonioThe adequacy of radial basis function neural networks to model the inside air temperature of a hydroponic greenhouse as a function of the outside air temperature and solar radiation, and the inside relative humidity, is addressed. As the model is intended to be incorporated in an environmental control strategy both off-line and on-line methods could be of use to accomplish this task. In this paper hybrid off-line training methods and on-line learning algorithms are analysed. An off-line method and its application to on-line learning is presented. It exploits the linear-nonlinear structure found in radial basis function neural networks.