SHORT-TERM EFFECTS OF SALINITY ON SOME PHYSIOLOGICAL PARAMETERS OF YOUNG OLIVE TREES OF ARBEQUINA, COBRANÇOSA AND GALEGA VARIETIES

SHORT-TERM EFFECTS OF SALINITY ON SOME PHYSIOLOGICAL PARAMETERS OF YOUNG OLIVE TREES OF ARBEQUINA, COBRANÇOSA AND GALEGA VARIETIES Ana Elisa Rato1,4, Renato Coelho1, Margarida Vaz1, Teresa Carola2, Dália Barbosa2, Nádia Silva1, José dos Santos2, Lourenço Machado2, João Godinho2, Luzia Ruas2, Margarida Barradas2, Hernani Pereira2, Sara Porfírio4 1 ICAAM, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal 2 Master students, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal 3 Ph.D. student, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal 4 aerato@uevora.pt Due to the desertification in some regions, the interest in plant’s tolerance to salinity has been increasing, as this response is determining for plant survival in stress conditions. This work reports the investigation of tolerance to salt in two year-old olive trees (Olea europaea L.) of three varieties, Arbequina, Cobrançosa and Galega vulgar. Plants were grown in 10 L plastic pots containing approximately 9 Kg of a sandy granitic soil, on a greenhouse. For 3 months (from the beginning of February to the end of April 2012), they were subjected to three levels of salinity in the irrigation water, 0 mM, 80 mM and 200 mM NaCl (6 plants per salinity level in a total of 18 plants of each variety),. Stomatal conductance (gs) and relative leaf chlorophyll content were assessed on each plant in February, March and April. Mid-day leaf water potential () and soil salinity were measured at the end of the experiment (April). On average, concerning all treatments and dates of determination, stomatal conductance of Arbequina and Galega vulgar was quite similar, around 40 mmol m-2 s-1, but Cobrançosa had a value of gs 36% higher, almost 50% higher (61 mmol m-2 s-1) when compared with the controls (0 mM salt) of the other two varieties. In percentage of controls, there was little difference in gs between varieties and between salinities during February and March. In contrast, in April, after about 90 days of exposure to salt, there was a clear decrease in gs with salt irrigation, proportional to salt concentration. Compared with controls, plants irrigated with 200 mM salt showed around 80% (Arbequina) or 85% (Cobrançosa and Galega vulgar) decrease in gs. Chlorophyll content of leaves showed less than 5% difference between varieties on the average of all treatments and dates of determination. During the course of this experiment, the salinity levels used did not show any relevant effect on chlorophyll content. Overall, at the end of the experimental period (April), leaf water potential () at midday was significantly higher in Cobrançosa (-1,4 MPa) than in Galega vulgar (-1,7 MPa) or Arbequina (-1,8 MPa), and salt decreased  of control plants (-1,25 MPa) by an average 30% (with 80 mM) and 65% (with 200 mM). At the end of the experiment, salinity in the soil irrigated with 0 mM, 80 mM or 200 mM NaCl was, on average of all varieties, 0,2 mS, 1,0 mS or 2,0 mS, respectively. Soil salinity was quite similar in Arbequina and Galega vulgar but about 35% lower in the pots of Cobrançosa, on average of all salt-irrigation levels. Plants of Cobrançosa had higher stomatal conductance, however they showed higher water potential and lower salinity in the soil. These apparently contradictory results seem to suggest that Cobrançosa responds to salt differently from the other two varieties. This issue needs further investigation.

Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models.