Advances on apple production under semiarid climate: N fertigation

The fertilizing management for apple tree is essential, especially for nitrogen, one of the most important nutrients affecting fruit yield. Thus, an experiment was conducted in 2012 and 2013 to evaluate the fruit production, yield and leaf chlorophyll of ?Princesa? and ?Eva? apples as a function of nitrogen fertigation under Brazilian semiarid conditions. The experimental design consisted of randomised blocks, with treatments distributed in a factorial arrangement 2 x 4, corresponding to apple cultivars (Eva and Princesa); and nitrogen doses (160, 120, 80 and 40 kg of N ha-1), with four replications and three plants. Calcium nitrate was used as nitrogen source (15.5% of N) with applications twice a week during 40 days, reaching 12 fertilizing performances through irrigation water. The following variables were evaluated: i) fruit production per plant (kg plant-1); ii) fruit yield (t ha-1); iii) number of fruits per plant; iv) leaf chlorophyll meter readings (index); and v) leaf nitrogen concentration (g kg-1). Princesa apple cultivar if compared to ?Eva? presents a better fruit production performance under Brazilian semiarid. Furthermore, nitrogen doses fertilized through irrigation water have no effect on fruit production of Eva and Princesa apple cultivars during the first production cycle.

A Method of Preparing Future Hourly Weather Data for the Study of Global Warming Impact on the Built Environment

The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of global warming on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since all building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. Based on a review of the existing weather data generation models, this paper presents an effective method to generate approximate future hourly weather data suitable for the study of the impact of global warming. Depending on the level of information available for the prediction of future weather condition, it is shown that either the method of retaining to current level, constant offset method or diurnal modelling method may be used to generate the future hourly variation of an individual weather parameter. An example of the application of this method to the different global warming scenarios in Australia is presented. Since there is no reliable projection of possible change in air humidity, solar radiation or wind characters, as a first approximation, these parameters have been assumed to remain at the current level. A sensitivity test of their impact on the building energy performance shows that there is generally a good linear relationship between building cooling load and the changes of weather variables of solar radiation, relative humidity or wind speed.