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1

Morphology and ultrastructure of kiwifruits resulting from artifical pollination

100%
Abreu I., Oliveira M., Veloso A.
Acta Physiologiae Plantarum
|
2004
|
tom 26
|
nr 3 suppl.
2
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Airborne pollen of Olea in five regions of Portugal

100%
Ribeiro H., Cunha M., Abreu I.
Annals of Agricultural and Environmental Medicine
|
2005
|
tom 12
|
nr 2
317-320
The aim of this work was to study spatial and temporal distribution of Olea europeae airborne pollen in different Portuguese regions: Reguengos de Monsaraz (south); Bairrada (west); Braga (northwest); Valenca do Douro and Foz Coa (north-east). Airborne pollen sampling was conducted from 1998-2003 using "Cour" type samplers located in each region. The main pollen season (MPS) of Olea lasted on average 36 days and occurred from late April until middle-to-end of June. During the studied period, inter-annual variations among and within regions, concerning the total annual pollen counts and the beginning, peak and ending dates of the MPS, were reported. Reguengos de Monsaraz and Bairrada registered the earliest MPS starting date, followed by Valenca do Douro and Foz-Coa, and the latest date was verified in Braga that also had the shortest MPS. Reguengos de Monsaraz presented the longest MPS with the highest differences in the beginning and ending dates, but minimum differences in the dates of the maximum pollen peak. Our results showed an increase in the Olea annual pollen index, from north to south, and from the west to the east regions of the country.
3
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Important phytopathogenic airborne fungal spores in a rural area: incidence of Botrytis cinerea and Oidium spp.

100%
Oliveira M., Guerner-Moreira J., Mesquita M. M., Abreu I.
Annals of Agricultural and Environmental Medicine
|
2009
|
tom 16
|
nr 2
197-204
4
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Annual variation of fungal spores in atmosphere of Porto: 2003

100%
Oliveira M., Ribeiro H., Abreu I.
Annals of Agricultural and Environmental Medicine
|
2005
|
tom 12
|
nr 2
309-315
The seasonal distribution of fungal spore concentration in the city of Porto, Portugal, was continuously studied, from 1 January to 31 December 2003, using a 7-day volumetric Burkard trap. In Portugal, aerobiological studies are scarce, and to our knowledge there are no published data on the atmospheric concentration of fungal spores. The aim of this work therefore is to initiate the aeromycological studies in Porto. The total airborne spore concentration fluctuated between 2 and 2,198 spores/m3 per day with an daily mean of 403 spores/m3. The highest airborne spore concentration was found during the summer and the early autumn, while the lowest concentration was registered during the winter. A range of allergenic and phytopathogenic fungal spores was present in the atmosphere of Porto throughout the entire year, although in different concentrations. Among the 22 fungal spore types identified Cladosporium (74.5%), Ganoderma (11.7%), Aspergillaceae (2.9%), Ustilago (2.5%), Coprinus (1.5%), Alternaria (1.3%) and Botrytis (1.3%) were the most frequent. Seasonally, spore levels of Cladosporium and Alternaria peaked in the autumn and winter, Ganoderma peaked toward autumn, whilst spore levels of the basidiomycete Coprinus fluctuated throughout the year. The total spore concentration was negatively correlated with wind speed and positively correlated with temperature and relative humidity.
5
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Definition of main pollen season using logistic model

100%
Ribeiro H., Cunha M., Abreu I.
Annals of Agricultural and Environmental Medicine
|
2007
|
tom 14
|
nr 2
This paper proposes a method to unify the defi nition of the main pollen season based on statistical analysis. For this, an aerobiological study was carried out in Porto region (Portugal), from 2003-2005 using a 7-day Hirst-type volumetric spore trap. To defi ne the main pollen season, a non-linear logistic regression model was fi tted to the values of the accumulated sum of the daily airborne pollen concentration from several allergological species. An important feature of this method is that the main pollen season will be characterized by the model parameters calculated. These parameters are identifi able aspects of the fl owering phenology, and determine not only the beginning and end of the main pollen season, but are also infl uenced by the meteorological conditions. The results obtained with the proposed methodology were also compared with two of the most used percentage methods. The logistic model fi tted well with the sum of accumulated pollen. The explained variance was always higher than 97%, and the exponential part of the predicted curve was well adjusted to the time when higher atmospheric pollen concentration was sampled. The comparison between the different methods tested showed large divergence in the duration and end dates of the main pollen season of the studied species.
6
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Forecasting ARIMA models for atmospheric vineyard pathogens in Galicia and Northern Portugal: Botrytis cinerea spores

76%
Fernandez-Gonzalez M., Rodriguez-Rajo F. J., Jato V., Aira M. J., Ribeiro H., Oliveira M., Abreu I.
Annals of Agricultural and Environmental Medicine
|
2012
|
tom 19
|
nr 2
Botrytis cinerea is the cause of the most common disease in the Galician and Portuguese vineyards. Knowledge of the spore levels in the atmosphere of vineyards is a tool for forecasting models of the concentration of spores in order to adjust the phytosanitary treatments to real risk infection periods. The presented study was conducted in two vineyards, one located in Cenlle (Spain) and other in Amares (Portugal), from 2005-2007. A volumetric trap, model Lanzoni VPPS-2000, was used for the aerobiological study. Phenological observations were conducted on 20 vines of three grape varieties in Cenlle (Treixadura, Godello and Loureira) and in Amares (Trajadura, Loureiro and Pedernã), by using the BBCH scale. The highest total spore concentrations during the grapevine cycle were recorded in 2007 in both locations (Cenlle:16,145 spores; Amares:1,858 spores), and the lowest, in 2005 in Cenlle (1,700 spores) and in Amares (800 spores) in 2006. In Cenlle, the best adjusted model was an ARIMA (0,2,2), including the relative humidity four days earlier, while in Amares there was an ARIMA (1,2,3), considering the relative humidity three days earlier and rainfall two days earlier. The t-test showed no significant difference between observed and predicted data by the model.
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