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The high penetration of smartphones and the advanced capabilities of the software that they can host, forces public agencies to rapidly transform their services in the mobile government environment for maximizing utility of services and minimizing costs. In this context, the aim of the paper is primarily to review the smartphone use and capabilities in agriculture. An overview of apps targeted to the agricultural business sector is provided. Secondly, the potential use of smartphones for mobile government is discussed and a transactional mobile government app for the Android operating system is proposed based on a case study for agriculture. The mobile government app is based on a previously developed electronic government system for farmers. Design and technical aspects for the implementation of the proposed app are presented and discussed. Such apps hope to be a promising solution for farmers enabling them to access government information and transact with public agencies at their convenience and at a location of their choice.

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The Joint Research Centre of the European Commission has developed Interpolated Meteorological Datasets available on a regular 25x25km grid both to the scientific community and the general public. Among others, the Interpolated Meteorological Datasets include daily maximum/minimum temperature, cumulated daily precipitation, evapotranspiration and wind speed. These datasets can be accessed through a web interface after a simple registration procedure. The Interpolated Meteorological Datasets also serve the Crop Growth Monitoring System (CGMS) at European level. The temporal coverage of the datasets is more than 30 years and the spatial coverage includes EU Member States, neighboring European countries, and the Mediterranean countries. The meteorological data are highly relevant for the development, implementation and assessment of a number of European Union (EU) policy areas: agriculture, soil protection, environment, agriculture, food security, energy, climate change.An online user survey has been carried out in order to assess the impact of the Interpolated Meteorological Datasets on research developments. More than 70% of the users have used the meteorological datasets for research purposes and more than 50% of the users have used those sources as main input for their models. The usefulness of the data scored more than 70% and it is interesting to note that around 25% of the users have published their scientific outputs based on the Interpolated Meteorological Datasets. Finally, the user feedback focuses mostly on improving the data distribution process as well as the visibility of the web platform.

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Here we assess the quality and in-season development of European wheat (Triticum spp.) yield forecasts during low, medium, and high-yielding years. 440 forecasts were evaluated for 75 wheat forecast years from 1993–2013 for 25 European Union (EU) Member States. By July, years with median yields were accurately forecast with errors below ~2%. Yield forecasts in years with low yields were overestimated by ~10%, while yield forecasts in high-yielding years were underestimated by ~8%. Four-fifths of the lowest yields had a drought or hot driver, a third a wet driver, while a quarter had both. Forecast accuracy of high-yielding years improved gradually during the season, and drought-driven yield reductions were anticipated with lead times of ~2 months. Single, contrasting successive in-season, as well as spatially distant dry and wet extreme synoptic weather systems affected multiple-countries in 2003, ’06, ’07, ’11 and 12’, leading to wheat losses up to 8.1 Mt (>40% of total EU loss). In these years, June forecasts (~ 1-month lead-time) underestimated these impacts by 10.4 to 78.4%. To cope with increasingly unprecedented impacts, near-real-time information fusion needs to underpin operational crop yield forecasting to benefit from improved crop modelling, more detailed and frequent earth observations, and faster computation.

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