Inspiralia project @Madrid, Spain (2013). The competitiveness of the European beekeeping sector is progressively falling due to the reduction of production as a direct consequence of the decrease in bee population. In addition, beekeeping products from countries with lower quality standards are gaining market share in Europe through an unfair competition. Furthermore, there is a lack of standards at European level for certain bee products like pollen and royal jelly.
This means that it is possible to find in the market products under these labels without any control of quality and authenticity. Few countries in Europe have some guidelines or regional standards for products other than honey, which results in a lack of standardization at the European level.
Therefore, the objectives of the APIFRESH project are threefold:
- to develop European standards for bee pollen and royal jelly;
- to establish health-relevant criteria for pollen and royal jelly;
- to determine the authenticity of both pollen and honey.
Partners of this project include:
- Balparmak (TR);
- Campomiel (ES);
- Centro Agrario de Marchamalo (ES);
- CTC - Centro Tecnológico Nacional de la Conserva y Alimentación (ES);
- EPBA - European Professional Beekeepers Association (EU);
- FNAP - Federação Nacional dos Apicultores de Portugal (PT);
- Inspiralia (ES);
- OMME - Országos Magyar Méhészeti Egyesület (HU);
- Parco Tecnologico Padano (IT);
- TÜBITAK-MAM - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu-Marmara Araştırma Merkezi (TR).
In this project, my work consists in the development of a software for the bee pollen classification and authentication. In a first step, bee pollen loads captured from a camera are separated by pollen type using a classification based on color. In a second step, a microscope is used to capture an accurate image of pollen grains from which discriminative features are extracted to identify the pollen origin, i.e. by considering the pollen grain as belonging either to a known type (pollen classification) or to an unknown type (outlier detection).