Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Elisavet Savvidaki"'
Autor:
Eleni Tsavea, Fotini-Paraskevi Vardaka, Elisavet Savvidaki, Abdessamie Kellil, Dimitrios Kanelis, Marcela Bucekova, Spyros Grigorakis, Jana Godocikova, Panagiota Gotsiou, Maria Dimou, Sophia Loupassaki, Ilektra Remoundou, Christina Tsadila, Tilemachos G. Dimitriou, Juraj Majtan, Chrysoula Tananaki, Eleftherios Alissandrakis, Dimitris Mossialos
Publikováno v:
Foods, Vol 11, Iss 7, p 943 (2022)
Pine honey is a honeydew honey produced in the East Mediterranean region (Greece and Turkey) from the secretions of the plant sucking insect Marchalina hellenica (Gennadius) (Coccoidea: Marchalini-dae) feeding on living parts of Pinus species. Nowada
Externí odkaz:
https://doaj.org/article/2e3b665caae74a0d848b079a3d18dde9
Autor:
Nikos Tsiknakis, Elisavet Savvidaki, Georgios C. Manikis, Panagiota Gotsiou, Ilektra Remoundou, Kostas Marias, Eleftherios Alissandrakis, Nikolas Vidakis
Publikováno v:
Plants, Vol 11, Iss 7, p 919 (2022)
Pollen identification is an important task for the botanical certification of honey. It is performed via thorough microscopic examination of the pollen present in honey; a process called melissopalynology. However, manual examination of the images is
Externí odkaz:
https://doaj.org/article/4720e2cba15e490f9222d44c6915a5ba
Autor:
Nikos Tsiknakis, Elisavet Savvidaki, Sotiris Kafetzopoulos, Georgios Manikis, Nikolas Vidakis, Kostas Marias, Eleftherios Alissandrakis
Publikováno v:
Applied Sciences, Vol 11, Iss 14, p 6657 (2021)
Pollen analysis and the classification of several pollen species is an important task in melissopalynology. The development of machine learning or deep learning based classification models depends on available datasets of pollen grains from various p
Externí odkaz:
https://doaj.org/article/0bc8acfac23345a4911c2cc26ffb3ad5
Autor:
Elisavet Savvidaki, Georgios Manikis, Nikos Tsiknakis, Kostas Marias, Eleftherios Alissandrakis, Nikolas Vidakis, Sotiris Kafetzopoulos
Publikováno v:
Applied Sciences
Volume 11
Issue 14
Applied Sciences, Vol 11, Iss 6657, p 6657 (2021)
Volume 11
Issue 14
Applied Sciences, Vol 11, Iss 6657, p 6657 (2021)
Pollen analysis and the classification of several pollen species is an important task in melissopalynology. The development of machine learning or deep learning based classification models depends on available datasets of pollen grains from various p