Výsledky vyhledávání

Akademický článek

Hyperspectral imaging combined with deep learning models for the prediction of geographical origin and fungal contamination in millet

Autor: Saimei Nie, Wenbin Gao, Shasha Liu, Mo Li, Tao Li, Jing Ren, Siyao Ren, Jian Wang

Publikováno v: Frontiers in Sustainable Food Systems, Vol 8 (2024)

Millet is one of the major coarse grain crops in China. Its geographical origin and Fusarium fungal contamination with ergosterol and deoxynivalenol have a direct impact on food quality, so the rapid prediction of the geographical origins and fungal

Externí odkaz: https://doaj.org/article/4b1e2bdaf020475ca6a3cd4094df0e94

Zobrazit plný text záznamu

Enhanced Internal Quantum Efficiency in Dye-Sensitized Solar Cells: Effect of Long-Lived Charge-Separated State of Sensitizers

Autor: Siyao Ren, Xueqin Zhou, Dongzhi Liu, Ting Lu, Haiya Sun, Tianyang Wang, Lichang Wang, Wei Li, Wenping Hu

Publikováno v: ACS Applied Materials & Interfaces. 9:9880-9891

Effective charge separation is one of the key determinants for the photovoltaic performance of the dye-sensitized solar cells (DSSCs). Herein, two charge-separated (CS) sensitizers, MTPA-Pyc and YD-Pyc, have been synthesized and applied in DSSCs to i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09612d22e3d1f5c0e99a1f85ec7711cc
https://doi.org/10.1021/acsami.6b14993

Zobrazit plný text záznamu

Periodical

Hebei Agricultural University Researchers Update Current Study Findings on Sustainable Food Systems (Hyperspectral imaging combined with deep learning models for the prediction of geographical origin and fungal contamination in millet).

Publikováno v: Food Weekly News; 10/3/2024, p77-77, 1p

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání