Nondestructive Testing Model of Mango Dry Matter Based on Fluorescence Hyperspectral Imaging Technology

Autor: Zhiliang Kang, Jinping Geng, Rongsheng Fan, Yan Hu, Jie Sun, Youli Wu, Lijia Xu, Cheng Liu

Publikováno v: Agriculture, Vol 12, Iss 9, p 1337 (2022)

The dry matter test of mango has important practical significance for the quality classification of mango. Most of the common fruit and vegetable quality nondestructive testing methods based on fluorescence hyperspectral imaging technology use a sing

Externí odkaz: https://doaj.org/article/ddb9085e4928490ead30ab23ee1c30c1

Motion Planning of the Citrus-Picking Manipulator Based on the TO-RRT Algorithm

Autor: Cheng Liu, Qingchun Feng, Zuoliang Tang, Xiangyu Wang, Jinping Geng, Lijia Xu

Publikováno v: Agriculture, Vol 12, Iss 5, p 581 (2022)

The working environment of a picking robot is complex, and the motion-planning algorithm of the picking manipulator will directly affect the obstacle avoidance effect and picking efficiency of the manipulator. In this study, a time-optimal rapidly-ex

Externí odkaz: https://doaj.org/article/c63eec0ea36e4d07b0e2beb7062c5d47

Identification of pesticide residues on black tea by fluorescence hyperspectral technology combined with machine learning

Autor: Jie SUN, Yan HU, Yulin ZOU, Jinping GENG, Youli WU, Rongsheng FAN, Zhiliang KANG

Publikováno v: Food Science and Technology v.42 2022
Food Science and Technology (Campinas)
Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron:SBCTA

Black tea has a long history in China, but in export trade, pesticide residues often exceed the standard. To obtain a rapid, accurate, and non-destructive identification method of pesticide residues on black tea, the fluorescence hyperspectral data o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2d60c165a4bc68496bfffe4f6e650e1
https://doi.org/10.1590/fst.55822