Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Zhiliang KANG"'
Autor:
Chunyi Zhan, Hongyi Mao, Rongsheng Fan, Tanggui He, Rui Qing, Wenliang Zhang, Yi Lin, Kunyu Li, Lei Wang, Tie’en Xia, Youli Wu, Zhiliang Kang
Publikováno v:
Foods, Vol 13, Iss 22, p 3547 (2024)
China ranks first in apple production worldwide, making the assessment of apple quality a critical factor in agriculture. Sucrose concentration (SC) is a key factor influencing the flavor and ripeness of apples, serving as an important quality indica
Externí odkaz:
https://doaj.org/article/265539695a3341cea17d9ba4fb0f164f
Publikováno v:
Molecules, Vol 29, Iss 3, p 682 (2024)
A rice classification method for the fast and non-destructive differentiation of different varieties is significant in research at present. In this study, fluorescence hyperspectral technology combined with machine learning techniques was used to dis
Externí odkaz:
https://doaj.org/article/aae1c2374f684566af03a02303d6ba1c
Autor:
Lijia Xu, Xiaoshi Shi, Zuoliang Tang, Yong He, Ning Yang, Wei Ma, Chengyu Zheng, Huabao Chen, Taigang Zhou, Peng Huang, Zhijun Wu, Yuchao Wang, Zhiyong Zou, Zhiliang Kang, Jianwu Dai, Yongpeng Zhao
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
IntroductionInsect pests from the family Papilionidae (IPPs) are a seasonal threat to citrus orchards, causing damage to young leaves, affecting canopy formation and fruiting. Existing pest detection models used by orchard plant protection equipment
Externí odkaz:
https://doaj.org/article/597a06cf3e9a42ecbebd329dd9928b4b
Autor:
Lijia Xu, Yi Xie, Xinyuan Chen, Yanjun Chen, Zhiliang Kang, Peng Huang, Zhiyong Zou, Yong He, Ning Yang, Yingqi Peng, Jianwu Dai, Zhijun Wu, Bi Liu, Yuchao Wang, Yongpeng Zhao
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Herein, a combined multipoint picking scheme was proposed, and the sizes of the end of the bud picker were selectively designed. Firstly, the end of the bud picker was abstracted as a fixed-size picking box, and it was assumed that the tea buds in th
Externí odkaz:
https://doaj.org/article/5079dc6331a34a2693674358ba862932
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
Publikováno v:
Foods, Vol 11, Iss 15, p 2344 (2022)
Oolong tea is a semi-fermented tea that is popular among people. This study aims to establish a classification method for oolong tea based on fluorescence hyperspectral technology(FHSI) combined with chemometrics. First, the spectral data of Tieguany
Externí odkaz:
https://doaj.org/article/c4acba130d484f8daf7b7f2137874daa
Autor:
Yan Hu, Zhiliang Kang
Publikováno v:
Molecules, Vol 27, Iss 4, p 1196 (2022)
Tieguanyin is one of the top ten most popular teas and the representative of oolong tea in China. In this study, a rapid and non-destructive method is developed to detect adulterated tea and its degree. Benshan is used as the adulterated tea, which i
Externí odkaz:
https://doaj.org/article/4bfef503dc28419facad86bbf44c6dfa
Publikováno v:
Agriculture, Vol 11, Iss 11, p 1106 (2021)
A rapid and nondestructive tea classification method is of great significance in today’s research. This study uses fluorescence hyperspectral technology and machine learning to distinguish Oolong tea by analyzing the spectral features of tea in the
Externí odkaz:
https://doaj.org/article/f3afd197b3434d08a8778380b1c1110e
Publikováno v:
Applied Sciences, Vol 11, Iss 23, p 11336 (2021)
This paper presents the results of a motion planning algorithm that has been used in an intelligent citrus-picking robot consisting of a six-link manipulator. The real-time performance of a motion planning algorithm is urgently required by the pickin
Externí odkaz:
https://doaj.org/article/0f555bf08038432bb709e3f84f93e874
Publikováno v:
Entropy, Vol 23, Iss 9, p 1146 (2021)
Mobile edge computing (MEC) focuses on transferring computing resources close to the user’s device, and it provides high-performance and low-delay services for mobile devices. It is an effective method to deal with computationally intensive and del
Externí odkaz:
https://doaj.org/article/6720e3d4f4a74b73a9cc228d32878907