Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Zhiheng Zou"'
Autor:
Xing Chen, Aijuan Zheng, Zhimin Chen, Shoaib Ahmed Pirzado, Zedong Wang, Jiang Chen, Zhiheng Zou, Guohua Liu
Publikováno v:
Poultry Science, Vol 103, Iss 10, Pp 104049- (2024)
ABSTRACT: Gut health of broiler chickens is essential for production performance. The present study aimed to evaluate the impact of dietary supplementation with potassium diformate (KDF) on growth performance and intestinal health in broiler chickens
Externí odkaz:
https://doaj.org/article/6767da5ea0c04d928c2fe3583136a977
Autor:
Xiaolian Chen, Wenjing Song, Pingwen Xiong, Di Cheng, Weiqun Wei, Quanyong Zhou, Chuanhui Xu, Qiongli Song, Huayuan Ji, Yan Hu, Zhiheng Zou
Publikováno v:
Frontiers in Veterinary Science, Vol 11 (2024)
IntroductionPlant essential oils (PEOs) have received significant attention in animal production due to their diverse beneficial properties and hold potential to alleviate weaning stress. However, PEOs effectiveness is often compromised by volatility
Externí odkaz:
https://doaj.org/article/e4ad3f0061fe47f88bbc97284ddf0c0a
Autor:
Qiongli Song, Zhiheng Zou, Xiaolian Chen, Gaoxiang Ai, Pingwen Xiong, Wenjing Song, Guohua Liu, Aijuan Zheng, Jiang Chen
Publikováno v:
Agriculture, Vol 14, Iss 9, p 1523 (2024)
This study aimed to investigate the impact of dietary supplementation with Moringa oleifera leaf powder (MOLP) on the growth performance, digestive enzyme activity, meat quality, and cecum microbiota of Ningdu yellow chickens. A total of 300 78-day-o
Externí odkaz:
https://doaj.org/article/8f3a8e95c0694c88ba4016e0d1e2f2cd
Autor:
Chuanhui Xu, Pingwen Xiong, Wenjing Song, Qiongli Song, Yan Hu, Tongxing Song, Huayuan Ji, Xiaolian Chen, Zhiheng Zou
Publikováno v:
Foods, Vol 13, Iss 12, p 1910 (2024)
In order to cope with the limited supply of feed for global animal production, there is a pressing need to explore alternative feed resources. Orange pulp, a by-product of agriculture and industry, has shown potential to positively or neutrally impac
Externí odkaz:
https://doaj.org/article/65213b48b8dc4dc98ff0c771a3e82801
Autor:
Xiaolian Chen, Pingwen Xiong, Wenjing Song, Qiongli Song, Zhiheng Zou, Jiangnan Huang, Jiang Chen, Chuanhui Xu, Weide Su, Gaoxiang Ai, Qipeng Wei
Publikováno v:
Frontiers in Veterinary Science, Vol 10 (2023)
IntroductionHoneycomb is a traditional natural health medicine and has antioxidant, antibacterial, anti-inflammatory, antiviral and antitumor activities. It is currently unclear whether honeycomb extract supplementation has positive effects on the in
Externí odkaz:
https://doaj.org/article/2ef52c014253493a8c30bd1dd24875af
Autor:
Wenjing Song, Zhiheng Zou, Xiaolian Chen, Jia Tan, Linxiu Liu, Qipeng Wei, Pingwen Xiong, Qiongli Song, Jiang Chen, Weide Su, Chuanhui Xu
Publikováno v:
Poultry Science, Vol 102, Iss 10, Pp 102986- (2023)
ABSTRACT: Traditional Chinese herbs have been widely researched as a green, safe, and effective feed additive for poultry. The purpose of this study was to investigate the effects of traditional Chinese prescription (TCP) based on various herbs in a
Externí odkaz:
https://doaj.org/article/1a0b714656f140a690fe0874ece323e7
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 70:1-14
With the continuous development of rail transit fully automatic operation, the urgent need to improve train operation safety makes obstacle detection become the research focus. In this work, a flexible and efficient multiscale one-stage object detect
Publikováno v:
ICCT
Pantograph slide abrasion is one of the key factors that affect urban rail transit vehicles current-collecting quality. In order to measure the abrasion value of pantograph slide in real time, an online-image detecting method was proposed in this pap
Publikováno v:
Measurement. 190:110728
Publikováno v:
Measurement. 176:109241
Obstacle detection plays an important role in train automatic operation. To overcome the low accuracy and poor real-time performance of traditional detection methods, and better detect medium and long distances obstacles, the Improved-YOLOv4 network