Ultra-high pressure-assisted enzymatic extraction enhances phenolic release and functional potency in fermented dark tea extracts - Xiaoying Lin; Jun Li; Yuanshan Yu; Dengwen Lei; Tenggen Hu; Manqin Fu; Qiang Xiao; Junying Zou; Ya Gao; Chao Huang; Jing Wen (Food Research International, 2026)

Underwater sea cucumber detection based on domain-invariant features - Fangqun Niu; Zejin Liu; Xinyu Zheng; Junyi Wang; Dexuan Zhang; Yuanshan Lin; Xiaoting Zhu; Shuai Yang; Wei Wang; Guodong Li (Aquaculture International, 2025)

ROV-assisted in situ density estimation for sea cucumbers via lightweight YOLOv8-FA and enhanced ByteTrack - Yanqiang Yang; Haolong Ban; Junyi Wang; Zejin Liu; Fangqun Niu; Qijun Chen; Jiaxu Zhang; Wei Wang; Zhijun Li; Yuanshan Lin (Aquaculture International, 2025)

Domain generalization for sea cucumber detection: Tackling background color variability in aquaculture settings - Fangqun Niu; Yifan Sheng; Junyi Wang; Xinyu Zheng; Kexin Liu; Yuanshan Lin; Wei Wang; GuoDong Li (Aquaculture International, 2025)

Straw-derived bio-organic fertilizer enhanced ecosystem multifunctionality in acidic paddy by improving microbial community composition and functional diversity - Feilong Rong; Yuanshan Lin; Manyun Zhang; Zhengwu Cai; Liqun Wu; Falin Chen (Journal of Environmental Management, 2025)

Fates of bioactive compounds and antioxidant activities of red pitaya pulp upon in vitro gastrointestinal digestion - Xian Lin; Xiangyu Li; Ying Huang; Jing Wen; Yuanshan Yu; Daobang Tang; Baojun Xu; Yujuan Xu (Food Research International, 2025)

MSGNet: multi-source guidance network for fish segmentation in underwater videos - Peng Zhang; Hong Yu; Haiqing Li; Xin Zhang; Sixue Wei; Wan Tu; Zongyi Yang; Junfeng Wu; Yuanshan Lin (Frontiers in Marine Science, 2023)
Fish segmentation in underwater videos provides basic data for fish measurements, which is vital information that supports fish habitat monitoring and fishery resources survey. However, because of water turbidity and insufficient lighting, fish segmentation in underwater videos has low accuracy and poor robustness. Most previous work has utilized static fish appearance information while ignoring fish motion in underwater videos. Considering that motion contains more detail, this paper proposes a method that simultaneously combines appearance and motion information to guide fish segmentation in underwater videos. First, underwater videos are preprocessed to highlight fish in motion, and obtain high-quality underwater optical flow. Then, a multi-source guidance network (MSGNet) is presented to segment fish in complex underwater videos with degraded visual features. To enhance both fish appearance and motion information, a non-local-based multiple co-attention guidance module (M-CAGM) is applied in the encoder stage, in which the appearance and motion features from the intra-frame salient fish and the moving fish in video sequences are reciprocally enhanced. In addition, a feature adaptive fusion module (FAFM) is introduced in the decoder stage to avoid errors accumulated in the video sequences due to blurred fish or inaccurate optical flow. Experiments based on three publicly available datasets were designed to test the performance of the proposed model. The mean pixel accuracy ( mPA ) and mean intersection over union ( mIoU ) of MSGNet were 91.89% and 88.91% respectively with the mixed dataset. Compared with those of the advanced underwater fish segmentation and video object segmentation models, the mPA and mIoU of the proposed model significantly improved. The results showed that MSGNet achieves excellent segmentation performance in complex underwater videos and can provide an effective segmentation solution for fisheries resource assessment and ocean observation. The proposed model and code are exposed via Github 1 .

Modeling collective motion for fish schooling via multi-agent reinforcement learning - Xin Wang; Shuo Liu; Yifan Yu; Shengzhi Yue; Ying Liu; Fumin Zhang; Yuanshan Lin (Ecological Modelling, 2023)

Ammonium Ions Induce Cellulase Synthesis in Trichoderma koningii - Lirong Xiang; Yuanshan Lin; Yun Tian; Qiyou Liu; Liujun Chen; Zhijie Tan (Current Microbiology, 2021)

Induction of cellulase gene transcription by a novel oligosaccharide: molasses alcohol stillage substance - Min Ling; Guiguang Chen; Yuanshan Lin; Zhiqun Liang (World Journal of Microbiology and Biotechnology, 2009)