Data-Driven Feed Optimization for Sustainable Aquaculture through Integrated Omics Analysis and Two-stage Bayesian optimization
Kei Terayama, Satoshi Soma, Hirofumi Furuita, Tomohito Shimizu, Takashi Iwasaki, Kenji Sakata, Ken-ichi Akagi, Taiga Asakura, Tetsuya Sanda, Tomofumi Yamaguchi, Yuji Fujikura, Yuki Hongo, Hideaki Shima, Hideo Yokota, Jun Kikuchi, , Miyuki Mekuchi
This paper develops a data-driven feed optimization system for aquaculture using Bayesian optimization and omics analysis to improve sustainability and growth efficiency.
bioRxiv · Jan 27, 2025 · PreprintEcology