Develop a hybrid machine learning model for promoting microbe biomass production
學年 111
學期 2
出版（發表）日期 2023-02-01
作品名稱 Develop a hybrid machine learning model for promoting microbe biomass production
作品名稱（其他語言）
著者 Pu-Yun Kow; Mei-Kuang Lu; Meng-Hsin Lee; Wei-Bin Lu; Fi-John Chang
單位
出版者
著錄名稱、卷期、頁數 Bioresource Technology 369
摘要 Since the cultivation condition of microbe biomass production (mycelia yield) involves a variety of factors, it’s a laborious process to obtain the optimal cultivation condition of Antrodia cinnamomea (A. cinnamomea). This study proposed a hybrid machine learning approach (i.e., ANFIS-NM) to identify the potent factors and optimize the cultivation conditions of A. cinnamomea based on a 32 fractional factorial design with seven factors. The results indicate that the ANFIS-NM approach successfully identified three key factors (i.e., glucose, potato dextrose broth, and agar) and significantly boosted mycelia yield. The interpretability of ANFIS rules made the cultivation conditions visually interpretable. Subsequently, a three-factor five-level central composite design was used to probe the optimal yield. This study demonstrates the proposed hybrid machine learning approach could significantly reduce the time consumption in laboratory cultivation and increase mycelia yield that meets SDGs 7 and 12, hitting a new milestone for biomass production.
關鍵字
語言 en
ISSN 1873-2976
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 否
國別 NLD
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128617 )