期刊
JOURNAL OF CLEANER PRODUCTION
卷 156, 期 -, 页码 367-377出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.04.055
关键词
Turbot skin; Fermentation technology; Aspergillus oryzae; Hydrolysate Functional substances; Antioxidant activity
资金
- Fundamental Research Funds for the Central Universities [201564018]
- Major Special Science and Technology Projects in Shandong Province [2016YYSP016]
- National Science and Technology Pillar Program during the Twelfth Five-year Plan Period [2015BAD16B0902]
- Qingdao Post-Doctor Applied Research Project Foundation
Booming development of fishing economy has significantly accelerated the fish waste generation in the world. The disposal of fish waste poses a serious environmental problem. The fish waste contains substantial amount high quality protein, which is an excellent resource of bioactive substance. In the conscious of eco-friendly and economical disposal, converting these waste into high value-added products for industrial applications is of profound implication. In this study, microorganism fermentation was employed and developed for the high-value utilization of discarded turbot skin. Among the various strains, Aspergillus oryzae showed the most promising hydrolysis ability. Under optimal conditions, a comprehensive detailed description of the fermentation process of hydrolysate from Aspergillus oryzae (AOH) is described. Additionally, amino acid compositions, volatile compounds, and antioxidant activity of AOH are studied. Size exclusion chromatography purification could effectively enhance the antioxidant activity. During gastrointestinal digestion, excellent residual antioxidant efficacy can be achieved by AOH and its chelating activity was improved. In physicochemical (temperature, light, pH) stability assays, AOH demonstrated better antioxidative stability in a wide range of pH and temperature conditions, but exhibited sensitivity to sunlight exposure. The results pointed out that turbot skin can be a cheap resource of antioxidant, which has many promising applications in pharmaceutical and food industry for health promotion and food preservation. Finally, fermentative bioprocess could be identified as a clean production which can not only be used for minimizing the impact of environment but also converting fish wastes into valuable functional substances. (C) 2017 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
Article
Green & Sustainable Science & Technology
Relative evaluation of probabilistic methods for spatio-temporal wind forecasting
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Comparison of ethane recovery processes for lean gas based on a coupled model
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
A novel deep-learning framework for short-term prediction of cooling load in public buildings
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION (2024)
分享论文
