In aquaculture, feed represents the main component of production costs, and the development of this sector depends on the development of an economical feed formulation that meets the qualitative and quantitative requi...In aquaculture, feed represents the main component of production costs, and the development of this sector depends on the development of an economical feed formulation that meets the qualitative and quantitative requirements of fish. The aim of this study was to determine the nutritive and microbiological quality of fish feed formulated from local flours enriched with Hermetia illucens larvae. The raw materials used for formulation were fishmeal, corn meal, low-grade rice, soybean meal and Hermetia illucens larvae meal. Different iso-protein feed compositions were prepared with 0%, 10%, 25%, 35%, 50%, 65%, 75% and 100% incorporation of Hermetia illucens larvae meal as a substitute for fish meal. Biochemical and microbiological analyses of these flours were determined using standard methods. The results showed that incorporation of larvae meal had an influence on the biochemical characteristics ash (8.15 to 20.27%), lipid (11.55 to 24.94%), fiber (13.93 to 20.41%) and dry matter (89.65 to 91.19%) of various formulated feed. Loads of fecal Streptococci, Staphylococci, Aeromonas, yeasts and molds ranged from 2.4 to 4.9 log 10 CFU/g;3.6 to 3.9 log 10 CFU/g;2.2 to 2.7 log 10 CFU/g;2.1 to 2.3 log 10 CFU/g, respectively. The level of contamination of these flours was below the microbiological criteria applicable to animal feed. Feed formulated with 0% and 10% Hermetia illucens larvae showed the best nutritive and microbiological characteristics. These results suggest that flours enriched with Hermetia illucens larvae could be used in fish feed.展开更多
目的通过对人工智能在营养领域应用的核心文献进行可视化分析,旨在揭示该领域的知识结构、研究热点及发展趋势,为营养学研究提供参考。方法采用文献计量学方法,检索2016—2024年Web of Science数据库中相关文献,限定文献类型为论著或综...目的通过对人工智能在营养领域应用的核心文献进行可视化分析,旨在揭示该领域的知识结构、研究热点及发展趋势,为营养学研究提供参考。方法采用文献计量学方法,检索2016—2024年Web of Science数据库中相关文献,限定文献类型为论著或综述。使用CiteSpace 6.4.R1软件进行可视化分析,包括关键词共现、聚类、时间线及突现性分析,构建知识图谱,并分析作者、机构合作网络及研究主题。结果共纳入1896篇核心文献,发文量呈加速增长趋势,2021年后进入快速增长阶段,总增长率达到485.7%,平均年增长率为19.8%。核心作者78人,占全部研究者的25.74%,发表文献433篇,占文献总数的22.84%。研究机构主要集中在中美两国,其中美国的加州大学和哈佛大学,中国的中国科学院和中国医学科学院/协和医科大学在合作网络中处于核心位置。关键词分析显示“机器学习”“代谢综合征”“肠道微生物”等为高频词汇,累计词频占总词频的45.31%。关键词聚类分析形成11个主题聚类,涵盖慢性病风险评估、个性化膳食干预等关键应用场景。关键词突现性分析揭示研究热点从疾病与膳食关联分析向营养干预、心理健康及技术标准化方向演化。结论人工智能在营养领域的应用研究呈现多元化和精细化发展,未来需加强跨学科合作,推动技术应用的标准化和政策化。展开更多
文摘In aquaculture, feed represents the main component of production costs, and the development of this sector depends on the development of an economical feed formulation that meets the qualitative and quantitative requirements of fish. The aim of this study was to determine the nutritive and microbiological quality of fish feed formulated from local flours enriched with Hermetia illucens larvae. The raw materials used for formulation were fishmeal, corn meal, low-grade rice, soybean meal and Hermetia illucens larvae meal. Different iso-protein feed compositions were prepared with 0%, 10%, 25%, 35%, 50%, 65%, 75% and 100% incorporation of Hermetia illucens larvae meal as a substitute for fish meal. Biochemical and microbiological analyses of these flours were determined using standard methods. The results showed that incorporation of larvae meal had an influence on the biochemical characteristics ash (8.15 to 20.27%), lipid (11.55 to 24.94%), fiber (13.93 to 20.41%) and dry matter (89.65 to 91.19%) of various formulated feed. Loads of fecal Streptococci, Staphylococci, Aeromonas, yeasts and molds ranged from 2.4 to 4.9 log 10 CFU/g;3.6 to 3.9 log 10 CFU/g;2.2 to 2.7 log 10 CFU/g;2.1 to 2.3 log 10 CFU/g, respectively. The level of contamination of these flours was below the microbiological criteria applicable to animal feed. Feed formulated with 0% and 10% Hermetia illucens larvae showed the best nutritive and microbiological characteristics. These results suggest that flours enriched with Hermetia illucens larvae could be used in fish feed.
文摘目的通过对人工智能在营养领域应用的核心文献进行可视化分析,旨在揭示该领域的知识结构、研究热点及发展趋势,为营养学研究提供参考。方法采用文献计量学方法,检索2016—2024年Web of Science数据库中相关文献,限定文献类型为论著或综述。使用CiteSpace 6.4.R1软件进行可视化分析,包括关键词共现、聚类、时间线及突现性分析,构建知识图谱,并分析作者、机构合作网络及研究主题。结果共纳入1896篇核心文献,发文量呈加速增长趋势,2021年后进入快速增长阶段,总增长率达到485.7%,平均年增长率为19.8%。核心作者78人,占全部研究者的25.74%,发表文献433篇,占文献总数的22.84%。研究机构主要集中在中美两国,其中美国的加州大学和哈佛大学,中国的中国科学院和中国医学科学院/协和医科大学在合作网络中处于核心位置。关键词分析显示“机器学习”“代谢综合征”“肠道微生物”等为高频词汇,累计词频占总词频的45.31%。关键词聚类分析形成11个主题聚类,涵盖慢性病风险评估、个性化膳食干预等关键应用场景。关键词突现性分析揭示研究热点从疾病与膳食关联分析向营养干预、心理健康及技术标准化方向演化。结论人工智能在营养领域的应用研究呈现多元化和精细化发展,未来需加强跨学科合作,推动技术应用的标准化和政策化。
