Preliminary Assessment of Microalgae, Chlorella vulgaris, and Black Soldier Fly, Hermetia illucens Larvae, as a Viable Alternative Feed Combination for Red Hybrid Tilapia, Oreochromis sp. Culture.

This study evaluates the potential of microalgae, Chlorella vulgaris, and black soldier fly larvae (BSFL), Hermetia illucens, as an alternative complete diet for red hybrid tilapia, addressing challenges arising from declining fish stocks and unsustainable aquaculture practices reliant on fish meal in commercial pellets. The study involved 270 tilapia separated into three groups: Group 1 received C. vulgaris alone, Group 2 was fed with a combination of BSFL and C. vulgaris, and Group 3 with commercial pellets (control) for 70 days. The results demonstrated that the combination of BSFL and C. vulgaris had a high potential to be an alternative to commercial pellets, with comparable growth performance with the control group. In contrast, fish‐fed with C. vulgaris alone exhibited significantly slower growth rates and higher mortality. Economic analysis showed that the BSFL and C. vulgaris combination reduced feed costs by 59.40% and increased the profit index by 144.79% compared to the control group. However, the combination diet did not provide significant protection against streptococcosis compared to commercial pellets. This study highlights the potential of incorporating BSFL and C. vulgaris into tilapia diets to enhance sustainability and economic outcomes for farmers. It also emphasizes the role of alternative feeds in promoting environmentally sustainable aquaculture practices, with the goal of achieving zero‐carbon emissions. This study is the earliest report on the direct combination of BSFL and C. vulgaris diet in tilapia, a globally cultivated aquaculture fish species. [ABSTRACT FROM AUTHOR]

Copyright of Aquaculture Nutrition is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)