article · Asian Journal of Scientific Research
Background and Objective: Municipal solid waste management has always been challenging in developing countries.Numerous waste management technologies, including landfill operations, pyrolysis and incineration are now available.However, these technologies frequently come with drawbacks (operational and maintenance issues) and have detrimental effects on the environment.In this regard, ongoing work is being done to create environmentally friendly technologies to address waste management issues.In response to these difficulties, Black Soldier Fly Larval (BSFL) biodegradation has emerged as an outstanding green waste management strategy.It hasnʼt, however, received much research.Therefore, the current study was to investigate the efficiency of larval treatment on a substrate containing varying proportions of water hyacinth, fruit waste and manure.Materials and Methods: Five feeding trays with different proportions of water hyacinth, fruit waste and manure were 65:25:10 (T1), 50:40:10 (T2), 35:55:10 (T3), 15:75:10 (T4) and 10:80:10 (T5), respectively.The percentage biomass conversion ratio (BCR), the effectiveness of waste reduction and the percentage growth of larvae were measured.Complete Randomized Design (CRD) was used in the experimentʼs design.Results: So, with a 2050% increase in initial larvae weight, 85.4% waste reduction efficiency and a biomass conversion rate of 30.71%,T3 had the best outcomes, followed by T5, T4, T2 and T1.The BSFLʼs growth performance, waste reduction effectiveness and biomass conversion ratio were remarkably high.The highest growth performance, reduction efficiency and conversion ratio of larvae reared on water hyacinth, fruit waste and manure may be attributed to a nutritionally balanced diet.Conclusion: Therefore, the different proportions of water hyacinth, fruit waste and manure fed to larvae significantly influence the percentage growth performance, waste reduction efficiency and biomass conversion ratio of the larvae.
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DOI: 10.3923/ajsr.2023.1.8
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