ArticleFood science of animal resources2023
Proximate Content Monitoring of Black Soldier Fly Larval (
Article in Food science of animal resources, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Monitoring of moisture content in meat emulsion using an SWIR hyperspectral imaging system.Food science of animal resources · 2026Article
- Dietary supplementation with black soldier fly (Hermetia illucens) larval meal modulates hepatic lipid homeostasis and reduces TNF-α expression in mice.Molecular biology reports · 2026Article
- Rapid feed component assessment to enhance livestock productivity and reduce emissions.Scientific reports · 2025Article
- Chitin Assessment in Insect-Based Products from Reference Methods to Near-Infrared Models.Insects · 2025Article
- Effects of Feeding Mandarin and Poultry By-Products on Growth Performance and Physicochemical Properties of Black Soldier Fly (Food science of animal resources · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Edible insects are gaining popularity as a potential future food source because of their high protein content and efficient use of space. Black soldier fly larvae (BSFL) are noteworthy because they can be used as feed for various animals including reptiles, dogs, fish, chickens, and pigs. However, if the edible insect industry is to advance, we should use automation to reduce labor and increase production. Consequently, there is a growing demand for sensing technologies that can automate the evaluation of insect quality. This study used short-wave infrared (SWIR) hyperspectral imaging to predict the proximate composition of dried BSFL, including moisture, crude protein, crude fat, crude fiber, and crude ash content. The larvae were dried at various temperatures and times, and images were captured using an SWIR camera. A partial least-squares regression (PLSR) model was developed to predict the proximate content. The SWIR-based hyperspectral camera accurately predicted the proximate composition of BSFL from the best preprocessing model; moisture, crude protein, crude fat, crude fiber, and crude ash content were predicted with high accuracy, with R
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Registered trials
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