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Proximate Content Monitoring of Black Soldier Fly Larval (Hermetia illucens) Dry Matter for Feed Material using Short-Wave Infrared Hyperspectral Imaging
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, i...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Food Science of Animal Resources
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636226/ https://www.ncbi.nlm.nih.gov/pubmed/37969323 http://dx.doi.org/10.5851/kosfa.2023.e33 |
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author | Kim, Juntae Kurniawan, Hary Faqeerzada, Mohammad Akbar Kim, Geonwoo Lee, Hoonsoo Kim, Moon Sung Baek, Insuck Cho, Byoung-Kwan |
author_facet | Kim, Juntae Kurniawan, Hary Faqeerzada, Mohammad Akbar Kim, Geonwoo Lee, Hoonsoo Kim, Moon Sung Baek, Insuck Cho, Byoung-Kwan |
author_sort | Kim, Juntae |
collection | PubMed |
description | 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(2) values of 0.89 or more, and root mean square error of prediction values were within 2%. Among preprocessing methods, mean normalization and max normalization methods were effective in proximate prediction models. Therefore, SWIR-based hyperspectral cameras can be used to create automated quality management systems for BSFL. |
format | Online Article Text |
id | pubmed-10636226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Korean Society for Food Science of Animal Resources |
record_format | MEDLINE/PubMed |
spelling | pubmed-106362262023-11-15 Proximate Content Monitoring of Black Soldier Fly Larval (Hermetia illucens) Dry Matter for Feed Material using Short-Wave Infrared Hyperspectral Imaging Kim, Juntae Kurniawan, Hary Faqeerzada, Mohammad Akbar Kim, Geonwoo Lee, Hoonsoo Kim, Moon Sung Baek, Insuck Cho, Byoung-Kwan Food Sci Anim Resour Special Section Articles 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(2) values of 0.89 or more, and root mean square error of prediction values were within 2%. Among preprocessing methods, mean normalization and max normalization methods were effective in proximate prediction models. Therefore, SWIR-based hyperspectral cameras can be used to create automated quality management systems for BSFL. Korean Society for Food Science of Animal Resources 2023-11 2023-11-01 /pmc/articles/PMC10636226/ /pubmed/37969323 http://dx.doi.org/10.5851/kosfa.2023.e33 Text en © Korean Society for Food Science of Animal Resources https://creativecommons.org/licenses/by-nc/3.0/This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Special Section Articles Kim, Juntae Kurniawan, Hary Faqeerzada, Mohammad Akbar Kim, Geonwoo Lee, Hoonsoo Kim, Moon Sung Baek, Insuck Cho, Byoung-Kwan Proximate Content Monitoring of Black Soldier Fly Larval (Hermetia illucens) Dry Matter for Feed Material using Short-Wave Infrared Hyperspectral Imaging |
title | Proximate Content Monitoring of Black Soldier Fly Larval
(Hermetia illucens) Dry Matter for Feed Material using
Short-Wave Infrared Hyperspectral Imaging |
title_full | Proximate Content Monitoring of Black Soldier Fly Larval
(Hermetia illucens) Dry Matter for Feed Material using
Short-Wave Infrared Hyperspectral Imaging |
title_fullStr | Proximate Content Monitoring of Black Soldier Fly Larval
(Hermetia illucens) Dry Matter for Feed Material using
Short-Wave Infrared Hyperspectral Imaging |
title_full_unstemmed | Proximate Content Monitoring of Black Soldier Fly Larval
(Hermetia illucens) Dry Matter for Feed Material using
Short-Wave Infrared Hyperspectral Imaging |
title_short | Proximate Content Monitoring of Black Soldier Fly Larval
(Hermetia illucens) Dry Matter for Feed Material using
Short-Wave Infrared Hyperspectral Imaging |
title_sort | proximate content monitoring of black soldier fly larval
(hermetia illucens) dry matter for feed material using
short-wave infrared hyperspectral imaging |
topic | Special Section Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636226/ https://www.ncbi.nlm.nih.gov/pubmed/37969323 http://dx.doi.org/10.5851/kosfa.2023.e33 |
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