Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement

The colour of seafood flesh is often not homogenous, hence measurement of colour requires repeat measurements to obtain a representative average. The aim of this study was to determine the optimal number of repeat colour measurements required for three different devices [machine vision (digital imag...

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Published in:Foods
Main Authors: Kieren Watkins, Melindee Hastie, Minh Ha, Graham Hepworth, Robyn Warner
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2024
Subjects:
Nix
Online Access:https://doi.org/10.3390/foods13071110
https://doaj.org/article/93a502e22ccb48889bba6d074541ab60
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spelling ftdoajarticles:oai:doaj.org/article:93a502e22ccb48889bba6d074541ab60 2024-09-15T17:56:28+00:00 Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement Kieren Watkins Melindee Hastie Minh Ha Graham Hepworth Robyn Warner 2024-04-01T00:00:00Z https://doi.org/10.3390/foods13071110 https://doaj.org/article/93a502e22ccb48889bba6d074541ab60 EN eng MDPI AG https://www.mdpi.com/2304-8158/13/7/1110 https://doaj.org/toc/2304-8158 doi:10.3390/foods13071110 2304-8158 https://doaj.org/article/93a502e22ccb48889bba6d074541ab60 Foods, Vol 13, Iss 7, p 1110 (2024) salmon rockling prawns fish Nix Minolta Chemical technology TP1-1185 article 2024 ftdoajarticles https://doi.org/10.3390/foods13071110 2024-08-05T17:49:37Z The colour of seafood flesh is often not homogenous, hence measurement of colour requires repeat measurements to obtain a representative average. The aim of this study was to determine the optimal number of repeat colour measurements required for three different devices [machine vision (digital image using camera, and computer processing); Nix Pro; Minolta CR400 colorimeter] when measuring three species of seafood (Atlantic salmon, Salmo salar , n = 8; rockling, Genypterus tigerinus , n = 8; banana prawns, Penaeus merguiensis , n = 105) for raw and cooked samples. Two methods of analysis for number of repeat measurements required were compared. Method 1 was based on minimising the standard error of the mean and Method 2 was based on minimising the difference in colour over repeat measurements. Across species, using Method 1, machine vision required an average of four repeat measurements, whereas Nix Pro and Minolta required 13 and 12, respectively. For Method 2, machine vision required an average of one repeat measurement compared to nine for Nix Pro and Minolta. Machine vision required fewer repeat measurements due to its lower residual variance: 0.51 compared to 3.2 and 2.5 for Nix Pro and Minolta, respectively. In conclusion, machine vision requires fewer repeat measurements than colorimeters to precisely measure the colour of salmon, prawns, and rockling. Article in Journal/Newspaper Atlantic salmon Salmo salar Directory of Open Access Journals: DOAJ Articles Foods 13 7 1110
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic salmon
rockling
prawns
fish
Nix
Minolta
Chemical technology
TP1-1185
spellingShingle salmon
rockling
prawns
fish
Nix
Minolta
Chemical technology
TP1-1185
Kieren Watkins
Melindee Hastie
Minh Ha
Graham Hepworth
Robyn Warner
Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
topic_facet salmon
rockling
prawns
fish
Nix
Minolta
Chemical technology
TP1-1185
description The colour of seafood flesh is often not homogenous, hence measurement of colour requires repeat measurements to obtain a representative average. The aim of this study was to determine the optimal number of repeat colour measurements required for three different devices [machine vision (digital image using camera, and computer processing); Nix Pro; Minolta CR400 colorimeter] when measuring three species of seafood (Atlantic salmon, Salmo salar , n = 8; rockling, Genypterus tigerinus , n = 8; banana prawns, Penaeus merguiensis , n = 105) for raw and cooked samples. Two methods of analysis for number of repeat measurements required were compared. Method 1 was based on minimising the standard error of the mean and Method 2 was based on minimising the difference in colour over repeat measurements. Across species, using Method 1, machine vision required an average of four repeat measurements, whereas Nix Pro and Minolta required 13 and 12, respectively. For Method 2, machine vision required an average of one repeat measurement compared to nine for Nix Pro and Minolta. Machine vision required fewer repeat measurements due to its lower residual variance: 0.51 compared to 3.2 and 2.5 for Nix Pro and Minolta, respectively. In conclusion, machine vision requires fewer repeat measurements than colorimeters to precisely measure the colour of salmon, prawns, and rockling.
format Article in Journal/Newspaper
author Kieren Watkins
Melindee Hastie
Minh Ha
Graham Hepworth
Robyn Warner
author_facet Kieren Watkins
Melindee Hastie
Minh Ha
Graham Hepworth
Robyn Warner
author_sort Kieren Watkins
title Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
title_short Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
title_full Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
title_fullStr Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
title_full_unstemmed Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement
title_sort machine vision requires fewer repeat measurements than colorimeters for precise seafood colour measurement
publisher MDPI AG
publishDate 2024
url https://doi.org/10.3390/foods13071110
https://doaj.org/article/93a502e22ccb48889bba6d074541ab60
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source Foods, Vol 13, Iss 7, p 1110 (2024)
op_relation https://www.mdpi.com/2304-8158/13/7/1110
https://doaj.org/toc/2304-8158
doi:10.3390/foods13071110
2304-8158
https://doaj.org/article/93a502e22ccb48889bba6d074541ab60
op_doi https://doi.org/10.3390/foods13071110
container_title Foods
container_volume 13
container_issue 7
container_start_page 1110
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