AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients.
Soya bean meal-induced enteritis (SBMIE) is a well-documented condition observed in distal intestine (DI) on Atlantic salmon (Salmo salar) fed with unprocessed soya. Many of the current studies describing inflammation in DI of Atlantic salmon fed unprocessed soya bean meal (SBM) utilize a semi-quant...
Main Author: | |
---|---|
Other Authors: | , , |
Format: | Master Thesis |
Language: | English |
Published: |
uis
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/11250/3088945 |
id |
ftunivstavanger:oai:uis.brage.unit.no:11250/3088945 |
---|---|
record_format |
openpolar |
spelling |
ftunivstavanger:oai:uis.brage.unit.no:11250/3088945 2023-10-09T21:49:53+02:00 AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. Stalvik, Mathias van der Giezen, Mark Eriksen, Tommy Berger Crappe, Delphine 2023 application/pdf https://hdl.handle.net/11250/3088945 eng eng uis no.uis:inspera:135003965:35964303 https://hdl.handle.net/11250/3088945 Master thesis 2023 ftunivstavanger 2023-09-13T22:43:38Z Soya bean meal-induced enteritis (SBMIE) is a well-documented condition observed in distal intestine (DI) on Atlantic salmon (Salmo salar) fed with unprocessed soya. Many of the current studies describing inflammation in DI of Atlantic salmon fed unprocessed soya bean meal (SBM) utilize a semi-quantitative scoring system for histological assessment, which is considered the gold standard. This thesis investigates if a quantitative assessment using image analysis with artificial intelligence (AI) can produce similar results as with semi-quantitative scoring systems. This study provides evidence that the results for assessing inflammation in the DI extracted from image analysis using AI correlate to results from similar studies utilizing semi-quantitative scoring systems. A standard diet not containing unprocessed SBM and a diet containing 25% SBM was used as control diets. Six experimental diets all containing 25% unprocessed SBM were supplemented with different inclusion levels of two phytogenic ingredients with anti-inflammatory characteristics. Atlantic salmon were distributed into 24 different experimental tanks and fed for 56 days. There was no significant effect from the experimental diets, as all the fish fed with SBM experienced severe morphological changes in the DI. The observed morphological changes indicated a decrease in the number of mucous, vacuoles and absorptive area fraction. An increase for lamina propria, EGC, IgD and apoptosis area fraction was also observed for fish fed with SBM. In total weight gained during the experimental trial, a significant difference was observed for the Atlantic salmon not receiving SBM as they gained 25.4% more weight. Master Thesis Atlantic salmon Salmo salar University of Stavanger: UiS Brage |
institution |
Open Polar |
collection |
University of Stavanger: UiS Brage |
op_collection_id |
ftunivstavanger |
language |
English |
description |
Soya bean meal-induced enteritis (SBMIE) is a well-documented condition observed in distal intestine (DI) on Atlantic salmon (Salmo salar) fed with unprocessed soya. Many of the current studies describing inflammation in DI of Atlantic salmon fed unprocessed soya bean meal (SBM) utilize a semi-quantitative scoring system for histological assessment, which is considered the gold standard. This thesis investigates if a quantitative assessment using image analysis with artificial intelligence (AI) can produce similar results as with semi-quantitative scoring systems. This study provides evidence that the results for assessing inflammation in the DI extracted from image analysis using AI correlate to results from similar studies utilizing semi-quantitative scoring systems. A standard diet not containing unprocessed SBM and a diet containing 25% SBM was used as control diets. Six experimental diets all containing 25% unprocessed SBM were supplemented with different inclusion levels of two phytogenic ingredients with anti-inflammatory characteristics. Atlantic salmon were distributed into 24 different experimental tanks and fed for 56 days. There was no significant effect from the experimental diets, as all the fish fed with SBM experienced severe morphological changes in the DI. The observed morphological changes indicated a decrease in the number of mucous, vacuoles and absorptive area fraction. An increase for lamina propria, EGC, IgD and apoptosis area fraction was also observed for fish fed with SBM. In total weight gained during the experimental trial, a significant difference was observed for the Atlantic salmon not receiving SBM as they gained 25.4% more weight. |
author2 |
van der Giezen, Mark Eriksen, Tommy Berger Crappe, Delphine |
format |
Master Thesis |
author |
Stalvik, Mathias |
spellingShingle |
Stalvik, Mathias AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
author_facet |
Stalvik, Mathias |
author_sort |
Stalvik, Mathias |
title |
AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
title_short |
AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
title_full |
AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
title_fullStr |
AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
title_full_unstemmed |
AI-based image analysis for detecting inflammation in distal intestine samples from Atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
title_sort |
ai-based image analysis for detecting inflammation in distal intestine samples from atlantic salmon and investigating the anti-inflammatory potential of phytogenic ingredients. |
publisher |
uis |
publishDate |
2023 |
url |
https://hdl.handle.net/11250/3088945 |
genre |
Atlantic salmon Salmo salar |
genre_facet |
Atlantic salmon Salmo salar |
op_relation |
no.uis:inspera:135003965:35964303 https://hdl.handle.net/11250/3088945 |
_version_ |
1779312924660072448 |