Safety assurance and nutritional quality enhancement of Phyllospora comosa biomass using hydrothermal treatment derived ensemble machine learning models

One of the major barriers to the mass industrial utilisation of brown seaweeds as food sources stem from the food safety risks associated with their iodine and arsenic concentrations, which typically exceed regulatory limits. Hydrothermal treatments might effectively reduce the high iodine and arsenic concentration of Phyllospora comosa below the Australian maximum residual limits (iodine = 1 mg/g and arsenic = 0.00667 mg/g; dry weight) set for brown seaweeds. The experimental hydrothermal treatments dictated that the 82 °C–250 s treatment reduced the iodine concentration from 2.76 mg/g to 0.88 mg/g (68% reduction) and arsenic concentration from 0.01693 mg/g to 0.00965 mg/g (43% reduction). Machine learning models predicted that blanching at 100 °C for ∼4 minutes will reduce the arsenic concentration below its maximum residual limit. Additive log-ratio transformations showed that around 50% (dw) of the hydrothermally treated Phyllospora comosa samples were leached out during the highest treatment intensity, 82 °C–250 s. Even though, a half of the biomass is lost, hydrothermally treated Phyllospora comosa products are safer for human consumption and thus may permit the expansion of seaweed production and consumption in Australia.

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Publication Details

Journal
Food Control
Published
2024-08-13
DOI
https://doi.org/10.1016/j.foodcont.2024.110802
Citations
5
Primary Topic
Date Palm Research Studies
Type
article
Field-Weighted Citation Impact
3.00

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article

Safety assurance and nutritional quality enhancement of Phyllospora comosa biomass using hydrothermal treatment derived ensemble machine learning models

David S. Francis, Thomas S. Mock, Damien L. Callahan, Thiru Chenduran Somasundaram
5 citations
Food Control
Date Palm Research Studies
3.00
article

Safety assurance and nutritional quality enhancement of Phyllospora comosa biomass using hydrothermal treatment derived ensemble machine learning models

David S. Francis, Thomas S. Mock, Damien L. Callahan, Thiru Chenduran Somasundaram
article en
5 citations

Abstract

One of the major barriers to the mass industrial utilisation of brown seaweeds as food sources stem from the food safety risks associated with their iodine and arsenic concentrations, which typically exceed regulatory limits. Hydrothermal treatments might effectively reduce the high iodine and arsenic concentration of Phyllospora comosa below the Australian maximum residual limits (iodine = 1 mg/g and arsenic = 0.00667 mg/g; dry weight) set for brown seaweeds. The experimental hydrothermal treatments dictated that the 82 °C–250 s treatment reduced the iodine concentration from 2.76 mg/g to 0.88 mg/g (68% reduction) and arsenic concentration from 0.01693 mg/g to 0.00965 mg/g (43% reduction). Machine learning models predicted that blanching at 100 °C for ∼4 minutes will reduce the arsenic concentration below its maximum residual limit. Additive log-ratio transformations showed that around 50% (dw) of the hydrothermally treated Phyllospora comosa samples were leached out during the highest treatment intensity, 82 °C–250 s. Even though, a half of the biomass is lost, hydrothermally treated Phyllospora comosa products are safer for human consumption and thus may permit the expansion of seaweed production and consumption in Australia.

Food ControlVol. 167
Deakin University (AU)
Deakin University, School of Life and Environmental Sciences, Deakin University
Zero hunger
Openalex Percentile: Top 9%
Date Palm Research Studies
3.00
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