2022
DOI: 10.3389/fmicb.2022.907703
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Tracing and regulating redox homeostasis of model benthic ecosystems for sustainable aquaculture in coastal environments

Abstract: Aquaculture in coastal environments has an increasingly important role in the world’s food supply; however, the accumulation of organic compounds on seafloors due to overfeeding adversely affects benthic ecosystems. To assess the ecological resilience of aquafarms to nutrient influx, we investigated the redox homeostasis of benthic ecosystems using a marine oligochaete as a model benthic organism in aquaculture fields. Real-time monitoring of the redox potential of a model benthic ecosystem constructed in an e… Show more

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“…The Japanese study focuses on estuarine sediments and uses abundant sediment polypeptide and mineral profiles along with microbial structure to demonstrate significant estuarine eutrophication in the Kanto region [71] . In particular, such eutrophicated mad sediment can be evaluated by electronic potentials, such as redox homeostasis: thus, regulation of redox homeostasis can be one of the critical factors for environmental purification [72] . Another report describes a strategy for integrating and understanding the data obtained by omics analysis of surface water samples from 681 sites in Japan, grouped into three clusters, through machine learning, factor mapping, and predictive-error variance decomposition [73] .…”
Section: Applications To Various Ecosystemsmentioning
confidence: 99%
“…The Japanese study focuses on estuarine sediments and uses abundant sediment polypeptide and mineral profiles along with microbial structure to demonstrate significant estuarine eutrophication in the Kanto region [71] . In particular, such eutrophicated mad sediment can be evaluated by electronic potentials, such as redox homeostasis: thus, regulation of redox homeostasis can be one of the critical factors for environmental purification [72] . Another report describes a strategy for integrating and understanding the data obtained by omics analysis of surface water samples from 681 sites in Japan, grouped into three clusters, through machine learning, factor mapping, and predictive-error variance decomposition [73] .…”
Section: Applications To Various Ecosystemsmentioning
confidence: 99%