Climate information systems (CIS) for aquaculture

The AICCRA project developed an air-water temperature relationship algorithm used to forecast pond water temperatures for integration with the data hub of the Intelligent Agricultural Systems Advisory Tool (iSAT) and an early temperature warning decision tree matrix. The project team will develop th...

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Autores principales: Stander, Henk, Greengrass, Catherine, Oladejo, Sunday, Watson, Bruce, Nel, Aldi, Salie, Khalid, Noris, Netsayi, Kakwasha, Keagan, Lundeba, Mary, Peerzadi, Rumana, Siamudaala, Victor
Formato: Artículo preliminar
Lenguaje:Inglés
Publicado: Accelerating Impacts of CGIAR Climate Research for Africa 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/159626
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author Stander, Henk
Greengrass, Catherine
Oladejo, Sunday
Watson, Bruce
Nel, Aldi
Salie, Khalid
Noris, Netsayi
Kakwasha, Keagan
Lundeba, Mary
Peerzadi, Rumana
Siamudaala, Victor
author_browse Greengrass, Catherine
Kakwasha, Keagan
Lundeba, Mary
Nel, Aldi
Noris, Netsayi
Oladejo, Sunday
Peerzadi, Rumana
Salie, Khalid
Siamudaala, Victor
Stander, Henk
Watson, Bruce
author_facet Stander, Henk
Greengrass, Catherine
Oladejo, Sunday
Watson, Bruce
Nel, Aldi
Salie, Khalid
Noris, Netsayi
Kakwasha, Keagan
Lundeba, Mary
Peerzadi, Rumana
Siamudaala, Victor
author_sort Stander, Henk
collection Repository of Agricultural Research Outputs (CGSpace)
description The AICCRA project developed an air-water temperature relationship algorithm used to forecast pond water temperatures for integration with the data hub of the Intelligent Agricultural Systems Advisory Tool (iSAT) and an early temperature warning decision tree matrix. The project team will develop the matrix into a dashboard based on input data and water quality parameter thresholds for critical scenarios for tilapia and catfish (Clarius Gariepinus). When predicted temperatures approach their thresholds, this activates a color-coded alarm corresponding with a specific action protocol to regulate pond temperatures. The purpose is to mitigate the impact of high-risk (24°C for minimum and 32°C for maximum) and emergency (12°C for minimum and 40°C for maximum) temperature scenarios on cultured stock.
format Artículo preliminar
id CGSpace159626
institution CGIAR Consortium
language Inglés
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher Accelerating Impacts of CGIAR Climate Research for Africa
publisherStr Accelerating Impacts of CGIAR Climate Research for Africa
record_format dspace
spelling CGSpace1596262025-11-11T17:10:01Z Climate information systems (CIS) for aquaculture Development of a temperature-based, early warning alert system for fish farmers in Zambia Stander, Henk Greengrass, Catherine Oladejo, Sunday Watson, Bruce Nel, Aldi Salie, Khalid Noris, Netsayi Kakwasha, Keagan Lundeba, Mary Peerzadi, Rumana Siamudaala, Victor aquaculture early warning systems climate resilience sustainable agriculture The AICCRA project developed an air-water temperature relationship algorithm used to forecast pond water temperatures for integration with the data hub of the Intelligent Agricultural Systems Advisory Tool (iSAT) and an early temperature warning decision tree matrix. The project team will develop the matrix into a dashboard based on input data and water quality parameter thresholds for critical scenarios for tilapia and catfish (Clarius Gariepinus). When predicted temperatures approach their thresholds, this activates a color-coded alarm corresponding with a specific action protocol to regulate pond temperatures. The purpose is to mitigate the impact of high-risk (24°C for minimum and 32°C for maximum) and emergency (12°C for minimum and 40°C for maximum) temperature scenarios on cultured stock. 2024-10 2024-11-12T20:44:26Z 2024-11-12T20:44:26Z Working Paper https://hdl.handle.net/10568/159626 en Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Stander, H., Greengrass, C., Oladejo, S., Watson, B., Nel, A., Salie, K., Mudege, N., Kakwasha, K., Lundeba, M., Hossain, R. P., Siamudaala, V. 2024. Climate information systems (CIS) for aquaculture. Development of a temperature-based, early warning alert system for fish farmers in Zambia. AICCRA Working Paper. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA).
spellingShingle aquaculture
early warning systems
climate resilience
sustainable agriculture
Stander, Henk
Greengrass, Catherine
Oladejo, Sunday
Watson, Bruce
Nel, Aldi
Salie, Khalid
Noris, Netsayi
Kakwasha, Keagan
Lundeba, Mary
Peerzadi, Rumana
Siamudaala, Victor
Climate information systems (CIS) for aquaculture
title Climate information systems (CIS) for aquaculture
title_full Climate information systems (CIS) for aquaculture
title_fullStr Climate information systems (CIS) for aquaculture
title_full_unstemmed Climate information systems (CIS) for aquaculture
title_short Climate information systems (CIS) for aquaculture
title_sort climate information systems cis for aquaculture
topic aquaculture
early warning systems
climate resilience
sustainable agriculture
url https://hdl.handle.net/10568/159626
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