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Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa

In 2008, the African Postharvest Losses Information Systems project (APHLIS, accessed on 6 September 2022) developed an algorithm for estimating the scale of cereal postharvest losses (PHLs). The relevant scientific literature and contextual information was used to build profiles of the PHLs occurri...

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Autores principales: Rembold, Felix, Mvumi, Brighton, Miller, David, Omari, Rose, Battilani, Paola, Galani, Yamdeu Joseph Hubert, Louw, Wiana, Falade, Titilayo D. O., Schweiger, Wolfgang, Ermolli, Monica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10054080/
https://www.ncbi.nlm.nih.gov/pubmed/36977065
http://dx.doi.org/10.3390/toxins15030174
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author Rembold, Felix
Mvumi, Brighton
Miller, David
Omari, Rose
Battilani, Paola
Galani, Yamdeu Joseph Hubert
Louw, Wiana
Falade, Titilayo D. O.
Schweiger, Wolfgang
Ermolli, Monica
author_facet Rembold, Felix
Mvumi, Brighton
Miller, David
Omari, Rose
Battilani, Paola
Galani, Yamdeu Joseph Hubert
Louw, Wiana
Falade, Titilayo D. O.
Schweiger, Wolfgang
Ermolli, Monica
author_sort Rembold, Felix
collection PubMed
description In 2008, the African Postharvest Losses Information Systems project (APHLIS, accessed on 6 September 2022) developed an algorithm for estimating the scale of cereal postharvest losses (PHLs). The relevant scientific literature and contextual information was used to build profiles of the PHLs occurring along the value chains of nine cereal crops by country and province for 37 sub-Saharan African countries. The APHLIS provides estimates of PHL figures where direct measurements are not available. A pilot project was subsequently initiated to explore the possibility of supplementing these loss estimates with information on the aflatoxin risk. Using satellite data on drought and rainfall, a time series of agro-climatic aflatoxin risk warning maps for maize was developed covering the countries and provinces of sub-Saharan Africa. The agro-climatic risk warning maps for specific countries were shared with mycotoxin experts from those countries for review and comparison with their aflatoxin incidence datasets. The present Work Session was a unique opportunity for African food safety mycotoxins experts, as well as other international experts, to meet and deepen the discussion about prospects for using their experience and their data to validate and improve agro-climatic risk modeling approaches.
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spelling pubmed-100540802023-03-30 Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa Rembold, Felix Mvumi, Brighton Miller, David Omari, Rose Battilani, Paola Galani, Yamdeu Joseph Hubert Louw, Wiana Falade, Titilayo D. O. Schweiger, Wolfgang Ermolli, Monica Toxins (Basel) Conference Report In 2008, the African Postharvest Losses Information Systems project (APHLIS, accessed on 6 September 2022) developed an algorithm for estimating the scale of cereal postharvest losses (PHLs). The relevant scientific literature and contextual information was used to build profiles of the PHLs occurring along the value chains of nine cereal crops by country and province for 37 sub-Saharan African countries. The APHLIS provides estimates of PHL figures where direct measurements are not available. A pilot project was subsequently initiated to explore the possibility of supplementing these loss estimates with information on the aflatoxin risk. Using satellite data on drought and rainfall, a time series of agro-climatic aflatoxin risk warning maps for maize was developed covering the countries and provinces of sub-Saharan Africa. The agro-climatic risk warning maps for specific countries were shared with mycotoxin experts from those countries for review and comparison with their aflatoxin incidence datasets. The present Work Session was a unique opportunity for African food safety mycotoxins experts, as well as other international experts, to meet and deepen the discussion about prospects for using their experience and their data to validate and improve agro-climatic risk modeling approaches. MDPI 2023-02-24 /pmc/articles/PMC10054080/ /pubmed/36977065 http://dx.doi.org/10.3390/toxins15030174 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Conference Report
Rembold, Felix
Mvumi, Brighton
Miller, David
Omari, Rose
Battilani, Paola
Galani, Yamdeu Joseph Hubert
Louw, Wiana
Falade, Titilayo D. O.
Schweiger, Wolfgang
Ermolli, Monica
Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title_full Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title_fullStr Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title_full_unstemmed Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title_short Abstracts of Presentations to the Working Session on Improving Predictive Modeling of Mycotoxin Risk for Africa Held at the 3rd ASM2022 on 7 September 2022, in Stellenbosch, South Africa
title_sort abstracts of presentations to the working session on improving predictive modeling of mycotoxin risk for africa held at the 3rd asm2022 on 7 september 2022, in stellenbosch, south africa
topic Conference Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10054080/
https://www.ncbi.nlm.nih.gov/pubmed/36977065
http://dx.doi.org/10.3390/toxins15030174
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