Mapping aflatoxin risk from milk consumption using biophysical and socio-economic data: A case study of Kenya

Abstract

This research reports a mapping of aflatoxin risk in the milk value chain in Kenya using a geographic information systems (GIS) approach. The objective was to spatially locate regions at risk by taking into account biophysical and socioeconomic factors such as humidity and rainfall, dairy cattle density, maize production and travel time to urban centres. This was combined with historical data of aflatoxin outbreaks obtained from literature search and geo-referenced. Median values for the datasets were then used to define the thresholds. Criteria-based mapping using Boolean overlays without weighting was implemented in the ArcGIS v10.3 platform. Areas of convergence were overlaid with regions of historical outbreaks to come up with likely locations of aflatoxin risk and target sample surveys to these areas. Higher resolution maize production and consumption data would be desirable to ensure more accurate results. The process followed in this project ensures an evidence-based and replicable methodology that can be used in other regions and with different crops. Feed and milk samples collected in the different categories identified support that this approach can be used to guide sampling and regional studies. The research also discusses the strengths and limitations of the approach.

Kenya dairy farmer perception of moulds and mycotoxins and implications for exposure to aflatoxins: A gendered analysis

“…Mapping aflatoxin risk in the dairy chain in Kenya was carried out using a geographic information systems approach described by Ochungo et al [17]. The procedure spatially locates regions that are at risk by taking into account relevant socio-economic and biophysical factors.…”

“…The criteria applied were humidity, temperature, rainfall, dairy cattle density, feed resources, farming systems and consumption of maize and milk. Criteriabased mapping using Boolean overlays without weighting was then implemented in the ArcGIS V. 10.3 platform [17,18]. Areas of convergence for all data layers were overlaid with regions of historical outbreaks to come up with locations of likelihood of risk of mycotoxin exposure within the dairy value chain.…”

Fungal diversity and mycotoxins detected in maize stored in silo‐bags: a review

“…Mycotoxins are found in grain samples throughout the world, but the problem is greater in tropical and subtropical regions because high temperature and humidity levels favor their biosynthesis 6,76,77 . Mycotoxin contamination generates large economic losses, as well as negative impacts on human and domestic animal health 21 .…”

“…Mycotoxins are found in grain samples throughout the world, but the problem is greater in tropical and subtropical regions because high temperature and humidity levels favor their biosynthesis. 6,76,77 Mycotoxin contamination generates large economic losses, as well as negative impacts on human and domestic animal health. 21 The main criteria used to evaluate the economic impact of mycotoxin contamination are losses in value of crops and animal productivity, as well as human health costs.…”

Representing Cattle Farming around the World: A Conceptual and Holistic Framework for Environmental and Economic Impact Assessment

“…The three categories described by [30] are subdivided into mixed and solely livestock systems, as well as medium-to-large-scale (more than four cows) and small-scale systems (four or less cows) [31][32][33]. Low intensity middle-to-large scale mixed systems and solely livestock systems are described as grazing based, and are in the same regions.…”